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SUNMONTUEWEDTHUFRISAT
Events for the 5th week of March
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Gas Turbine Engine Accident Investigation GTAI 24-2Mon, Mar 25, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
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Helicopter Accident Investigation HAI 24-2
Mon, Mar 25, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
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USC Symposium on Frontiers of Generative AI Models in Science and Society
Mon, Mar 25, 2024 @ 08:30 AM - 06:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Various, USC Machine Learning Center
Talk Title: USC Symposium on Frontiers of Generative AI Models in Science and Society
Abstract: The USC Machine Learning Center and Computer Science Department is excited to host the syposium on "Frontiers of Generative AI Models in Science and Society". Experts in generative AI models will discuss recent progresses and their applications in science and soceity.
Keynote Speakers: Alessandro Vespignani (Northeastern University), Nitesh Chawla (Notre Dame), Yizhou Sun (UCLA), & Jian Ma (CMU)
Spotlight Speakers: Jieyu Zhao, Robin Jia, Yue Wang, Vatsal Sharan, & Ruishan Liu (USC Thomas Lord Department of Computer Science)
Host: USC Machine Learning Center
More Info: https://www.eventbrite.com/e/usc-symposium-on-frontiers-of-generative-ai-models-in-science-and-society-tickets-860269668737?aff=oddtdtcreator
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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CS Colloquium: Junzhe Zhang - Towards Causal Reinforcement Learning
Mon, Mar 25, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Junzhe Zhang, Columbia University
Talk Title: Towards Causal Reinforcement Learning
Abstract: Causal inference provides a set of principles and tools that allows one to combine data and knowledge about an environment to reason with questions of a counterfactual nature - i.e., what would have happened if the reality had been different - even when no data of this unrealized reality is currently available. Reinforcement learning provides a collection of methods that allows the agent to reason about optimal decision-making under uncertainty by trial and error - i.e., what would the consequences (e.g., subsequent rewards, states) be had the action been different? While these two disciplines have evolved independently and with virtually no interaction, they operate over various aspects of the same building block, i.e., counterfactual reasoning, making them umbilically connected. This talk will present a unified theoretical framework, called causal reinforcement learning, that explores the nuanced interplays between causal inference and reinforcement learning. I will discuss a recent breakthrough in partial identification that allows one to infer unknown causal effects from a combination of model assumptions and available data. Delving deeper, I will then demonstrate how this method could be applicable to address some practical challenges in classic reinforcement learning tasks, including robust off-policy evaluation from confounded observations and accelerating online learning with offline data. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Junzhe Zhang is a postdoctoral research scientist in the Causal AI lab at Columbia University. He obtained his doctoral degree in Computer Science at Columbia University, advised by Elias Bareinboim. His research centers on causal inference theory and its applications in reinforcement learning, algorithmic fairness, and explainability. His works have been selected for oral presentations in top refereed venues such as NeurIPS.
Host: Sven Koenig
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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EiS Communications Hub Drop-In Hours
Mon, Mar 25, 2024 @ 10:00 AM - 01:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Viterbi Ph.D. students are invited to stop by the EiS Communications Hub for one-on-one instruction for their academic and professional communications tasks. All instruction is provided by Viterbi faculty at the Engineering in Society Program.
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home?authuser=0
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EiS Communications Hub Drop-In Hours
Mon, Mar 25, 2024 @ 10:00 AM - 01:00 PM
Engineering in Society Program
Student Activity
Drop-in hours for writing and speaking support for Viterbi Ph.D. students
Location: Ronald Tutor Hall of Engineering (RTH) - 222
Audiences: Everyone Is Invited
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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ECE Seminar: Dr. Guanghan Meng, "Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution"
Mon, Mar 25, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Guanghan Meng, Postdoctoral Scholar, Dept of EECS, UC Berkeley
Talk Title: Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution
Abstract: Optical microscopy has become an indispensable tool for non-invasive, high-resolution in vivo imaging of living organisms. Its capability to provide insights into real-time physiological and pathological processes within the body underscores its significance in bioscience and medicine. However, conventional optical microscopy methods have certain limitations. For instance, multiphoton fluorescence microscopy, the method of choice for in vivo imaging through scattering tissue such as the mammalian brains, delivers excellent resolution but falls short in speed for capturing rapid biological activities, such as blood flow dynamics. On the other hand, optical coherence tomography (OCT), a label-free deep-tissue imaging method, stands as a powerful instrument in contemporary optometry clinics, but its high cost limits its broad use, especially in lower-income communities. In this presentation, I will share my research on the development of high-speed multiphoton fluorescence microscopy and cost-effective OCT for brain and eye imaging, respectively, through the utilization of both optical engineering and computational methods.
Biography: Dr. Guanghan Meng, currently a postdoctoral scholar in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, focuses on advancing high-speed, high-resolution fluorescence, and label-free microscopy technologies for deep tissue imaging in vivo. Having earned her PhD from the same university, her doctoral research spanned the disciplines of Molecular and Cell Biology and Physics, primarily concentrating on enhancing two-photon fluorescence microscopy for mouse brain imaging. At present, she is working on computational label-free imaging with a specific interest in the human eye. Guanghan has been recognized with various best presentation awards at scientific conferences and is a recipient of the Berkeley Center for Innovation in Vision and Optics (CIVO) postdoctoral fellowship. Guanghan is also an invited lecturer at the 17th Edition of the Frontiers in Neurophotonics Summer School in Quebec City, Canada in 2024.
Host: Dr. Justin Haldar, jhaldar@usc.edu
Webcast: https://usc.zoom.us/j/96234786783?pwd=eXF0NnlvNEhPRHllS1NDUEFZWklSdz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/96234786783?pwd=eXF0NnlvNEhPRHllS1NDUEFZWklSdz09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CSC/CommNetS-MHI Seminar: Chandra Murthy
Mon, Mar 25, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Chandra Murthy, Professor, Department of Electrical Communication Engineering | Indian Institute of Science, Bangalore, India
Talk Title: Sparsity-aware Bayesian Inference and its Applications
Series: CSC/CommNetS-MHI Seminar Series
Abstract: This talk presents a set of tools based on a Bayesian framework to address the general problem of sparse signal recovery, and discusses the challenges associated with them. Bayesian methods offer superior performance compared to convex optimization-based methods and are largely parameter tuning-free. They also have the flexibility necessary to deal with a diverse range of measurement modalities and structured sparsity in signals than hitherto possible. We discuss recent developments towards providing rigorous theoretical guarantees for these methods. Further, we show that, by re-interpreting the Bayesian cost function as a technique to perform covariance matching, one can develop new and ultra-fast Bayesian algorithms for sparse signal recovery. As example applications, we discuss the utility of these algorithms in the context of (a) 5G communications with several case studies such as wideband time-varying channel estimation, low-resolution ADCs, etc, and (b) controllability and observability of linear dynamical systems under sparsity constraints.
Biography: Chandra R. Murthy is a professor in the department of Electrical Communication Engineering at the Indian Institute of Science, Bangalore, India. His research interests are in sparse signal recovery, energy harvesting-based communication, performance analysis, and optimization of 5G and beyond communications. Papers coauthored by him have received Student/Best Paper Awards at the NCC 2014, IEEE ICASSP 2018, IEEE ISIT 2021, IEEE SPAWC 2022, and NCC 2023. He is a senior area editor for the IEEE Transactions on Signal Processing and the IEEE Transactions on Information Theory. He is an elected member of the IEEE SPS SAM Technical Committee. He is an IEEE Fellow (Class of 2023), and a fellow of the Indian National Academy of Engineering (2023).
Host: Dr. Urbashi Mitra, ubli@usc.edu
More Information: 2024.03.25 CSC Seminar - Chandra Murthy.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Ph.D. Thesis Defense - Ali Omrani
Mon, Mar 25, 2024 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
Ph.D. Thesis Defense - Ali Omrani
Committee: Morteza Dehghani (Chair), Xiang Ren, Robin Jia, Payam Piray, and Jeffrey Sorensen
Title: Countering Problematic Content in Digital Space: Bias Reduction and Dynamic Content Adaptation
Abstract: Problematic content, such as hate speech, poses a significant challenge to society, leading to discrimination and exclusion while undermining inclusivity and well-being. This thesis proposal outlines my efforts to create adaptable solutions for combating problematic content in digital space through a theory-motivated approach that bridges language technology and social sciences. I will begin by presenting an innovative group-agnostic method for bias mitigation in language models, which is grounded in a deep understanding of stereotyping from social psychology. Subsequently, I will introduce a novel continual learning framework for problematic content detection that captures the ever-evolving nature of this issue. Afterward, I discuss my work that extends this framework to multilingual settings, with a specific emphasis on two key aspects: 1. Harnessing cultural diversity for cross-lingual transfer of offensive language detection and 2. Investigating the challenges posed by disparities in data quality across various languages.Date and Time: March 25th, 2:00 PM - 4:00 PM
Location: Room 266, USC Brain and Creativity Institute 605, 3620 McClintock Ave, Los Angeles, CA 90089
Location: Dornsife Neuroscience Imaging Center (DNI) - 266
Audiences: Everyone Is Invited
Contact: CS Events
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How to Search for a Job in Today’s Digital Age
Mon, Mar 25, 2024 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
THIS EVENT WILL BE HOSTED HYBRID: IN-PERSON & ONLINE SIMULTANEOUSLY Zoom link: https://usc.zoom.us/meeting/register/tJYtduquqT8pHtJvtZs8at8XEZCbaNBjyFzd Learn about how recruitment has changed in this virtual environment and review best practices by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners. For more information about all workshops, please visit viterbicareers.usc.edu/workshops.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
Event Link: https://usc.zoom.us/meeting/register/tJYtduquqT8pHtJvtZs8at8XEZCbaNBjyFzd
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Gas Turbine Engine Accident Investigation GTAI 24-2
Tue, Mar 26, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
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Helicopter Accident Investigation HAI 24-2
Tue, Mar 26, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
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CS Colloquium: Xiang Anthony Chen - Catalyzing AI Advances with Human-Centered Interactive Systems
Tue, Mar 26, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Xiang Anthony Chen, UCLA
Talk Title: Catalyzing AI Advances with Human-Centered Interactive Systems
Abstract: Despite the unprecedented advances in AI, there has always been a gap between how well an AI model performs and how such performance can serve humanity. In this seminar, I will describe my past work to close this gap. Specifically, I develop human-centered interactive systems that catalyze advances in AI to achieve three levels of objectives: aligning with human values, assimilating human intents, and augmenting human abilities. Further, I will discuss my ongoing and future research, focused on AI for scientific discovery, AI with Theory of Mind, and AI-mediated human communication. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Xiang ‘Anthony' Chen is an Assistant Professor in UCLA's Department of Electrical & Computer Engineering. He received a Ph.D. in the School of Computer Science at Carnegie Mellon University. Anthony's area of expertise is Human-Computer Interaction (HCI). His research employs human-centered design methods to build systems that catalyze advances in AI to better serve humanity, supported by NSF CAREER Award, ONR YIP Award, Google Research Scholar Award, Intel Rising Star Award, Hellman Fellowship, NSF CRII Award, and Adobe Ph.D. Fellowship. Anthony’s work has resulted in 55+ publications with three best paper awards and three honorable mentions in top-tier HCI conferences.
Host: Heather Culbertson
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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DREAM Industry Mentorship speaker series- Nick Daze
Tue, Mar 26, 2024 @ 11:00 AM - 12:00 PM
USC Viterbi School of Engineering
University Calendar
DREAM (Direct Response to Engineers Aspirations from Mentors) connects students with experienced industry professionals from a variety of tech and destination companies who help them create a vision for their futures, align their careers around purpose, and build character in the context of growth, reinvention, and constant change. Industry mentors discuss how professional challenges present opportunities for character and leadership development. This event features Nick Daze on his journey as an entrepreneur and CEO at Heirloom, a startup building the future of self-sovereign identity on the blockchain. Co-sponsored with Annenberg School of Communication.
Location: Michelson Center for Convergent Bioscience (MCB) - 102
Audiences: Everyone Is Invited
Contact: Elisabeth Arnold Weiss
Event Link: https://cglink.me/2nB/r395856
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Where are the Jobs? Uncovering the Hidden Job Market
Tue, Mar 26, 2024 @ 12:00 PM - 01:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
THIS EVENT WILL BE HOSTED HYBRID: IN-PERSON & ONLINE SIMULTANEOUSLY
Zoom link: https://usc.zoom.us/meeting/register/tJArcOutrDkoHtwd36V2fdNrxXPcWfsMmnSl
Increase your career and internship knowledge on networking by attending this professional development Q&A moderated by Viterbi Career Connections staff. For more information about all workshops, please visit viterbicareers.usc.edu/workshops.
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
Event Link: https://usc.zoom.us/meeting/register/tJArcOutrDkoHtwd36V2fdNrxXPcWfsMmnSl
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Lockheed Martin Office Hours
Tue, Mar 26, 2024 @ 12:00 PM - 04:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Lockheed Martin Virtual Office Hours
Sign up for a 15-minute virtual meeting with Lockheed Martin recruiting Margaret Paulin to discuss career questions, application tips, or recruitment-specific topics about Lockheed Martin!
These virtual office hours will be hosted on Teams on March 26th from 12-4 pm.
Go to Viterbi Career Gateway > Events for event details and to signup
Please only sign up for a single meeting time slot.
Use your USC email.
A link to the virtual meeting will be emailed to you 24 hours before the event.
Location: Virtual
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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CAIS Webinar: Dr. Jessica Ridgway (University of Chicago) - Predictive Analytics for Engagement in HIV Care
Tue, Mar 26, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Jessica Ridgway, University of Chicago
Talk Title: Predictive Analytics for Engagement in HIV Care
Abstract: Engagement in care is essential for the health of people with HIV, but only half of people with HIV in the U.S. receive regular medical care. Dr. Ridgway will discuss her research utilizing machine learning models based on electronic medical record data to predict engagement in care among people with HIV. She has developed machine learning models using structured data as well as natural language processing of unstructured clinical notes. She will discuss challenges and pitfalls in utilizing electronic medical record data for HIV-related predictive modeling, as well as implications for implementation in clinical practice.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Jessica Ridgway, MD, MS, is an Associate Professor of Medicine in the Section of Infectious Diseases and Global Health and Director of Medical Informatics at the University of Chicago. She is Director of Predictive Analytics for the Chicago Center for HIV Elimination. Her research focuses on utilizing large electronic medical record databases to understand HIV epidemiology across the continuum of care and implementation of clinical informatics interventions to improve HIV care and prevention.
Host: USC Center for Artificial Intelligence in Society (CAIS)
More Info: https://usc.zoom.us/webinar/register/WN_gEn8OHXBQnmpYiWc9hJimw
Location: Zoom only - https://usc.zoom.us/webinar/register/WN_gEn8OHXBQnmpYiWc9hJimw
Audiences: Everyone Is Invited
Contact: CS Events
Event Link: https://usc.zoom.us/webinar/register/WN_gEn8OHXBQnmpYiWc9hJimw
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ECE-EP Seminar - Zaijun Chen, Tuesday, March 26th at 2pm in EEB 248
Tue, Mar 26, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Zaijun Chen, University of Southern California
Talk Title: Large-Scale Photonic Circuits for AI Computing and Metrology
Series: ECE-EP Seminar
Abstract: The rapid expansion of artificial intelligence (AI), internet of things (IoT) and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware. Optical computing is emerging to enable new computing paradigms with high optical bandwidth, parallel processing, and low-loss data movement. However, the scalability of existing optical accelerators is limited by the electro-optic conversion efficiency, large photonic device footprints, lack of optical nonlinearity, etc. In this talk, I will present our computing approaches to overcomes these bottlenecks with hyperdimensional multiplexing. Our experimental results have realized large-scale AI processing in models with half a million parameters, a full-system energy efficiency at few femtojoule per operation (fJ/OP) and computing density of 6 TOP/(mm2·s). This computing efficiency and density outperform the state-of-the-art digital processors for the first time, with 100 folds improvement. In the last part, I will cover some interferometry techniques based on laser frequency combs for broadband, high-speed precision sensing and metrology at quantum-limited sensitivity.
Biography: Zaijun Chen is a research assistant professor at the Ming Hsieh Department of Electrical and Computer Engineering at USC. He accomplished his Ph.D. degree (summa cum laude) in Prof. Theodor W. Haensch's (Nobel laureate 2005) group at Max-Planck Institute of Quantum Optics (MPQ) in 2019, and postdoc with Prof. Dirk Englund at MIT. He is a recipient of 2023 SPIE best paper award for Machine learning and Artificial intelligence, 2023 Sony faculty Innovation Award, 2023 Optica Foundation Challenge Award, and leading PI in a 2023 DARPA project (NaPSAC). He is an early career editor of Advanced Photonics.
Host: ECE-Electrophysics
More Information: Zaijun Chen Seminar Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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PhD Dissertation Defense - Aniruddh Puranic
Tue, Mar 26, 2024 @ 03:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Dissertation Defense - Aniruddh Puranic Committee: Jyotirmoy V. Deshmukh (Chair), Gaurav Sukhatme, Stefanos Nikolaidis, and Stephen Tu Title: Sample-Efficient and Robust Neurosymbolic Learning from Demonstrations Abstract: Learning-from-demonstrations (LfD) is a popular paradigm to obtain effective robot control policies for complex tasks via reinforcement learning (RL) without the need to explicitly design reward functions. However, it is susceptible to imperfections in demonstrations and also raises concerns of safety and interpretability in the learned control policies. To address these issues, this thesis develops a neurosymbolic learning framework which is a hybrid method that integrates neural network-based learning with symbolic (e.g., rule, logic, graph) reasoning to leverage the strengths of both approaches. Specifically, this framework uses Signal Temporal Logic (STL) to express high-level robotic tasks and its quantitative semantics to evaluate and rank the quality of demonstrations. Temporal logic-based specifications allow us to create non-Markovian rewards and are also capable of defining interesting causal dependencies between tasks such as sequential task specifications. This dissertation presents the LfD-STL framework that learns from even suboptimal/imperfect demonstrations and STL specifications to infer reward functions; these reward functions can then be used by reinforcement learning algorithms to obtain control policies. Experimental evaluations on several diverse set of environments show that the additional information in the form of formally specified task objectives allows the framework to outperform prior state-of-the-art LfD methods. Many real-world robotic tasks consist of multiple objectives (specifications), some of which may be inherently competitive, thus prompting the need for deliberate trade-offs. This dissertation then further extends the LfD-STL framework by a developing metric - performance graph - which is a directed graph that utilizes the quality of demonstrations to provide intuitive explanations about the performance and trade-offs of demonstrated behaviors. This performance graph also offers concise insights into the learning process of the RL agent, thereby enhancing interpretability, as corroborated by a user study. Finally, the thesis discusses how the performance graphs can be used as an optimization objective to guide RL agents to potentially learn policies that perform better than the (imperfect) demonstrators via apprenticeship learning (AL). The theoretical machinery developed for the AL-STL framework examines the guarantees on safety and performance of RL agents. https://usc.zoom.us/j/98964159897?pwd=a2ljaGNEOGcvMkl1WU9yZENPc0M1dz09
Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Everyone Is Invited
Contact: Aniruddh Puranic
Event Link: https://usc.zoom.us/j/98964159897?pwd=a2ljaGNEOGcvMkl1WU9yZENPc0M1dz09
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Epstein Institute, ISE 651 Seminar Class
Tue, Mar 26, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Xuan Song, Assistant Professor, James A. Chisman Faculty Fellow, Department of Industrial & Systems Engr, Iowa Technology Institute
Talk Title: Toward Mild Additive Manufacturing for Extremes
Host: Prof. Yong Chen
More Information: March 26, 2024.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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Helicopter Accident Investigation HAI 24-2
Wed, Mar 27, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
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Gas Turbine Engine Accident Investigation GTAI 24-2
Wed, Mar 27, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
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EiS Communications Hub Drop-In Hours
Wed, Mar 27, 2024 @ 10:00 AM - 01:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Viterbi Ph.D. students are invited to stop by the EiS Communications Hub for one-on-one instruction for their academic and professional communications tasks. All instruction is provided by Viterbi faculty at the Engineering in Society Program.
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home?authuser=0
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EiS Communications Hub Drop-In Hours
Wed, Mar 27, 2024 @ 10:00 AM - 01:00 PM
Engineering in Society Program
Student Activity
Drop-in hours for writing and speaking support for Viterbi Ph.D. students
Location: Ronald Tutor Hall of Engineering (RTH) - 222
Audiences: Everyone Is Invited
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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CS Colloquium: Paul Liang - Foundations of Multisensory Artificial Intelligence
Wed, Mar 27, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Paul Liang, CMU
Talk Title: Foundations of Multisensory Artificial Intelligence
Abstract: Building multisensory AI systems that learn from multiple sensory inputs such as text, speech, video, real-world sensors, wearable devices, and medical data holds great promise for impact in many scientific areas with practical benefits, such as in supporting human health and well-being, enabling multimedia content processing, and enhancing real-world autonomous agents. In this talk, I will discuss my research on the machine learning principles of multisensory intelligence, as well as practical methods for building multisensory foundation models over many modalities and tasks. In the first half, I will present a theoretical framework formalizing how modalities interact with each other to give rise to new information for a task. These interactions are the basic building blocks in all multimodal problems, and their quantification enables users to understand their multimodal datasets and design principled approaches to learn these interactions. In the second part, I will present my work in cross-modal attention and multimodal transformer architectures that now underpin many of today’s multimodal foundation models. Finally, I will discuss our collaborative efforts in scaling AI to many modalities and tasks for real-world impact on mental health, cancer prognosis, and robot control. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Paul Liang is a Ph.D. student in Machine Learning at CMU, advised by Louis-Philippe Morency and Ruslan Salakhutdinov. He studies the machine learning foundations of multisensory intelligence to design practical AI systems that integrate, learn from, and interact with a diverse range of real-world sensory modalities. His work has been applied in affective computing, mental health, pathology, and robotics. He is a recipient of the Siebel Scholars Award, Waibel Presidential Fellowship, Facebook PhD Fellowship, Center for ML and Health Fellowship, Rising Stars in Data Science, and 3 best paper/honorable mention awards at ICMI and NeurIPS workshops. Outside of research, he received the Alan J. Perlis Graduate Student Teaching Award for instructing courses on multimodal ML and advising students around the world in directed research.
Host: Willie Neiswanger / Xiang Ren
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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Computer Science General Faculty Meeting
Wed, Mar 27, 2024 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS Chair
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PhD Thesis Proposal- Xin Qin
Wed, Mar 27, 2024 @ 12:45 PM - 01:45 PM
Thomas Lord Department of Computer Science
Student Activity
PhD Thesis Proposal- Xin Qin
Title: Data-driven and Logic-based Analysis of Learning-enabled Cyber-Physical Systems
Committee: Jyotirmoy Deshmukh, Chao Wang, Souti Chattopadhyay, Yan Liu and Paul Bogdan
Abstract: Rigorous analysis of cyber-physical systems (CPS) is becoming increasingly important, especially for safety-critical applications that use learning-enabled components. In this proposal, we will discuss various pieces of a broad framework that enable scalable reasoning techniques tuned to modern software design practices in autonomous CPS applications. The proposal will center around three main pillars: (1) Statistical verification techniques to give probabilistic guarantees on system correctness; here, we treat the underlying CPS application as a black-box and use distribution-free and model-free techniques to provide probabilistic correctness guarantees. (2) Predictive monitoring techniques that use physics-based or data-driven models of the system to continuously monitor logic-based requirements of systems operating in highly uncertain environments; this allows us to design runtime mitigation approaches to take corrective actions before a safety violation can occur. (3) Robust testing for CPS using reinforcement learning. We train an agent to produce a policy to initiate unsafe behaviors in similar target systems without the need for retraining, thereby allowing for the elicitation of faulty behaviors across various systems. The proposal hopes to demonstrate the scalability of our approaches on various realistic models of autonomous systems.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 349
Audiences: Everyone Is Invited
Contact: Xin Qin
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CS Colloquium: Teodora Baluta - New Algorithmic Tools for Rigorous Machine Learning Security Analysis
Wed, Mar 27, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Teodora Baluta, National University of Singapore
Talk Title: New Algorithmic Tools for Rigorous Machine Learning Security Analysis
Abstract: Machine learning security is an emerging area with many open questions lacking systematic analysis. In this talk, I will present three new algorithmic tools to address this gap: (1) algebraic proofs; (2) causal reasoning; and (3) sound statistical verification. Algebraic proofs provide the first conceptual mechanism to resolve intellectual property disputes over training data. I show that stochastic gradient descent, the de-facto training procedure for modern neural networks, is a collision-resistant computation under precise definitions. These results open up connections to lattices, which are mathematical tools used for cryptography presently. I will also briefly mention my efforts to analyze causes of empirical privacy attacks and defenses using causal models, and to devise statistical verification procedures with ‘probably approximately correct’ (PAC)-style soundness guarantees. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Teodora Baluta is a Ph.D. candidate in Computer Science at the National University of Singapore. She enjoys working on security problems that are both algorithmic in nature and practically relevant. She is one of the EECS Rising Stars 2023, a Google PhD Fellow, a Dean’s Graduate Research Excellence Award recipient and a President’s Graduate Fellowship recipient at NUS. She interned at Google Brain working in the Learning for Code team. Her works are published in security (CCS, NDSS), programming languages/verification conferences (OOPSLA, SAT), and software engineering conferences (ICSE, ESEC/FSE). More details are available on her webpage: https://urldefense.com/v3/__https://teobaluta.github.io/__;!!LIr3w8kk_Xxm!pCgCXC327otABpiCTruPDSq7pyOXJEWhQ5X0UekIkZhAzt8Q0u0y5QtnemfzYURw7fop1LHm8tR_SY5JCA$ .
Host: Mukund Raghothaman
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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AME Seminar
Wed, Mar 27, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Shima Shahab, Virginia Tech
Talk Title: Ultrasound-Responsive Intelligent Material Systems
Abstract: Intelligent material systems, often known as smart materials, may adapt their behavior in response to changes in external stimuli. The use of smart materials in numerous sensitive applications has increased the demand for a remote, wireless, efficient, and physiologically safe stimulus. These needs will be addressed in this presentation by using Focused Ultrasound (FUS) as an external trigger. To achieve the desired response of an ultrasound-responsive smart structure, FUS has the unique property of maintaining both spatial and temporal control and propagating over large distances with low losses. Shape Memory Polymers (SMPs) and piezoelectric (PZT) materials will be discussed as ultrasound-responsive smart materials. First, we will look into the acoustic-thermoelastic dynamics of ultrasound-stimulated SMPs in order to develop next-generation delivery, sensing, and morphing devices. When activated by FUS, SMPs can be manipulated into any temporary shape and then recover to their stress-free permanent shape. FUS is a promising stimulus with the unique and superior capacity to cause localized heating, activate various intermediate shapes, and enable noninvasive shape recovery in polymers. Second, we'll go through the fundamentals of PZT-based Ultrasonic Power Transfer (UPT) systems. UPT along with acoustic holograms is a new technique that relies on piezoelectric receivers to receive FU in selective patterns. UPT is used to wirelessly charge modest to high-power electronics in biomedical implants and enclosed electronic devices working in unmanned aerial and undersea vehicles. Finally, holographic lenses, also referred to as acoustic holograms, will be discussed. These lenses are utilized to generate complicated FUS fields. They save the desired wavefront's phase profile, which is utilized to reconstruct the acoustic pressure field when illuminated by a single acoustic source. Because of its robustness, simplicity, and low cost, the use of holographic lenses for sound modification in medical applications has attracted interest in recent years. Ultrasound-guided thermal therapy is one such application that use the absorbed acoustic field to generate a therapeutic effect within the human body.
Biography: Shima Shahab is Mary V. Jones Faculty Fellow and an Associate Professor in the Department of Mechanical Engineering at Virginia Tech. She completed her Ph.D. and M.S. in Mechanical Engineering at Georgia Institute of Technology. Dr. Shahab is the Director of Multiphysics Intelligent and Dynamical Systems (MInDS) laboratory and an Associate Editor of Journal of Intelligent Material Systems and Structures (JIMSS). Her theoretical and experimental research program focuses on the intersection of smart materials and dynamical systems for various interdisciplinary applications such as contactless ultrasound power transfer, ultrasound responsive polymer-based systems, ultrasound atomization, and acoustic holograms. Dr. Shahab has served as principal investigator on research grants from the National Science Foundation, Alpha Foundation, Oakridge National Laboratory, and Ford Motor Company. In addition to a recent NSF CAREER award, Dr. Shahab is the recipient of ASME Gary Anderson Early Achievement Award. The award recognizes a young researcher on the rise who has already made significant contributions to the field of Adaptive Structures and Material Systems. More at https://me.vt.edu/people/faculty/shahab-shima.html
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09Location: James H. Zumberge Hall Of Science (ZHS) - 252
WebCast Link: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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Alumni Career Panel & Mixer
Wed, Mar 27, 2024 @ 05:00 PM - 06:30 PM
Viterbi School of Engineering Career Connections
Receptions & Special Events
Alumni Career Panel & Mixer connects students with Viterbi Alumni and industry professionals. Distinguished Viterbi Alumni will share their career journey, activities they were involved with on-campus, and advice on how they landed their internships & full-time jobs. You will also be able to network with them after the panel and obtain job search tips and suggestions.
Location: Michelson Center for Convergent Bioscience (MCB) -
Audiences: All Viterbi BS, MS Students
Contact: RTH 218 Viterbi Career Connections
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Min Family Challenge Semi Finals
Wed, Mar 27, 2024 @ 06:00 PM - 08:00 PM
Viterbi Technology Innovation and Entrepreneurship
Receptions & Special Events
Come and hear from this years Min Family Challenge teams as they pitch to a panel of judges and compete for 50k towards their social impact venture. Top teams will advance to the Min Family Challenge Finals.
Location: Sign into EngageSC to View Location
Audiences: Everyone Is Invited
Contact: Johannah Murray
Event Link: https://engage.usc.edu/Viterbitie/rsvp?id=396441
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Gas Turbine Engine Accident Investigation GTAI 24-2
Thu, Mar 28, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
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Helicopter Accident Investigation HAI 24-2
Thu, Mar 28, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
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CS Colloquium: Yangsibo Huang - Auditing Policy Compliance in Machine Learning Systems
Thu, Mar 28, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Yangsibo Huang, Princeton University
Talk Title: Auditing Policy Compliance in Machine Learning Systems
Abstract: As the capabilities of large-scale machine learning models expand, so too do their associated risks. There is an increasing demand for policies that mandate these models to be safe, privacy-preserving, and transparent regarding data usage. However, there are significant challenges with developing enforceable policies and translating the qualitative mandates into quantitative, auditable, and actionable criteria. In this talk, I will present my work on addressing the challenges. I will first share my exploration of privacy leakage and mitigation strategies in distributed training. Then, I will explore strategies for auditing compliance with data transparency regulations. I will also examine methods to quantify and assess the fragility of safety alignments in Large Language Models. Finally, I will discuss my plans for future research directions, including collaboration with policy researchers and policymakers. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Yangsibo Huang is a Ph.D. candidate and Wallace Memorial Fellow at Princeton University. She has been doing research at the intersection of machine learning, systems, and policy, with a focus on auditing and improving machine learning systems’ compliance with policies, from the perspectives of privacy, safety, and data usage. She interned at Google AI, Meta AI, and Harvard Medical School and was named an EECS rising star in 2023.
Host: Yue Zhao
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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ECE-S Seminar - Dr. Amrita Roy Chowdhury
Thu, Mar 28, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Amrita Roy Chowdhury, CRA/CCC CIFellow, University of California, San Diego
Talk Title: Data Privacy in the Decentralized Era
Abstract: Data is today generated on smart devices at the edge, shaping a decentralized data ecosystem comprising multiple data owners (clients) and a service provider (server). Clients interact with the server with their personal data for specific services, while the server performs analysis on the joint dataset. However, the sensitive nature of the involved data, coupled with inherent misalignment of incentives between clients and the server, breeds mutual distrust. Consequently, a key question arises: How to facilitate private data analytics within a decentralized data ecosystem, comprising multiple distrusting parties?
My research shows a way forward by designing systems that offer strong and provable privacy guarantees while preserving complete data functionality. I accomplish this by systematically exploring the synergy between cryptography and differential privacy, exposing their rich interconnections in both theory and practice. In this talk, I will focus on two systems, CryptE and EIFFeL, which enable privacy-preserving query analytics and machine learning, respectively.
Biography: Amrita Roy Chowdhury is a CRA/CCC CIFellow at University of California-San Diego, working with Prof. Kamalika Chaudhuri. She graduated with her PhD from University of Wisconsin-Madison and was advised by Prof. Somesh Jha. She completed her Bachelor of Engineering in Computer Science from the Indian Institute of Engineering Science and Technology, Shibpur where she was awarded the President of India Gold Medal. Her work explores the synergy between differential privacy and cryptography through novel algorithms that expose the rich interconnections between the two areas, both in theory and practice. She has been recognized as a Rising Star in EECS in 2020 and 2021, and a Facebook Fellowship finalist, 2021. She has also been selected as a UChicago Rising Star in Data Science, 2021.
Host: Dr. Viktor Prasanna, prasanna@usc.edu
More Info: https://usc.zoom.us/j/94200520726?pwd=U1ZSd3VUVzIrMVI3QUE3d25hVzIvZz09
Webcast: https://usc.zoom.us/j/94200520726?pwd=U1ZSd3VUVzIrMVI3QUE3d25hVzIvZz09More Information: 2024.03.28 ECE-S Seminar - Amrita Roy Chowdhury.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
WebCast Link: https://usc.zoom.us/j/94200520726?pwd=U1ZSd3VUVzIrMVI3QUE3d25hVzIvZz09
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://usc.zoom.us/j/94200520726?pwd=U1ZSd3VUVzIrMVI3QUE3d25hVzIvZz09
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NL Seminar-Informative Example Selection for In-Context Learning
Thu, Mar 28, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Shivanshu Gupta, UCI
Talk Title: Informative Example Selection for In-Context Learning
Series: NL Seminar
Abstract: 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 inform us at (nlg-seminar-host(at)isi.edu) beforehand so we’ll 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. For more information on the NL Seminar series and upcoming talks, please visit: https://nlg.isi.edu/nl-seminar/ In-context Learning (ICL) uses large language models (LLMs) for new tasks by conditioning them on prompts comprising a few task examples. With the rise of LLMs that are intractable to train or hidden behind APIs, the importance of such a training-free interface cannot be overstated. However, ICL is known to be critically sensitive to the choice of in-context examples. Despite this, the standard approach for selecting in-context examples remains to use general-purpose retrievers due to the limited effectiveness and training requirements of prior approaches. In this talk, I'll posit that good in-context examples demonstrate the salient information necessary to solve a given test input. I'll present efficient approaches for selecting such examples, with a special focus on preserving the training-free ICL pipeline. Through results with a wide range of tasks and LLMs, I'll demonstrate that selecting informative examples can indeed yield superior ICL performance.
Biography: Shivanshu Gupta is a Computer Science Ph.D. Candidate at the University of California Irvine, advised by Sameer Singh. Prior to this, he was a Research Fellow at LinkedIn and Microsoft Research India, and completed his B.Tech. and M.Tech. in Computer Science at IIT Delhi. His primary research interests are systematic generalization, in-context learning, and multi-step reasoning capabilities of large language models. If speaker approves to be recorded for this NL Seminar talk, it will be posted on the USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI. Subscribe here to learn more about upcoming seminars: https://www.isi.edu/events/
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://www.youtube.com/watch?v=Vqvy4XIOtcELocation: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=Vqvy4XIOtcE
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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PhD Dissertation Defense - Chuizheng Meng
Thu, Mar 28, 2024 @ 01:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
Committee Members: Yan Liu (Chair), Willie Neiswanger, and Assad A Oberai (external member)
Title: Trustworthy Spatiotemporal Prediction Models
Abstract: With the great success of data-driven machine learning methods, concerns with the trustworthiness of machine learning models have been emerging in recent years. From the modeling perspective, the lack of trustworthiness amplifies the effect of insufficient training data. Purely data-driven models without constraints from domain knowledge tend to suffer from over-fitting and losing the generalizability of unseen data. Meanwhile, concerns with data privacy further obstruct the availability of data from more providers. On the application side, the absence of trustworthiness hinders the application of data-driven methods in domains such as spatiotemporal forecasting, which involves data from critical applications including traffic, climate, and energy. My dissertation constructs spatiotemporal prediction models with enhanced trustworthiness from both the model and the data aspects. For model trustworthiness, the dissertation focuses on improving the generalizability of models via the integration of physics knowledge. For data trustworthiness, the proposal proposes a spatiotemporal forecasting model in the federated learning context, where data in a network of nodes is generated locally on each node and remains decentralized. Furthermore, the dissertation amalgamates the trustworthiness from both aspects and combines the generalizability of knowledge-informed models with the privacy preservation of federated learning for spatiotemporal modeling.Location: Waite Phillips Hall Of Education (WPH) - B26
Audiences: Everyone Is Invited
Contact: Chuizheng Meng
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ECE-EP Faculty Candidate - Srujan Meesala, Thursday, March 28th at 2pm in EEB 248
Thu, Mar 28, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Srujan Meesala, Caltech
Talk Title: Generating quantum correlations between light and Microwaves with a chip-scale device
Series: ECE-EP Seminar
Abstract: Experimental capabilities in modern quantum science and engineering allow the control of quantum states in a variety of solid-state systems such as superconducting circuits, atomic-scale defect centers, and chip-scale optical and acoustic structures. Controlling interactions between physically different qubits across such platforms is a frontier in the quest to build quantum hardware at scale and to probe the coherence limits of solid-state devices. I will present recent progress on constructing a quantum interconnect between superconducting qubits and optical photons. By integrating specially engineered optical, mechanical, and superconducting microwave components in a chip-scale transducer, we made a photon pair source and used it to generate single optical and microwave photons in entangled pairs. Such devices can be used to connect superconducting qubits in distant cryogenic nodes using room-temperature fiber-optic communication channels. I will discuss open challenges with such transducers and a few near-term routes to address them. I will conclude with results from a different set of experiments where we used nanomechanical devices to control the electronic structure and coherence limits of a spin qubit in an atomic-scale defect center.
Biography: Srujan Meesala is an IQIM Postdoctoral Scholar at Caltech in Oskar Painter's research group. He received his PhD from Harvard where he worked in Marko Loncar's research group.
Host: ECE-EP
More Information: Srujan Meesala Seminar Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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CS Colloquium: Ram Sundara Raman - Global Investigation of Network Connection Tampering
Thu, Mar 28, 2024 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ram Sundara Raman, University of Michigan
Talk Title: Global Investigation of Network Connection Tampering
Abstract: As the Internet's user base and criticality of online services continue to expand daily, powerful adversaries like Internet censors are increasingly monitoring and restricting Internet traffic. These adversaries, powered by advanced network technology, perform large-scale connection tampering attacks seeking to prevent users from accessing specific online content, compromising Internet availability and integrity. In recent years, we have witnessed recurring censorship events affecting Internet users globally, with far-reaching social, financial, and psychological consequences, making them important to study. However, characterizing tampering attacks at the global scale is an extremely challenging problem, given intentionally opaque practices by adversaries, varying tampering mechanisms and policies across networks, evolving environments, sparse ground truth, and safety risks in collecting data. In this talk, I will describe my research on building empirical methods to characterize connection tampering globally and investigate the network technology enabling tampering. First, I will describe a modular design for the Censored Planet Observatory that enables it to remotely and sustainably measure Internet censorship longitudinally in more than 200 countries. I will introduce time series analysis methods to detect key censorship events in longitudinal Censored Planet data, and reveal global censorship trends. I will also briefly describe methods to detect connection tampering using purely passive data. Next, I will introduce novel network measurement methods for locating and examining network devices that perform censorship. Finally, I will describe exciting ongoing and future research directions, such as building intelligent measurement platforms. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Ram Sundara Raman is a PhD candidate in Computer Science and Engineering at the University of Michigan, advised by Prof. Roya Ensafi. His research lies in the intersection of computer security, privacy, and networking, employing empirical methods to study large-scale Internet attacks. Ram has been recognized as a Rising Star at the Workshop on Free and Open Communications on the Internet (FOCI), and was awarded the IRTF Applied Networking Research Prize in 2023. His work has helped produce one of the biggest active censorship measurement platforms, the Censored Planet Observatory, and has helped prevent large-scale attacks on end-to-end encryption.
Host: Jyo Deshmukh
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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Gas Turbine Engine Accident Investigation GTAI 24-2
Fri, Mar 29, 2024 @ 08:00 AM - 12:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
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Helicopter Accident Investigation HAI 24-2
Fri, Mar 29, 2024 @ 08:00 AM - 12:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
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EiS Communications Hub Drop-In Hours
Fri, Mar 29, 2024 @ 10:00 AM - 01:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Viterbi Ph.D. students are invited to stop by the EiS Communications Hub for one-on-one instruction for their academic and professional communications tasks. All instruction is provided by Viterbi faculty at the Engineering in Society Program.
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home?authuser=0
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EiS Communications Hub Drop-In Hours
Fri, Mar 29, 2024 @ 10:00 AM - 01:00 PM
Engineering in Society Program
Student Activity
Drop-in hours for writing and speaking support for Viterbi Ph.D. students
Location: Ronald Tutor Hall of Engineering (RTH) - 222
Audiences: Everyone Is Invited
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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Alfred E. Mann Department of Biomedical Engineering
Fri, Mar 29, 2024 @ 11:00 AM - 11:50 AM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hadley Sikes, Ph.D., The Willard Henry Dow Professor and Graduate Officer in Chemical Engineering, and PI in the Antimicrobial Resistance Interdisciplinary Research Group in Singapores CREATE campus MIT
Talk Title: Protein and reaction engineering for accessible, scalable medical diagnostics
Abstract: Paper-based medical diagnostic tests have an appealingly low cost of goods and can be very simple to operate. However, new tests typically take months to a year or more to develop, driving up costs. A longstanding focus in our lab has been developing and applying an engineering design approach to new medical diagnostic tests. One of the slow and expensive steps in developing diagnostic immunoassays is identification of pairs, or sets in the case of multiplexed assays, of affinity reagents that simultaneously bind non-overlapping target epitopes and also do not cross-react with one another or complex matrix components. Engineered binding molecules derived from a thermophilic organism will be presented as alternatives to antibodies, human or camelid, along with a method for selecting pairs or sets of these reagents for diagnostic immunoassays. Analysis of reaction rates and fluid flow within paper-based tests suggested further protein engineering strategies to improve sensitivity. Generalized assay design principles for integrating these engineered proteins into antigen and serology tests will be discussed, as well as innovations in scalable manufacturing of test formats beyond conventional lateral flow tests. Finally, key elements of the commercialization process for new diagnostic tests will be presented, including protection of intellectual property, technology transfer to partners, manufacturing under ISO13485 certification, usability and clinical testing, and regulatory filings.
Biography: Hadley D. Sikes is the Willard Henry Dow Professor and Graduate Officer in Chemical Engineering at the Massachusetts Institute of Technology and a PI in the Antimicrobial Resistance Interdisciplinary Research Group in Singapores CREATE campus. She advises a team of researchers in the application of physical principles to design, synthesize, characterize, and test molecules for utility in detecting and understanding disease. Hadley earned degrees in chemistry, a BS at Tulane University (D.K. Schwartz lab) and a PhD Stanford University (C.E.D. Chidsey lab) and trained as a postdoctoral scholar in chemical engineering at the University of Colorado, Boulder (C.N. Bowman lab), and at the California Institute of Technology (F.H. Arnold lab) prior to joining the faculty at MIT. Hadley is an Associate Editor at Bioengineering and Translational Medicine.
Host: Maral Mousavi
Location: Olin Hall of Engineering (OHE) - 100B
Audiences: Everyone Is Invited
Contact: Carla Stanard
