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Conferences, Lectures, & Seminars
Events for November
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CS Colloquium: Fei Miao - Learning and Control for Safety, Efficiency, and Resiliency of Embodied AI
Wed, Nov 01, 2023 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Fei Miao, University of Connecticut
Talk Title: Learning and Control for Safety, Efficiency, and Resiliency of Embodied AI
Series: CS Colloquium
Abstract: With rapid evolution of sensing, communication, and computation, integrating learning and control presents significant Embodied AI opportunities. However, current decision-making frameworks lack comprehensive understanding of the tridirectional relationship among communication, learning and control, posing challenges for multi-agent systems in complex environments. In the first part of the talk, we focus on learning and control with communication capabilities. We design an uncertainty quantification method for collaborative perception in connected autonomous vehicles (CAVs). Our findings demonstrate that communication among multiple agents can enhance object detection accuracy and reduce uncertainty. Building upon this, we develop a safe and scalable deep multi-agent reinforcement learning (MARL) framework that leverages shared information among agents to improve system safety and efficiency. We validate the benefits of communication in MARL, particularly in the context of CAVs in challenging mixed traffic scenarios. We incentivize agents to communicate and coordinate with a novel reward reallocation scheme based on Shapley value for MARL. Additionally, we present our theoretical analysis of robust MARL methods under state uncertainties, such as uncertainty quantification in the perception modules or worst-case adversarial state perturbations. In the second part of the talk, we briefly outline our research contributions on robust MARL and data-driven robust optimization for sustainable mobility. We also highlight our research results concerning CPS security. Through our findings, we aim to advance Embodied AI and CPS for safety, efficiency, and resiliency in dynamic environments.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Fei Miao is Pratt & Whitney Associate Professor of the Department of Computer Science and Engineering, a Courtesy Faculty of the Department of Electrical & Computer Engineering, University of Connecticut, where she joined in 2017. She is affiliated to the Institute of Advanced Systems Engineering and Eversource Energy Center. She was a postdoc researcher at the GRASP Lab and the PRECISE Lab of Upenn from 2016 to 2017. She received Ph.D. degree and the Best Doctoral Dissertation Award in Electrical and Systems Engineering, with a dual M.S. degree in Statistics from the University of Pennsylvania in 2016. She received the B.S. degree in Automation from Shanghai Jiao Tong University in 2010. Her research focuses on multi-agent reinforcement learning, robust optimization, uncertainty quantification, and game theory, to address safety, efficiency, robustness, and security challenges of Embodied AI and CPS, for systems such as connected autonomous vehicles, sustainable and intelligent transportation systems, and smart cities. Dr. Miao is a receipt of the NSF CAREER award and a couple of other awards from NSF. She received the Best Paper Award and Best Paper Award Finalist at the 12th and 6th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) in 2021 and 2015, Best paper Award at the 2023 AAAI DACC workshop, respectively.
Host: Heather Culbertson
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
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AME Seminar
Wed, Nov 01, 2023 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Nikhil Admal, University of Illinois Urbana-Champaign
Talk Title: TBD
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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NL Seminar- What We Learned from 570K ChatGPT Interaction Logs In The Wild
Thu, Nov 02, 2023 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Wenting Zhao, Cornell University
Talk Title: What We Learned from 570K ChatGPT Interaction Logs In The Wild
Series: NL Seminar
Abstract: Reminder: Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom. If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we will be aware of your attendance and let you in. In-person attendance will be permitted for USC/ISI faculty, staff, students only. Open to the public virtually via the zoom link. More Info: https://nlg.isi.edu/nl-seminar/ Chatbots such as GPT 4 and ChatGPT are currently serving millions of users. Despite their widespread use, there remains a lack of public datasets that showcase how these tools are used by users in practice. In this talk, I will introduce in the WildChat, a corpus of 570K user ChatGPT conversations, which comprises over 1.5 million interaction turns. I will show that, compared to other popular user-chatbot interaction datasets, WildChat offers the most diverse user prompts and presents the richest variety of potentially toxic use-cases. Finally, I will demonstrate the potential utility of this dataset in fine-tuning state-of-the-art instruction following models.
Biography: Wenting Zhao is a Ph.D. candidate in Computer Science at Cornell University. Her research focuses on improving reasoning capabilities of large language models by exploiting explicit problem structures. She organizes an ACL tutorial on complex reasoning over Natural Language and the second workshop on Natural Language Reasoning and Structured Explanations. She has done internships at IBM Research, Amazon Alexa, and AI2 Mosaic.
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://youtu.be/lx1XcTdhalULocation: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://youtu.be/lx1XcTdhalU
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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Adaptive Attention: Bringing Active Vision into the Camera - Prof. Sanjeev Koppal
Thu, Nov 02, 2023 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sanjeev Koppal, University of Florida
Talk Title: Adaptive Attention: Bringing Active Vision into the Camera
Abstract: Most cameras today capture images without considering scene content. In contrast, animal eyes have fast mechanical movements that control how the scene is imaged in detail by the fovea, where visual acuity is highest. The prevalence of active vision during biological imaging, and the wide variety of it, makes it very clear that this is an effective visual design strategy. In this talk, I cover our recent work on creating *both* new camera designs and novel vision algorithms to enable adaptive and selective active vision and imaging inside cameras and sensors.
Biography: Sanjeev J. Koppal is an Associate Professor at the University of Florida’s Electrical and Computer Engineering Department and is a Kent and Linda Fuchs Faculty Fellow. He also holds a UF Term Professorship for 2021-23. Sanjeev is the Director of the FOCUS Lab at UF. Since 2022, Sanjeev has been an Amazon Scholar with Amazon Robotics. Prior to joining UF, he was a researcher at the Texas Instruments Imaging R&D lab. Sanjeev obtained his Masters and Ph.D. degrees from the Robotics Institute at Carnegie Mellon University. After CMU, he was a postdoctoral research associate in the School of Engineering and Applied Sciences at Harvard University. He received his B.S. degree from the University of Southern California in 2003 as a Trustee Scholar. He is a co-author on best student paper awards for ECCV 2016 and NEMS 2018, and work from his FOCUS lab was a CVPR 2019 best-paper finalist. Sanjeev won an NSF CAREER award in 2020 and is an IEEE Senior Member and an Optica Senior Member. His interests span computer vision, computational photography and optics, novel cameras and sensors, 3D reconstruction, physics-based vision, and active illumination
Host: Gaurav S. Sukhatme
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
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Intro to Blockchain Hands-On-Workshop
Thu, Nov 02, 2023 @ 06:00 PM - 07:00 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Join us for a hands-on workshop with Blockchain@USC to learn about blockchain in the world today. Create your own metamask wallet!
Location: Sign into EngageSC to View Location
Audiences: Everyone Is Invited
Contact: Thelma Federico Zaragoza
Event Link: https://engage.usc.edu/WIE/rsvp?id=393345
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Nov 03, 2023 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Heather Clark, Director of the School for Biological and Health Systems Engineering at Arizona State University
Talk Title: "Nanosensors for Imaging the Chemistry of the Body"
Abstract: My group is currently working at the interface of chemistry and biology to develop and apply novel nanoscale probes for biological measurements. In order to fulfill our goal of chemical imaging deep in the body (brain, central nervous system, circulatory system) we are we are tailoring our sensors to be compatible with advanced imaging techniques (diffuse in vivo flow cytometry, photoacoustics, or MRI) to image deep in the body. Ultimately, we will use the probes to image specific chemical processes and biomarkers in the brain/body, in real-time. I will discuss two projects that image real-time signaling in the body. The first is a fluorescent probe to measure acetylcholine in the peripheral nervous system, the second is a red blood cell cloaked sensor for sodium that circulates in the blood stream.
Biography: Heather Clark is the Director of the School for Biological and Health Systems Engineering at Arizona State University and an Associate Editor at ACS Sensors. Previously, she was a Professor at Northeastern University where she was the Founding Director of the Institute for Chemical Imaging of Living Systems. She received her PhD in Analytical Chemistry from the University of Michigan and completed a postdoc in the Center for Cell Analysis & Modeling at the University of Connecticut Health Center. She is a AIMBE Fellow and has received awards for both research and teaching, including the DARPA Young Faculty Award. Her work has been featured in a live CNN interview, the Wall Street Journal, WIRED magazine and MIT Technology Review.
Host: Maral Mousavi
More Info: zoom link available upon request
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Carla Stanard
Event Link: zoom link available upon request
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MHI ISSS Seminar - Dr. Sudipto Chakraborty, Friday, Nov 3rd at 2pm in EEB132
Fri, Nov 03, 2023 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sudipto Chakraborty, IBM T.J. Watson Research Center
Talk Title: Low power cryo-CMOS design for quantum computing applications
Series: Integrated Systems
Abstract: This talk will cover practical challenges for cryogenic CMOS designs for next generation quantum computing. Starting from system level, it will detail the design considerations for a non-multiplexed, semi-autonomous, transmon qubit state controller (QSC) implemented in 14nm CMOS FinFET technology. The QSC includes an augmented general-purpose digital processor that supports waveform generation and phase rotation operations combined with a low power current-mode single sideband upconversion I/Q mixer-based RF arbitrary waveform generator (AWG). Implemented in 14nm CMOS FinFET technology, the QSC generates control signals in its target 4.5GHz to 5.5 GHz frequency range, achieving an SFDR > 50dB for a signal bandwidth of 500MHz. With the controller operating in the 4K stage of a cryostat and connected to a transmon qubit in the cryostat's millikelvin stage, measured transmon T1 and T2 coherence times were 75.5uS and 73 uS, respectively, in each case comparable to results achieved using conventional room temperature controls. In further tests with transmons, a qubit-limited error rate of 7.76x10-4 per Clifford gate is achieved, again comparable to results achieved using room temperature controls. The QSC's maximum RF output power is -18 dBm, and power dissipation per qubit under active control is 23mW.
Biography: Sudipto Chakraborty received his B. Tech from Indian Institute of Technology, Kharagpur in 1998 and Ph.D in EE from Georgia Institute of Technology in 2002. He worked as a researcher in Georgia Electronic Design Center (GEDC) till 2004. From 2004 to 2016, he was a senior member of technical staff at Texas Instruments where he contributed to low power integrated circuit design in more than 10 product families in the areas of automotive, wireless, medical and microcontrollers. Since 2017, he has been working at the IBM T. J. Watson Research Center where he leads the low power circuit design for next generation quantum computing applications using nano CMOS technology nodes. He has authored or co-authored more than 75 papers, two books and holds 87 US patents. He has served in the technical program committees of various conferences including CICC, RFIC, IMS and has been elected as an IBM master inventor in 2022 for his contributions.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Information: Chaitali Joshi Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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ECE Seminar: QMC of everything: A universal algorithm for simulating arbitrary quantum many-body systems
Tue, Nov 07, 2023 @ 01:00 PM - 02:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Itay Hen, Principal Scientist, USC Viterbi Information Sciences Institute
Talk Title: QMC of everything: A universal algorithm for simulating arbitrary quantum many-body systems
Abstract: Gaining insight into the equilibrium properties of quantum many-body systems is essential for advancing our understanding of fundamental physics, materials science, and a wide range of scientific and technological applications. Quantum Monte Carlo (QMC) techniques are, in the majority of cases, the only viable approach to developing a systematic understanding of large-scale quantum systems. However, current QMC schemes have limitations, with a major one being the need to tailor distinct, specific updates to each model to ensure the ergodicity of the stochastic process. In this talk, I will discuss a novel, universal, parameter-free QMC algorithm capable of simulating arbitrarily conceived physical models, including models containing mixtures of particle types and interactions in arbitrary geometries. This work is a collaboration with Lev Barash (ISI) and Arman Babakhani (Physics Dept. and ISI).
Biography: Itay Hen is a Principal Scientist at Viterbi's Information Sciences Institute, where he leads the computational physics group. He also holds an adjunct appointment as a research associate professor in the Department of Physics and Astronomy. Dr. Hen's main areas of research are quantum computing, specifically quantum simulation algorithms, and computational physics, particularly quantum many-body simulations and optimization. He currently serves as the PI for several quantum computing-related projects sponsored by DARPA, the Department of Energy, and the NSF. Dr. Hen earned his Ph.D. in particle physics from Tel-Aviv University in 2009. He then held a postdoctoral fellowship in theoretical condensed matter at Georgetown University and later completed another postdoctoral fellowship in theoretical condensed matter and quantum computing at UC Santa Cruz in 2012. Before joining USC in 2013, Dr. Hen spent a year as a senior scientist in the Intelligent Systems Division at NASA Ames Research Center as a member of the Quantum Artificial Intelligence Laboratory.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/99781295519?pwd=RVFOelJUbVhJS0pPek5RcERpc3RvQT09More Information: ECE-Seminar-Hen-110723.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/99781295519?pwd=RVFOelJUbVhJS0pPek5RcERpc3RvQT09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 07, 2023 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Esteban Moro , Researcher, Data Scientist -“ MIT Connection Science at IDSS and Associate Professor -“ Universidad Carlos III (UC3M), Spain
Talk Title: Understanding Urban Social Resilience Through Behavioral Mobility Data
Host: Dr. Abigail Horn
More Information: November 7, 2023.pdf
Location: SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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SERC Seminar
Tue, Nov 07, 2023 @ 05:00 PM - 06:20 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: Justin Walsh , Chapman University
Talk Title: Human Heritage in Outer Space: Problems and Opportunities
Abstract: Humans have been sending all kinds of objects -“ from crewed spacecraft to nanosatellites to robotic rovers (and more) - into space for 66 years. Some of those objects have been imbued with significant meaning due to technological developments, historical events, and/or cultural associations, making it possible to include them among the items we consider to be HERITAGE. This lecture will consider the range of items in space that might be called heritage, their legal status (including the possibility of protecting them), and challenges and opportunities for documenting them. Can Tranquility Base be a National Park? How do we balance the preservation of satellites like the Hubble Space Telescope with the need to clean up space debris?
Biography: Justin Walsh is a professor of art, history, archaeology, and space studies at Chapman University and an Ad Astra Fellow in Space Habitats and Space Anthropology at SERC.
Host: ASTE Department
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116
Audiences: Everyone Is Invited
Contact: Dell Cuason
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Distinguished Lecturer Series: Dr. David Patterson
Wed, Nov 08, 2023 @ 03:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. David Patterson, UC Berkeley Pardee Professor of Computer Science, Emeritus | Vice Chair of the Board of Directors of RISC-V Foundation
Talk Title: A Decade of Machine Learning Accelerators: Lessons Learned and Carbon Footprint
Abstract: The success of deep neural networks (DNNs) from Machine Learning (ML) has inspired domain specific architectures (DSAs) for them. Google's first-generation DSA offered 50x improvement over conventional architectures for ML inference in 2015. Google next built the first production DSA supercomputer for the much harder problem of training. Subsequent generations greatly improved performance of both phases. We start with ten lessons learned from such efforts.
The rapid growth of DNNs rightfully raised concerns about their carbon footprint. The second part of the talk identifies the "4Ms" (Model, Machine, Mechanization, Map) that, if optimized, can reduce ML training energy by up to 100x and carbon emissions up to 1000x. By improving the 4Ms, ML held steady at
Biography: David Patterson is a UC Berkeley Pardee professor emeritus, a Google distinguished engineer, and the RISC-V International Vice-Chair. His most influential Berkeley projects likely were RISC (Reduced Instruction Set Computer) and RAID (Redundant Array of Inexpensive Disks). His best-known book is Computer Architecture: A Quantitative Approach. He and his co-author John Hennessy shared the 2017 ACM A.M Turing Award and the 2022 NAE Charles Stark Draper Prize for Engineering. The Turing Award is often referred to as the "Nobel Prize of Computing" and the Draper Prize is considered a "Nobel Prize of Engineering."
Host: Drs. Timothy Pinkston, Arash Saifhashemi
Location: EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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AME Seminar
Wed, Nov 08, 2023 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Geno Pawlak, UCSD
Talk Title: The Coastal Ocean Boundary Layer: Cross-shore structure, bottom roughness and trapped baroclinic waves
Abstract: In this talk I will describe analysis of the cross shore structure of the coastal ocean boundary layer using velocity measurements from an autonomous underwater vehicle (AUV) along with time series observations of the alongshore pressure gradient. Ensemble phase averages of the alongshore pressure gradient and velocities from multiple AUV surveys reveal characteristics akin to the Stokes oscillating boundary layer, with the nearshore flow leading the offshore flow in phase and with a corresponding velocity attenuation at shallower depths. Analysis of the alongshore momentum balance allows estimation of the drag coefficient as a function of cross shore distance which compares favorably with roughness from LIDAR and AUV based mapping. Roughness data suggest that larger scales, with wavelengths comparable to the total depth, play a more significant role than smaller meter scale roughness in determining the drag on the tidal flow. I will also present observations that highlight the role of coastal trapped baroclinic waves in driving barotropic tidal flow on the inner shelf.
Biography: Before joining the Jacobs School of Engineering, Pawlak served as an associate professor in the Department of Ocean and Resources Engineering at the University of Hawaii at Manoa. Pawlak is a UC San Diego alumnus, having earned his Ph.D. from the Department of Applied Mechanics and Engineering Sciences (now mechanical and aerospace engineering) here in 1997.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09 Meeting ID: 981 2114 1178 Passcode: NhXrDOqQU8
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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NL Seminar - Manipulating Large Language Model Predictions Through Data
Thu, Nov 09, 2023 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Alexander Wan, University of Cal-Berkeley
Talk Title: Manipulating Large Language Model Predictions Through Data
Series: NL Seminar
Abstract: This talk will be a live presentation only, it will not be recorded.
REMINDER: Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom.
If you’re an outside visitor, please provide your: Full Name, Title and Name of Workplace to (nlg-seminar-host(at)isi.edu) beforehand so we’ll be aware of your attendance. Also, let us know if you plan to attend in-person or virtually.
More Info on NL Seminars can be found at: https://nlg.isi.edu/nl-seminar/
Large language models use large amounts of unmoderated data at each stage of the training and deployment pipeline. In this talk, I will show how these lax requirements enable adversaries to manipulate both training and test data, allowing a myriad of possible attacks. First, during training time, I will show that adversaries can modify instruction-tuning datasets to systematically manipulate predictions across a range of tasks or induce degenerate outputs across hundreds of arbitrary tasks, using as few as 100 poison examples. At inference time, additional data is often used in retrieval- or tool-augmented models. Naturally, these models will face information from a wide variety of sources that have varying degrees of quality. Humans are also faced with this same range of sources but can make judgements of trustworthiness based on factors like the style of argumentation or the recency of information. We show that not only do model predictions differ significantly from human credibility judgements, but also that gaps in this judgement creates opportunities for adversaries to manipulate answers to user queries.
Biography: Alexander Wan is a third-year undergraduate at UC Berkeley majoring in Computer Science, Statistics, and Mathematics. He works closely with folks at the Berkeley NLP Group and the MSU Heterogeneous Learning and Reasoning lab, with a focus on improving the robustness and interpretability of large language models. He's also more broadly interested in the intersection of machine learning and cognitive science: using current ML models to better understand human cognition and building more robust models through cognitively inspired architectures and training.
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://usc.zoom.us/j/95174101995Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://usc.zoom.us/j/95174101995
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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CAIS Webinar: A Carative Approach to AI Governance
Thu, Nov 09, 2023 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Kush R. Varshney, IBM Research
Talk Title: A Carative Approach to AI Governance
Abstract: In recent times, we often hear a call for the governance of AI systems, but what does that really mean? In this talk, I will first adopt a control theory perspective to explain governance that determines the reference input via value alignment, data scientists acting as the controller to meet the values in a machine learning system, and facts captured in transparent documentation as the feedback signal. I will then adopt a nursing theory perspective to explain how the control theory perspective lacks caring and the need for a carative approach that starts with the real world problem as experienced by the most vulnerable people. I will conclude with an example of a project on using machine learning to evaluate applicants for home solar panel systems in rural India.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Kush R. Varshney is a distinguished research scientist and senior manager at IBM Research -“ T. J. Watson Research Center where he leads the Trustworthy Machine Intelligence department and the IBM Science for Social Good initiative
Register for the Zoom webinar here: https://usc.zoom.us/webinar/register/WN_p39kMQKnTaKdaJRKNox5uQ
Host: CAIS
More Info: https://usc.zoom.us/webinar/register/WN_p39kMQKnTaKdaJRKNox5uQ
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/webinar/register/WN_p39kMQKnTaKdaJRKNox5uQ
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Civil and Environmental Department Seminar Series
Thu, Nov 09, 2023 @ 02:00 PM - 03:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Babak Moaveni, Tufts University
Talk Title: Digital Twinning of Offshore Wind Turbines Using Vibration Measurements
Host: Dr. Audrey Olivier
More Info: https://usc.zoom.us/j/91558672174
Location: Zoom Only
Audiences: Everyone Is Invited
Contact: Salina Palacios
Event Link: https://usc.zoom.us/j/91558672174
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Civil and Environmental Department Seminar Series
Thu, Nov 09, 2023 @ 02:00 PM - 03:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Babak Moaveni, Tufts University
Talk Title: Digital Twinning of Offshore Wind Turbines Using Vibration Measurements
Abstract: See attached abstract
Host: Dr. Audrey Olivier
More Info: https://usc.zoom.us/j/91558672174
More Information: Babak Moaveni Announcement 110923.docx
Location: Zoom Only
Audiences: Everyone Is Invited
Contact: Salina Palacios
Event Link: https://usc.zoom.us/j/91558672174
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Munushian Seminar - Jelena Vuckovic, Friday, November 10th at 10am in EEB 132 & Zoom
Fri, Nov 10, 2023 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jelena Vuckovic, Stanford University
Talk Title: Unlocking the power of photonics through inverse design and heterogeneous integration
Series: Munushian Visiting Seminar Series
Abstract: Novel computational techniques such as photonics inverse design, along with new nanofabrication approaches, play a crucial role in building scalable integrated photonics. While initial inverse design demonstrations focused on individual small footprint devices, recent developments enable rapid optimization of large 3-dimensional structures, with linear dimensions over 100 microns, and fully compatible with foundry fabrication. We illustrate this with recent demonstrations of powerful integrated photonic systems for applications such as optical interconnects. To enable all necessary functionalities, future photonic systems also require integration of traditional and non-traditional photonic materials, including silicon, silicon-carbide, diamond, sapphire, and strong electro-optic materials such as lithium niobate, strontium titanate, and barium titanate. We show that compact and efficient lasers, isolators, electro-optic modulators, and detectors can all be integrated on silicon compatible platform. We also show that a broadly tunable Ti:sapphire laser, the workhorse of optics laboratories, can be miniaturized into sub-cubic centimeter volume together with its pump, and without any loss of performance. Finally, we will discuss how silicon carbide and diamond can be employed to build scalable quantum technologies.
Biography: Jelena Vuckovic (PhD Caltech 2002) is the Jensen Huang Professor in Global Leadership in the School of Engineering, and Professor of Electrical Engineering and by courtesy of Applied Physics at Stanford, where she leads the Nanoscale and Quantum Photonics Lab. She was the inaugural director of Q-FARM, the Stanford-SLAC Quantum Science and Engineering Initiative, and the Fortinet Founders Chair of the Electrical Engineering Department at Stanford. Vuckovic has received many awards and honors including recently the Geoffrey Frew Fellowship from the Australian Academy of Sciences (2023), the Vannevar Bush Faculty Fellowship (2022), the Mildred Dresselhaus Lectureship from MIT (2021), the James Gordon Memorial Speakership from the OSA (2020), the IET A. F. Harvey Engineering Research Prize (2019), Distinguished Scholarship of the Max Planck Institute for Quantum Optics (2019), the Hans Fischer Senior Fellowship from the Institute for Advanced Studies in Munich (2013), and the Humboldt Prize (2010). She is a member of the National Academy of Sciences (NAS), Fellow of the APS, of the Optica, and of the IEEE, and an associate editor of the ACS Photonics.
Host: ECE-EP
Webcast: Zoom ID 98662068700 Passcode 538109More Information: Jelena Vuckovic Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: Zoom ID 98662068700 Passcode 538109
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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ECE Seminar: Filter Banks on Arbitrary Graphs Using Generalized Laplacian Eigenvectors
Tue, Nov 14, 2023 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Eduardo Pavez Carvelli, Postdoctoral Research Associate/Ming Hsieh Department of Electrical and Computer Engineering
Talk Title: Filter Banks on Arbitrary Graphs Using Generalized Laplacian Eigenvectors
Abstract: In the past decade, Graph Signal Processing (GSP) has become a popular framework to represent and process irregular and unstructured data, such as 3D point clouds arising from immersive communication and autonomous vehicle applications.
In this talk I will present our recent work on two channel filter banks for signals on graphs. Filter banks and other multi-resolution transformations have been extensively used for signal and image processing. Due to graph irregularities it can be challenging to construct filter banks for graphs, while satisfying desirable properties such as critical sampling, perfect reconstruction and low complexity. Bipartite filter banks are amongst the most popular designs satisfying these requirements, yet they are limited to bipartite graphs represented by their normalized Laplacian matrix. In practice graphs are rarely bipartite and other graph matrices are often preferred.
We substantially extend bipartite filter bank theory to arbitrary (non-bipartite) graphs and positive definite graph matrices. Our key insight is realizing the limitations of graph eigenvectors for spectral design of graph filter banks. As an alternative, we propose to use Q-orthogonal generalized eigenvectors of graphs, which can be constructed with certain spectral symmetries that can be exploited for filter bank design. The proposed graph filter banks are applied to graphs constructed on 3D point clouds with hundreds of thousands of nodes.
Biography: Eduardo Pavez Carvelli received the B.S. and M.Sc. degrees in electrical engineering from the University of Chile, Santiago, Chile, in 2011 and 2013, respectively, and the Ph.D. degree in electrical engineering from the University of Southern California, in 2019. He was an intern at Microsoft Research, and Mitsubishi Electric Research Laboratories, and he is currently a Postdoctoral Research Associate at the University of Southern California. His research is in the areas of graph signal processing, 3D point cloud processing and compression. His work on point cloud and video compression received best paper awards at IEEE ICIP 2020 and 2022.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/95889271695?pwd=TDFRWEsyY1VMWEFFQmZTdkg4ODhYQT09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/95889271695?pwd=TDFRWEsyY1VMWEFFQmZTdkg4ODhYQT09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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ECE Seminar: Reinforcement Learning for Control and Beyond
Tue, Nov 14, 2023 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jay H. Lee, C. H. Cho Professor of Mork Family Department of Chemical Engineering and Materials Science University of Southern California
Talk Title: Reinforcement Learning for Control and Beyond
Abstract: Since Alan Turing’s remarkable foresight of creating a machine that simulates the “adult brain” starting from the “child mind” through a computer algorithm that educates through rewards and punishments, reinforcement learning (RL) has been at the forefront of many academic fields including psychology, computer science, and control. With recent advancement of deep learning and GPU-computing as well as well-publicized success stories like the Alpha-Go, it is enjoying a renaissance of popularity and offers opportunities for applications with commercial impacts. RL and control originated from the different fields but they both address the same basic problem of making sequential decisions in an uncertain, dynamic environment to maximize/minimize a long-term objective function. In this presentation, similarities and differences between reinforcement learning and optimal control will be brought to attention and some ideas will be shared on how they can be brought to complement and support each other in solving complex industrial decision problems. Some exemplary applications expected to benefit significantly from the use of RL concepts and methods will be presented, including batch process control, energy planning, and materials design.I will also give a short introduction to other research topics I am currently engaged in, including lithium-ion battery’s state of health prediction and evaluation of CO2 capture, utilization, and storage (CCUS) technologies.
Biography: Jay H. Lee obtained his B.S. degree in Chemical Engineering from the University of Washington, Seattle, in 1986, and his Ph.D. degree in Chemical Engineering from California Institute of Technology, Pasadena, in 1991. From 1991 to 1998, he was with the Department of Chemical Engineering at Auburn University, AL, as an Assistant Professor and an Associate Professor. From 1998-2000, he was with School of Chemical Engineering at Purdue University, West Lafayette, and then with the School of Chemical Engineering at Georgia Institute of Technology, Atlanta from 2000-2010 and Chemical and Biomolecular Engineering Department at Korea Advanced Institute of Science and Technology (KAIST) from 2010-2022, where he was the department head from 2010-2015, Associate VP of International Relations from 2015-2017, KEPCO Chair Professor and the founding Director of Saud Aramco-KAIST CO2 Management Center at KAIST. He is currently C. H. Cho Chair Professor of Mork Family Department of Chemical Engineering and Materials Science at University of Southern California. He was a recipient of the National Science Foundation’s Young Investigator Award in 1993 and was elected as an IEEE Fellow and an IFAC (International Federation of Automatic Control) Fellow in 2011 and an AIChE Fellow in 2013. He was also the recipient of the 2013 Computing in Chemical Engineering Award given by the AIChE’s CAST Division and the 2016 Roger Sargent Lecturer at Imperial College, UK. He is an Editor of Computers and Chemical Engineering and Discover Chemical Engineering. He was currently the Editor-in-Chief of Korean Journal of Chemical Engineering and also the chair of IFAC Coordinating Committee on Process and Power Systems. He published over 260 manuscripts in SCI journals with ~21000 Google Scholar citations. His research interests are in the areas of system identification, state estimation, robust control, model predictive control, and reinforcement learning with applications to sustainable energy systems, bio-refinery, and CO2 capture/conversion systems.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/93773325275?pwd=V3R4aEg1cW9DU1AvT3RCcHArS3RWUT09More Information: ECE-Seminar-Lee-111423.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/93773325275?pwd=V3R4aEg1cW9DU1AvT3RCcHArS3RWUT09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 14, 2023 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Chai Keong Toh, ITS Senior Fellow, Berkeley Institute of Transportation Studies, University of California, Berkeley
Talk Title: Smart Cities: Design & Research
Host: Dr. Neil Siegel
More Information: November 14, 2023.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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AME Seminar
Wed, Nov 15, 2023 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Xiao Hu, Emory University
Talk Title: Unleashing the Power of AI for Precision Health: The Vital Role of Physiological and Nursing Data
Abstract: Artificial intelligence (AI) has tremendous potential to advance clinical practice and patient care by providing clinicians augmented abilities to derive diagnostic and prognostic insights from various types of data. Medical images, structured data, clinical notes in electronic health record systems are data modalities that have so far received much attention. In addition to these data modalities in spotlight, continuous physiological data including electrocardiography, blood pressure, intracranial pressure, electroencephalography, photoplethysmography signals are part of standard of care, hence ubiquitously available for patients in acute care, and least susceptible to practice variations. Rich and dynamic pathophysiological information is embedded in these signals and yet there are no experts like radiologists dedicated to interpreting these signals at scale. Therefore, there is a vast amount of untapped information in these signals. In this keynote, we will explore three overarching approaches to process physiological data: The single modality approach, where novel metrics are derived from a single signal, unveiling physiological insights that remain concealed in conventional patient monitors. The multi-signal approach, which analyzes multiple signal modalities to elucidate the intrinsic interplay among different organ systems, providing more precise signatures of acute illnesses. The multimodality approach, which integrates physiological data with other clinical information, enabling enhanced patient monitoring capabilities and more precise care delivery. Bedside nurses play a pivotal role in continuously managing, interpreting, documenting, and communicating physiological data. However, they often face alarm fatigue due to inferior built-in algorithms of patient monitors. By harnessing the power of AI tools to process physiological data, we can alleviate this burden, elevate the nursing profession, and ultimately improve patient care outcomes.
Biography: Xiao Hu is Asa Griggs Candler Chair Professor at the Nell Hodgson Woodruff School of Nursing, associated faculty at the Departments of Computer Sciences and Biomedical Informatics, and PhD program faculty at the joint Biomedical Engineering program of Georgia Tech and Emory University. He also serves as the Associate Director of the Center for Data Science. In his remarkable career, he has held faculty positions at esteemed institutions like UCLA, UCSF, and Duke University. Dr. Hu's pioneering research lies at the intersection of computational and health sciences, using advanced algorithms to transform healthcare data into actionable patient care insights. His significant contributions include over 160 peer-reviewed publications, multiple NIH research projects, and nine US patents.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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NL Seminar- Cultural Knowledge and Cultural Biases: Analyzing the Multilingual Performance of Text-to-Image Models
Thu, Nov 16, 2023 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Michael Saxon, UCSB
Talk Title: Cultural Knowledge and Cultural Biases: Analyzing the Multilingual Performance of Text-to-Image Models
Abstract: REMINDER: Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom. Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please provide your: Full Name, Title and Name of Workplace to (nlg-seminar-host(at)isi.edu) beforehand so we’ll be aware of your attendance. Also, let us know if you plan to attend in-person or virtually. More Info for NL Seminars can be found at: https://nlg.isi.edu/nl-seminar/ Despite being ostensibly trained on solely English data, most text-to-image (T2I) models carry some degree of multilingual capability, with significant variation in performance between models and languages. To guide the future development of T2I systems, both measuring and qualitatively analyzing these language-specific performance variations is desirable, to mitigate cross-lingual disparities in performance as well as language-specific demographic biases.To quantify multilingual performance we introduce the Conceptual Coverage Across Languages (CoCo-CroLa) benchmark, which allows us to measure the "possession" of a set of tangible noun "concepts" across English, Spanish, German, Chinese, Japanese, Hebrew, and Indonesian. This technique allows us to estimate how well-suited a model is to a target language as well as identify model-specific weaknesses, spurious correlations, and biases without any a-priori assumptions of their form. We demonstrate how it can be used to rank T2I models in terms of multilinguality, and that despite its simplicity our method captures the necessary conditions for the impressive “creative” generative abilities users expect from T2I models.We then build on this benchmarking work with a detailed qualitative analysis of “failure” and “success” cases for specific concepts. Even in the “possession” case, concepts are expressed differently across languages. These qualitative cross-lingual variations in model behaviors form a continuous spectrum of ethical acceptability, running the gamut from culturally variable popular dog breeds to racially-biased sexualization in depictions of women. While the edge cases are easy to laud or condemn, drawing the line of acceptability in between them is an open ethical question as well as an open technical challenge. Unfortunately, interventions that successfully remove the most deleterious biases also erase cultural distinctiveness, motivating a need for more targeted interventions in future work.
Biography: Michael Saxon is a CS Ph.D. candidate in the NLP Group at the University of California, Santa Barbara. His research is driven by a desire to improve our objective understanding of the semantic capabilities of large generative AI systems, in particular generative image and language models. Toward this goal he focuses on developing novel data resources and metrics for to model semantic phenomena in generative model, as well as techniques for model-driven dataset improvement to remove biases and spurious correlations. He has previously interned at Meta AI and Amazon working on NLP and speech, and is supported by the NSF Graduate Research Fellowship Program.
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://youtu.be/nlu57ZSKbi0Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://youtu.be/nlu57ZSKbi0
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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CAIS Webinar: Sidestepping the Black-Box: A New Paradigm for Explainable AI
Thu, Nov 16, 2023 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Amulya Yadav, PNC Technologies Career Development Assistant Professor (Penn State University)
Talk Title: Sidestepping the Black-Box: A New Paradigm for Explainable AI
Abstract: Existing work in Explainable Artificial Intelligence (XAI) has been focused on developing techniques to interpret decisions made by pre trained and black box machine learning (ML) models. This black box assumption is reasonable in a lot of settings, e.g., explaining Amazons recommender systems requires assuming a black box model because it is infeasible to assume glass box access to Amazons proprietary models, etc. However, I argue that in many real world settings (especially those that pertain to low resource domains), the black box assumption is unnecessary, undesirable, and often, overly limiting. In this talk, I motivate the need to move away from the black box assumption of XAI by discussing two deployed use cases of responsible AI research i. automated tele triage for poor pregnant women in Kenya, and ii. raising awareness of HIV among homeless youth in Los Angeles. Through my experiences with the deployment of AI in these domains, we will argue the need for a new paradigm in explainable AI. Next, I will discuss two new frameworks i. CounterNet, a novel end to end learning framework which integrates Machine Learning (ML) model training and the generation of corresponding counterfactual (CF) explanations into a single end to end pipeline and ii. RoCourseNet, a training framework that jointly optimizes predictions and recourses that are robust to future data shifts.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Amulya Yadav is the PNC Technologies Career Development Assistant Professor in the College of Information Sciences and Technology at Penn State University, where he serves as Director of the RAISE Research Lab. He is also the Associate Director (Programs) at the Center for Socially Responsible AI at Penn State. Amulyas research work in the field of Responsible AI and Artificial Intelligence for Social Good focuses on developing theoretically grounded approaches to real world problems that can have an impact in the field. His algorithms have been deployed in the real world, particularly in the field of public health and wildlife protection. Amulya is a recipient of the AAMAS 2016 Best Student Paper Award, the AAAI 2017 Best Video and Best Student Video Award, the IDEAS 2016 Most Visionary Paper Award, and the AAMAS 2017 Best Paper Award nomination. His work has also been highlighted by Mashable.com as one of 26 incredible innovations that improved the world in 2015.
Amulya holds a Ph.D. in Computer Science from the University of Southern California, and a B. Tech. in Computer Science and Engineering from Indian Institute of Technology (IIT), Patna.
Register for the Zoom webinar here: https://usc.zoom.us/webinar/register/WN_nPykyeAAQH-B3R6p5-kezg
Host: CAIS
More Info: https://usc.zoom.us/webinar/register/WN_nPykyeAAQH-B3R6p5-kezg
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/webinar/register/WN_nPykyeAAQH-B3R6p5-kezg
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Munushian Distinguished Lecture - Eli Yablonovitch, Thursday, Nov. 16th at 2pm in EEB 132
Thu, Nov 16, 2023 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Eli Yablonovitch, EECS - University of California, Berkeley
Talk Title: Physics does Optimization (for Free); A New Approach Toward Computation
Series: Munushian Visiting Seminar Series
Abstract: Optimization is vital to science, engineering, and artificial intelligence. It is usually done digitally, but every physics inequality performs optimization in the normal course of dynamical evolution-for free. In driven systems we have Onsager's principle of minimum heat generation. Physics-based optimization usually relies upon this inequality. Optical Onsager machines can run 10^7 times faster than conventional machines, while consuming far less power.
Biography: Prof. Yablonovitch introduced the idea that strained semiconductor lasers could have superior performance due to reduced valence band (hole) effective mass. With almost every human interaction with the internet, optical telecommunication occurs by strained semiconductor lasers.
He is regarded as a Father of the Photonic BandGap concept, and he coined the term "Photonic Crystal". The geometrical structure of the first experimentally realized Photonic bandgap, is sometimes called "Yablonovite".
In his photovoltaic research, Yablonovitch introduced the 4(n squared) ("Yablonovitch Limit") light-trapping factor that is in worldwide use, for almost all commercial solar panels.
His mantra that "a great solar cell also needs to be a great LED", is the basis of the world record solar cells: single-junction 29.1% efficiency; dual-junction 31.5%; quadruple-junction 38.8% efficiency; all at 1 sun.
His cellphone antenna company, Ethertronics Inc., shipped over 2x10^9 antennas.He was also a co-Founder of Luxtera Inc., the pioneer in Silicon Photonics, now part of Cisco.
He co-Founded Luminescent Inc., the company that originated "Inverse Lithography Technology".
Host: ECE-Electrophysics
Webcast: Meeting ID: 96220203431 Pass Code: 949129More Information: Eli Yablonovitch Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: Meeting ID: 96220203431 Pass Code: 949129
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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2023 Eberhardt Rechtin Keynote Lecture
Thu, Nov 16, 2023 @ 04:00 PM - 06:00 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Mark S. Daskin, Clyde W. Johnson Collegiate Professorship, Emeritus; Immediate past Department Chair of the Industrial and Operations Engineering Department at the University of Michigan
Talk Title: Core Principles of Operations Management
Host: Epstein ISE Dept.
More Info: ***Please send email to: owh@usc.edu to RSVP***
More Information: 2023 Recthin Lecture flyer.jpg
Location: USC Hotel, Center Ballroom
Audiences: Everyone Is Invited
Contact: Grace Owh
Event Link: ***Please send email to: owh@usc.edu to RSVP***
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WIE Meets WII
Thu, Nov 16, 2023 @ 05:30 PM - 07:30 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
The event was created to help our fellow female engineering students gain perspective on what it is like to work in the industry and get advice on transitioning from college to the workplace. Our theme this year is âIf you can Dream it, you can Be itâ.
Filming Notice:
The University of Southern California is photographing and or video recording the event in which you are participating and or attending. By your presence in this area, you acknowledge that you have been informed that you may be photographed and/or recorded as part of the program/event.
Feel free to contact tfederic@usc.edu if you have any questions.
Location: Sign into EngageSC to View Location
Audiences: Everyone Is Invited
Contact: Thelma Federico Zaragoza
Event Link: https://engage.usc.edu/WIE/rsvp?id=393327
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Quantum Science & Technology Seminar - Srujan Meesala, Friday, Nov. 17th at 10:30am in EEB 132
Fri, Nov 17, 2023 @ 10:30 AM - 11:45 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Srujan Meesala, Caltech
Talk Title: A chip-scale source of entangled microwave and optical photons
Series: Quantum Science & Technology Seminar Series
Abstract: Classical supercomputers and the internet are based on optically connected microwave frequency processors. An analogous architecture for large-scale quantum computers and networks would involve entanglement distribution between superconducting microwave processor modules using optical communication links. Connecting quantum particles in these two vastly different platforms while preserving quantum coherence is an outstanding technical challenge. I will present a recent experimental advance where we used a chip-scale transducer to prepare entangled states of single optical and microwave photons. We achieved this through a low-noise parametric down-conversion process in a device with carefully engineered optical, acoustic and superconducting components. This device can enable a room-temperature optical interconnect between superconducting qubits cooled in separate cryogenic nodes in the near term. I will discuss open challenges and opportunities with such devices en route to the long-term vision of a distributed quantum computer.
Biography: I am an Institute for Quantum Information and Matter (IQIM) Postdoctoral Scholar at Caltech in Oskar Painter's group. Previously, I received my PhD from Harvard where I worked in Marko Loncar's group. I perform experimental research on a variety of solid-state quantum platforms including superconducting circuits, defect center spins, and nanoscale optical and acoustic devices. I am interested in connecting such platforms to address open questions on building large-scale quantum systems for computation, communication and sensing.
Host: Quntao Zhang, Wade Hsu, Mengjie Yu, Jonathan Habif & Eli Levenson-Falk
More Information: Srujan Meesala Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Semiconductors & Microelectronics Technology Seminar - Joel K.W. Yang, Friday, November 17th at 1:45pm in EEB 132
Fri, Nov 17, 2023 @ 01:45 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Joel K.W. Yang, Singapore University of Technology and Design
Talk Title: Nanoscale 3D Printing of Structural Colors and Micro Optics
Series: Semiconductors & Microelectronics Technology
Abstract: Structural colors are generated from nanoscale features of various materials due either to interference or optical resonance effects. The ability to achieve a wide range of colors by simply tuning geometric properties opens fascinating opportunities to the nanoengineer or nanoscientist to design colors using material properties, and nanostructure geometry as input parameters. This physical approach contrasts with the chemical approach for synthesizing pigments and dyes, where colors arise due to optical absorption. Using semiconductor fabrication methods, 2D structures based on metals and high index dielectrics have been realized, e.g. nanodisks, ellipses, etc. defined with electron-beam lithography and vacuum deposition methods. Recently, we extended the generation of structural colors from 3D nanostructures created using two-photon polymerization lithography (TPL). The use of TPL, an additive manufacturing process with sub-micron print resolutions, to produce structures for optical effect is a relatively new endeavor. We have previously shown the fabrication of nanopillars, gratings, mesh-like, and wood-pile photonic crystal structures that appear colorful under white-light illumination. We now demonstrate the integration of these structural colors with other micro-optical elements, such as microlenses and spiral phase plates. Equipped with TPL as a nanoscale 3D printer, structural color geometries are conveniently integrated in a single print run with other user-defined optics. Doing so enables one to produce structured light from incoherent light sources, holographic color prints, and control of the light-field for 3D representation. We will discuss the use of structural colors combined with micro-optics for enhanced information content and optical security.
Biography: Joel Yang received his Master of Science (2005) and PhD (2009) degrees from the Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science. He is Full Professor (since Aug 2023) in the Engineering Product Development pillar at the Singapore University of Technology and Design (SUTD). He held a joint appointment as Principal Scientist at the Institute of Materials Research and Engineering (IMRE) of A*STAR until 2023. He is recognized for pioneering work in plasmonic and structural color printing, achieving record-level printing resolution at 100,000 dpi and credited for the widely-used "salty-developer" to improve the resolution of electron beam lithography. His research interests include Nanoplasmonics, 2D and 3D printed nano optical design elements (NODE), and sub-10-nm resolution lithography. He serves as Associate Editor of Science Advances. He is Fellow of Optica (former OSA The Optical Society), National Research Foundation (NRF) Investigator (class of 2020), and A*STAR Investigator (2010). His accolades include the Institute of Physics Singapore (IPS) Nanotechnology Medal and Prize, MIT Technology Review TR35 award, and the Singapore Young Scientist Award.
Host: J Ravichandran, J Yang, H. Wang, C. Zhou, S. Cronin, W. Wu
More Information: Joel Yan Flyer_v2.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Integrated Systems Seminar - Mingoo Seok, Friday, Nov. 17th at 2pm in EEB 248 & Zoom
Fri, Nov 17, 2023 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mingoo Seok, Columbia University
Talk Title: SRAM-based In-Memory Computing Hardware: Analog vs Digital and Macros to
Series: Integrated Systems
Abstract: In the last decade, SRAM-based in-memory computing (IMC) hardware has received significant research attention for its massive energy efficiency and performance boost. In this seminar, first, we will introduce two very recent macro prototypes that achieve state-of-the-art performance and energy efficiency yet leverage very different computing mechanisms. Specifically, one adopted analog-mixed-signal (AMC) computing mechanisms (capacitive coupling and charge sharing), whereas the other adopted a fully digital approach. After this macro-level introduction, we will present recent microprocessor prototypes employing IMC-based accelerators, which can perform on-chip inferences at high energy efficiency and low latency.
Biography: Mingoo Seok is an associate professor of Electrical Engineering at Columbia University. He received his B.S. from Seoul National University, South Korea, in 2005 and his M.S. and Ph.D. degrees from the University of Michigan in 2007 and 2011, respectively, all in electrical engineering. His research interests are various aspects of VLSI circuits and architecture, including ultra-low-power integrated systems, cognitive and machine-learning computing, an adaptive technique for the process, voltage, temperature variations, transistor wear-out, integrated power management circuits, event-driven controls, and hybrid continuous and discrete computing. He won the 2015 NSF CAREER award and the 2019 Qualcomm Faculty Award. He is the technical program committee member for multiple conferences, including the IEEE International Solid-State Circuits Conference (ISSCC). In addition, He has been an IEEE SSCS Distinguished Lecturer for Feb/2023-Feb/2025 and an associate editor for IEEE Transactions on Circuits and Systems Part I (TCAS-I) (2014-2016), IEEE Transactions on VLSI Systems (TVLSI) (2015-present), IEEE Solid-State Circuits Letter (SSCL) (2017-2022), and as a guest associate editor for IEEE Journal of Solid-State Circuits (JSSC) (2019).
Host: MHI - ISSS, Hashemi, Chen and Sideris
Webcast: Zoom Meeting ID: 919 9842 7261, Passcode: 520437More Information: Abstract and Bio_Mingoo.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: Zoom Meeting ID: 919 9842 7261, Passcode: 520437
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 21, 2023 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: ,
Talk Title: **NO SEMINAR - THANKSGIVING BREAK**
Location: SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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SERC Seminar
Tue, Nov 28, 2023 @ 01:00 PM - 02:00 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: David Miller, NASA-JPL
Talk Title: If You Cannot Create Space in Your Lab, Create Your Lab in Space
Abstract: Experimentation is an essential step in maturing technology. Whether it is to measure new phenomena, assess the repeatability and reliability of components, calibrate simulations, determine performance limits, identify operational drivers, or to demonstrate to a decision-maker that the technology works in an operational environment, those experiments must be conducted in an operationally authentic environment. For space, those environments include thermal, radiation, vacuum, lighting conditions, orbital dynamics, the “view,” and long-duration micro-gravity. The first four can be tested to some fidelity in ground-based chambers but the latter three require testing in space.
Analogous to a wind tunnel, testing in long duration micro-gravity allows a formative technology to be tested, under nominal and (more importantly) off-nominal conditions, without harm to the technology, the operator and the platform. This talk will illustrate the use of Shuttle, Mir and the International Space Station as research platforms for maturing space technology whose behavior is dependent upon long duration micro-gravity. This will be done through the lens of three evolvable research facilities that the presenter’s laboratory at MIT developed over the past three decades.
Biography: David W. Miller is the former Director of the Space Systems Laboratory and the Jerome C. Hunsaker Professor (Post Tenure) in the Department of Aeronautics and Astronautics at M.I.T. Prof. Miller has played an engineering role in the development of space-based apertures. He has built and operated a dozen space flight experiments spanning Shuttle, Mir, ISS, and free flyers. He was a member of the JWST Product Integrity Team and the Vice Chair and S&T Chair of the Air Force Scientific Advisory Board. He served two and a half years as NASA's Chief Technologist at NASA Headquarters in Washington, DC and three years as Vice President and Chief Technology Officer at the Aerospace Corporation. He is currently the Chief Technologist for the Astronomy and Fundamental Physics Directorate at NASA’s Jet Propulsion Laboratory and an AIAA Fellow and member of the National Academy of Engineering.
Host: ASTE Department
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Everyone Is Invited
Contact: Dell Cuason
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SERC Seminar
Tue, Nov 28, 2023 @ 02:00 PM - 03:00 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: Charles L. Gustafson, UC Berkeley
Talk Title: Transformational Communications Satellite, Lessons Learned
Abstract: The Transformational Communications Satellite Program (TSAT) was an ambitious military program that existed from 2003-2009. It looked to combine existing frequency hopped communications methods with internet protocols and laser communications to provide military users with significant new capabilities. It was ultimately canceled in 2009 prior to fully entering development. This talk will provide an overview of intended capabilities and lessons learned from the program.
Biography: Charles L. Gustafson is the former Senior Vice President of the Engineering and Technology Group at The Aerospace Corporation, a non-profit consulting company working on government satellite and launch systems. His entire career was spent at Aerospace, during which he worked on a number of communication and remote sensing satellites, launch systems, and intelligence community programs. He served as a member of the Air Force Scientific Advisory Board for four years, including one year overseeing the science and technology review process. He holds a PhD in Electrical Engineering and Computer Science from UC Berkeley.
Host: ASTE Department
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Everyone Is Invited
Contact: Dell Cuason
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 28, 2023 @ 03:50 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Paul Grigas, Assistant Professor, Department of Industrial Engineering & Operations Research, University of California, Berkeley
Talk Title: A Margin Theory for Contextual Stochastic Linear Optimization: From Generalization to Active Learning
Host: Dr. Meisam Razaviyayn
More Information: November 28, 2023.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium: Niloufar Salehi (UC Berkeley) - Designing Reliable Human-AI Interactions
Tue, Nov 28, 2023 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Niloufar Salehi, UC Berkeley
Talk Title: Designing Reliable Human-AI Interactions
Abstract: How can users trust an AI system that fails in unpredictable ways? Machine learning models, while powerful, can produce unpredictable results. This uncertainty becomes even more pronounced in areas where verification is challenging, such as in machine translation or probabilistic genotyping. Providing users with guidance on when to rely on a system is challenging because models can create a wide range of outputs (e.g. text), error boundaries are highly stochastic, and automated explanations themselves may be incorrect. In this talk, I will focus on the case of health-care communication to share approaches to improving the reliability of ML-based systems by designing actionable strategies for users to gauge reliability and recover from potential errors.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Niloufar Salehi is an assistant professor in the School of Information at UC, Berkeley and faculty member of Berkeley AI Research (BAIR). Her research interests are in social computing, human-centered AI, and more broadly, human-computer interaction (HCI). Her research is in close collaboration with partners and domain experts spanning education to healthcare to restorative justice. Her work has been published and received awards in premier venues including ACM CHI and CSCW and has been covered in VentureBeat, Wired, and the Guardian. She is a W. T. Grant Foundation scholar. She received her PhD in computer science from Stanford University in 2018.
Host: Souti Chattopadhyay
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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CSCI 591 Colloquium: Prof. Yisen Wang (Peking University) - Theoretical Understanding of Self-Supervised Learning
Wed, Nov 29, 2023 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Yisen Wang, Peking University
Talk Title: Theoretical Understanding of Self-Supervised Learning
Abstract: Self-supervised learning (SSL) is an unsupervised approach for representation learning without relying on human-provided labels. It creates auxiliary tasks on unlabeled input data and learns representations by solving these tasks. SSL has demonstrated great success on various tasks. The existing SSL research mostly focuses on improving the empirical performance without a theoretical foundation. While the proposed SSL approaches are empirically effective on benchmarks, they are not well understood from a theoretical perspective. In this talk, I will introduce a series of our recent work on theoretical understanding of SSL, particularly on contrastive learning and masked autoencoders. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Yisen Wang is an assistant professor at Peking University. His research interests include machine learning theory and algorithms, focusing on adversarial robustness, graph learning, and weak/self-supervised learning theory. He has published more than 50 top academic papers in the field of machine learning, including ICML, NeurIPS, ICLR, etc., and many of them have been selected as Oral or Spotlight. He has won the ECML 2021 Best Paper Award.
Host: Yue Zhao
More Info: https://usc.zoom.us/j/97892066727?pwd=LytmZmltbDk5aWZtZHdKTjZyclI1QT09
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Chair's Assistant
Event Link: https://usc.zoom.us/j/97892066727?pwd=LytmZmltbDk5aWZtZHdKTjZyclI1QT09
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AME Seminar
Wed, Nov 29, 2023 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Chinedum (Chi) Okwudire, University of Michigan Ann Arbor
Talk Title: Smart Additive Manufacturing
Abstract: There is a lot of excitement about the potential of smart manufacturing (involving the use of information, automation, computation, software, sensing, and networking technologies) to revolutionize the manufacturing industry, e.g., by boosting manufacturing quality and productivity at low cost. An excellent application for such “smart” technologies is additive manufacturing (AM), another area of manufacturing that is gaining a lot of traction but is plagued by quality, productivity and cost issues. In this talk, I will share some of my research results in smart AM, aimed at enhancing AM quality and productivity at low cost using smart technologies. Specifically, I will discuss our work on speeding up 3D printers at low cost using advanced controls and cloud computing. I will also discuss our new research on intelligent optimization of scan sequence to minimize thermal induced defects in laser powder bed fusion AM. Finally, I will give a brief overview of efforts I am leading at the University of Michigan to integrate smart AM into our educational curriculum.
Biography: Chinedum (Chi) Okwudire is a Professor of Mechanical Engineering and Miller Faculty Scholar at the University of Michigan. His research is focused on exploiting knowledge at the intersection of machine design, control and computing to boost the performance of manufacturing automation systems at low cost. Chi has received a number of awards including the NSF CAREER Award; SME Outstanding Young Manufacturing Engineer Award; and UC Berkeley’s Russell Severance Springer Visiting Professorship. He was recently selected by SME as one of the 25 leaders transforming manufacturing. He has co-authored a number of best-paper-award-winning papers in the areas of manufacturing automation, control and mechatronics.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/98121141178?pwd=VGEyaXVWYnRaazFYWUVhbVAycGVWQT09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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ECE Seminar: Safe Autonomous Systems through Neurosymbolic Reasoning
Thu, Nov 30, 2023 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jyotirmoy V. Deshmukh, Associate Professor, Thomas Lord Department of Computer Science, USC Viterbi School of Engineering
Talk Title: Safe Autonomous Systems through Neurosymbolic Reasoning
Abstract: Huge strides have made in the widespread adoption of autonomous and human-in-the-loop cyber-physical systems (CPS), partly fueled by dramatic improvements in learning-based techniques. An important aspect of many such CPS applications is that they are safety-critical; any undesirable behavior by such systems can cause serious harm to human lives or property. The formal methods community has been an advocate of using logic and automata as specifications for safety-critical CPSs, and the past few decades have seen significant strides in algorithms for their verification, testing, and automated synthesis. A new challenge now is the presence of learning-enabled components (LECs) in CPSs. In this talk, we will review some recent work on using logic and learning-based techniques to provide guarantees for CPS applications using LECs. Such techniques are neurosymbolic in nature; they rely on infusing symbolic knowledge in neural network-based learning algorithms, as well as using symbolic techniques to reason about such neural systems. We will discuss the applicability and scalability of these techniques to real-world systems, discussing some success stories, as well as lay out some of the challenge problems that would need to be solved.
Biography: Jyotirmoy V. Deshmukh (Jyo) is an Associate Professor in the Department of Computer Science at the University of Southern California, and the co-Director of the Center for Autonomy and AI. Before joining USC, Jyo worked as a Principal Research Engineer at Toyota R&D. He got his Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin in 2010. He was the 2010-12 Computing Innovation Postdoctoral research Fellow at the University of Pennsylvania. He is the recipient of the 2021 NSF Career Award and the 2021 Amazon Research Award.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/93509653910?pwd=QjVaQUhPOWVHVHFibXE3VjRkRXN4dz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/93509653910?pwd=QjVaQUhPOWVHVHFibXE3VjRkRXN4dz09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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NL Seminar
Thu, Nov 30, 2023 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kawin Ethayarajh, Stanford University
Talk Title: Machine Learning with Human Fault-Tolerance
Abstract: REMINDER: This talk will be a live presentation only, it will not be recorded. Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please provide your: Full Name, Title and Name of Workplace to (nlg-seminar-host(at)isi.edu) beforehand so we’ll be aware of your attendance. Also, let us know if you plan to attend in-person or virtually. More Info for NL Seminars can be found at: https://nlg.isi.edu/nl-seminar/ In machine learning, we have long recognized the need to build systems that can tolerate hardware faults and software faults. In this talk, I propose the need for a third kind of fault-tolerance: human fault-tolerance. The methods used to develop, evaluate, and deploy machine learning systems today assume that the humans that build and use them are rational actors making highly-informed decisions based on consistent preferences—this is far from true in practice. We can address the failures of these assumptions by drawing from economics, a field that has long been aware of how unfounded beliefs about human behavior can go wrong. Specifically, I will cover how we can develop theoretically grounded tools that discover human mistakes, design algorithms and methods for robustly eliciting and incorporating human feedback, and implement end-to-end platforms that make ML and NLP more transparent and reproducible. This line of work has led to the creation of datasets, models, and platforms that have been widely adopted by industry giants like Amazon, Google, and Meta.
Biography: Kawin Ethayarajh is a 5th year PhD student at Stanford University, where he works on bringing human fault-tolerance to machine learning. His research draws from economics to make machine learning and NLP more robust to the irrational, inconsistent, and uninformed human decisions made at every step. His work has been supported by a Facebook Fellowship and an NSERC PGS-D, and he has received an Outstanding Paper Award at ICML 2022. He co-created the Stanford Human Preferences dataset and the Dynaboard platform (behind Dynabench).
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://usc.zoom.us/j/99484520082Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://usc.zoom.us/j/99484520082
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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Quantum Science & Technology Seminar - Chaitali Joshi, Thursday, Nov. 30th at 2pm in EEB 248
Thu, Nov 30, 2023 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Chaitali Joshi, Google, Santa Barbara
Talk Title: A chiral light-matter interface with superconducting qubits
Series: Quantum Science & Technology Seminar Series
Abstract: Noise Improving qubit connectivity in quantum networks is crucial for distributed information processing, and for reducing resource overheads in certain error correction protocols. While superconducting circuits have shown great promise for large-scale quantum processors, controlling the flow of light in complex qubit networks has remained a challenge. In this talk, I will discuss our recent work on realizing nonreciprocal light-matter interactions in the microwave domain using a transmon qubit strongly coupled to a 1D waveguide. By modulating the atom-waveguide coupling using magnetic fields, we gain control over the direction of photon emission from the qubit, with the ratio of forward-to-backward coupling rates exceeding 100. I will discuss applications of this platform, including photon-mediated gates between distant qubits and the preparation of many-body dark states in chiral atom arrays. In the second part, I will discuss our exploratory work on using disordered superconducting materials for nonlinear devices suitable for quantum links operating in the millimeter-wave frequency regime. Work based on: Phys. Rev. X 13, 021039 (2023), Phys. Rev. Applied 18, 064088 (2022)
Biography: Chaitali is currently a quantum research scientist at Google Santa Barbara. Previously, she was an IQIM/AWS Postdoctoral scholar in Electrical Engineering at Caltech, where she worked on waveguide quantum electrodynamics with superconducting qubits. She obtained her PhD from Cornell University in 2020, where she worked on nonlinear and integrated photonics for time-frequency manipulation of quantum states of light.
Host: Quntao Zhang, Wade Hsu, Mengjie Yu, Jonathan Habif & Eli Levenson-Falk
More Information: Chaitali Joshi Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
