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CA DREAMS - Technical Seminar Series
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Fri, Jun 06, 2025 @ 12:00 PM - 01:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: J. Joshua Yang, Professor, USC
Talk Title: Real-Time RF Signal Processing in Extreme Environments with Memristors
Series: CA DREAMS - Technical Seminar Series
Abstract: The von Neumann bottleneck significantly increases energy consumption and processing delays in modern computing systems, especially for data-intensive tasks such as real-time RF signal processing. Memristor-based in-memory computing addresses this challenge by performing computations directly within analog memory arrays. In this seminar, I will present a memristor-based analog system-on-chip (SoC) designed for real-time RF signal processing. This innovative SoC integrates real-time Discrete Fourier Transform (DFT) computation and neural network processing within a unified analog memristor framework. Furthermore, due to the inherent robustness of memristors in extreme environments, including radiation exposure and high-temperature conditions, this technology is highly suitable for harsh environment applications. Our analog SoC demonstrates substantial improvements in energy efficiency and throughput compared to traditional digital computing systems, making it a promising solution for next-generation RF signal processing applications under extreme conditions.
Biography: J. Joshua Yang is the Arthur B. Freeman Chair Professor in the Department of Electrical and Computer Engineering at the University of Southern California (USC). His research focuses on post-CMOS hardware for neuromorphic computing, machine learning, and artificial intelligence, in which he has published several pioneering papers and holds over 120 granted U.S. patents. Dr. Yang is the Founding Chair of the IEEE Neuromorphic Computing Technical Committee, Director of the USC–Air Force Center of Excellence on Neuromorphic Computing, and Co-Founder of TetraMem Inc. He has received numerous honors, including the USC senior faculty research award and the Powell Faculty Research Award. He serves as an Associate Editor for associate editor of Science Advances (AAAS), ED-M (IEEE), PNAS (NAS). Dr. Yang is a Clarivate™ Highly Cited Researcher and ranked among the Top Scientists by Research.com. He is a Fellow of IEEE and the National Academy of Inventors (NAI), recognized for his seminal contributions to resistive switching materials and devices for non-volatile memory and neuromorphic computing.
Host: Dr. Steve Crago
More Info: https://www.isi.edu/events/5813/real-time-rf-signal-processing-in-extreme-environments-with-memristors/
Webcast: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addonWebCast Link: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addon
Audiences: Everyone Is Invited
Contact: Amy Kasmir
Event Link: https://www.isi.edu/events/5813/real-time-rf-signal-processing-in-extreme-environments-with-memristors/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Liquid Rocket Engines for Spacecraft Pressure-Fed Propulsion SystemsSat, Jun 07, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: Dr. Ghanshyam Purshottamda Purohit, USC Astronautical Engineering
Talk Title: Liquid Rocket Engines for Spacecraft Pressure-Fed Propulsion Systems
Abstract: This three-day course provides an overview of the fundamental concepts and technologies of modern satellite liquid propellant rocket engines. The course will concentrate scientific and engineering foundations of pressure - fed, monopropellant, bipropellant, dual mode, and secondary combustion augmented thrusters for satellite orbit-raising and station-keeping operations.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/astronautical-engineering/liquid-rocket-engines-spacecraft-pressure-fed-propulsion-systems/
Audiences: Liquid Rocket Engines Students
Contact: VASE Executive Education
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Black Belt
Mon, Jun 09, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Black Belt
Tue, Jun 10, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Black Belt
Wed, Jun 11, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
PhD Dissertation Defense - Chrysovalatnis Anastasiou
Wed, Jun 11, 2025 @ 12:30 PM - 02:30 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Recovering Trajectories From Location Data Probablistically
Date and Time: Wednesday, June 11th, 2025 | 12:30p - 2:30p
Location: PHE 106
Committee Members: Cyrus Shahabi (Chair), Jose-Luis Ambite, Marlon Boarnet
Abstract: Understanding urban mobility is crucial for effective city planning, transportation management, and the development of responsive location-based services. However, challenges associated with real-world trajectory data often significantly hamper the derivation of robust insights. These include privacy restrictions limiting access to detailed movement histories, inherent sparsity in collected data points, and uncertainty stemming from sensor inaccuracies. Existing approaches rely on deterministic assumptions (like shortest paths), or necessitate extensive calibration or large, potentially biased training datasets, hindering progress.
This thesis addresses these critical challenges by developing and evaluating a suite of novel data-driven and probabilistic methodologies. We first introduce a purely data-driven technique for time-dependent reachability analysis that leverages raw trajectory data directly, thereby bypassing the complexities of traditional graph-based. To handle data sparsity effectively, we propose time-variant, road network-constrained probabilistic models ("bridgelets"), which realistically represent the inherent uncertainty of movement between sparse location samples. Furthermore, we develop a comprehensive framework (VPE), to reliably estimate vehicle visit probabilities on road segments using observations from uncertain and potentially unreliable roadside sensors.
The practical effectiveness of the proposed methods is rigorously evaluated through extensive experiments using large-scale, real-world datasets from various cities. Quantitative and qualitative results demonstrate that our probabilistic and data-driven approaches significantly improve accuracy and efficiency compared to baseline and traditional techniques. Collectively, the contributions of this thesis provide practical, robust, and innovative tools for researchers, planners, and policymakers to gain deeper, more reliable insights into complex urban mobility dynamics, enabling more informed decision-making even when faced with prevalent data limitations.Location: Charles Lee Powell Hall (PHE) - 106
Audiences: Everyone Is Invited
Contact: Chrysovalantis Anastasiou
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Suyash P. Awate Seminar - Robust and Data-Scarce Statistical Learning for Improved Neuroimaging, Wednesday, June 11th at 2pm in EEB 132 & Zoom
Wed, Jun 11, 2025 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Suyash P. Awate, Indian Institute of Technology (IIT) Bombay
Talk Title: Robust and Data-Scarce Statistical Learning for Improved Neuroimaging
Series: ECE Seminar
Abstract: Improvements in medical imaging, image-reconstruction, and image-quality-enhancement continue to push towards enabling higher resolution in space and/or time, e.g., in dynamic MRI, and towards lower radiation dose, e.g., in PET and CT. While learning-based approaches hold great potential in pushing the state of the art, they are limited by the unavailability of large (high-quality) datasets for supervised training. This talk describes our recent methods for image reconstruction and quality enhancement that can learn from limited data, model uncertainty estimates associated with their outputs, and exhibit robustness to out-of-distribution data. We design these methods to leverage statistical modeling paradigms using traditional machine learning as well as deep learning.
Biography: Suyash P. Awate is the Asha and Keshav Bhide Chair Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (IIT) Bombay. His research focuses on quantitative methods and applications in medical image computing, leveraging principles in statistical inference and machine learning. He has around 100 full-length publications in well-known conferences and journals, receiving many best-paper awards/nominations and honors. He was a Program Chair of IEEE ISBI 2022, and serves as an Associate Editor of Medical Image Analysis. More information available at https://www.cse.iitb.ac.in/~suyash/
Host: Richard Leahy
More Info: https://usc.zoom.us/j/91606117125?pwd=zLMkLtb4EjnEvGA1u5O6sxlwnEjaoq.1
More Information: Suyash Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/91606117125?pwd=zLMkLtb4EjnEvGA1u5O6sxlwnEjaoq.1
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Black Belt
Thu, Jun 12, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Pre-SPARK seminar
Thu, Jun 12, 2025 @ 12:30 PM - 01:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Daria Mochly-Rosen, Professor of Chemical & Systems Biology @ Stanford Cellular/Molecular Engineering of Pharmaceuticals
Talk Title: SPARKing Translation at Stanford: 19 Years of Experience (2006- )
Host: Eun Ji Chung
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Yi Huang
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
PhD Dissertation Defense - Xisen Jin
Thu, Jun 12, 2025 @ 01:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Towards Continual Learning of Language Models in the Wild
Date and Time: Thursday, June 12th, 2025 | 1:00p - 3:00p
Location: RTH 306
Committee Members: Xiang Ren (Chair), Jesse Thomason, Mahdi Soltanolkotabi
Abstract: Language language models (LLMs/LMs) have become foundations of many artificial intelligence (AI) applications, and greatly benefited users in seeking information and completing tasks. Alongside the success of LLMs, there is an increasing need to promptly update these models for new application domains, new factual knowledge, and mitigating harmful behaviors. The large-scale models and the complicated data distributions have introduced unforeseen challenges in earlier study of continual learning; at the same time, new paradigms of building models, e.g., fine-tuning open-source models, have become prevalent. These new challenges and resources create a context of continual learning of language models, which we term continual learning in the wild, that differentiates the problem from the past study.
The thesis focuses on identifying and addressing the emerging challenges in continual learning of language models. In the first part of the thesis, I propose training and evaluation protocols representative of two different goals of continual learning. I create two datasets, namely a domain-incremental research paper stream and a chronologically-ordered tweet stream, alongside downstream datasets to test model capability. In addition, I extensively evaluate existing or new continual learning algorithms for the setup and identify that knowledge distillation from past model checkpoints stands out as an effective continual learning algorithm.
In the second part of the thesis, I propose to study how merging weights of existing models can achieve the goal of fusing knowledge of multiple models without access to original training data. I propose a novel model merging algorithm, RegMean, which is simple to implement, computationally efficient, and outperforms baseline merging algorithms significantly.
In the remaining part of the thesis, I introduce my work on analyzing patterns of upstream knowledge forgetting in continual learning. I interpret significant patterns of forgetting in upstream data that arise when fine-tuning LLMs. The analysis demonstrates that accurate predictions about forgetting can be made using embedding similarity models, or matrix completion from a small set of observed occurrences of forgetting. I further illustrate how predicting forgetting can lead to the development of simple and effective continual learning algorithms.Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Everyone Is Invited
Contact: Xisen Jin
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Black Belt
Fri, Jun 13, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
CA DREAMS - Technical Seminar Series
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Fri, Jun 13, 2025 @ 12:00 PM - 01:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Rehan Kapadia, Professor, USC
Talk Title: MOSIS 2.0
Series: CA DREAMS - Technical Seminar Series
Abstract: Since its founding in 1981, the original MOSIS service revolutionized VLSI prototyping by letting universities, startups, and government labs share multiproject wafers—shrinking tape-out costs and accelerating more than 60 000 chips to silicon. Today, MOSIS 2.0 builds on that legacy, expanding services to include access to IP, design services, and low-volume semiconductor prototyping services. In this talk, we will discuss the current state of the offerings and lay out a roadmap for the future.
Biography: Professor Rehan Kapadia joined the faculty of the University of Southern California in the Ming Hsieh Department of Electrical and Computer Engineering in July 2014. He currently holds the Colleen and Roberto Padovani Early Career Chair, and serves as Director of MOSIS 2.0 and Director of the John O’Brien Nanofabrication Laboratory. He received his bachelors in electrical engineering from the University of Texas at Austin in 2008, and his Ph.D. in electrical engineering from the University of California, Berkeley in 2013. During his time at Berkeley, he was a National Science Foundation Graduate Research Fellow and winner of the David J. Sakrison Memorial Prize for outstanding research. At USC, he is the recipient of AFOSR and ONR Young Investigator Awards and the Peter Mark Memorial Award from the AVS. His interests lie at the intersection of material science and electrical engineering focusing on non-equilibrium electron devices, and materials growth technologies for next-generation electronic and photonic devices.
Host: Dr. Steve Crago
More Info: https://www.isi.edu/events/5862/mosis-2-0/
Webcast: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addonWebCast Link: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addon
Audiences: Everyone Is Invited
Contact: Amy Kasmir
Event Link: https://www.isi.edu/events/5862/mosis-2-0/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Liquid Rocket Engines for Spacecraft Pressure-Fed Propulsion Systems
Sat, Jun 14, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: Dr. Ghanshyam Purshottamda Purohit, USC Astronautical Engineering
Talk Title: Liquid Rocket Engines for Spacecraft Pressure-Fed Propulsion Systems
Abstract: This three-day course provides an overview of the fundamental concepts and technologies of modern satellite liquid propellant rocket engines. The course will concentrate scientific and engineering foundations of pressure - fed, monopropellant, bipropellant, dual mode, and secondary combustion augmented thrusters for satellite orbit-raising and station-keeping operations.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/astronautical-engineering/liquid-rocket-engines-spacecraft-pressure-fed-propulsion-systems/
Audiences: Liquid Rocket Engines Students
Contact: VASE Executive Education
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
PhD Thesis Proposal - Understanding the Role of Emotions in Online Opinion Polarization
Tue, Jun 17, 2025 @ 02:00 PM - 03:30 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Understanding the Role of Emotions in Online Opinion Polarization
Time and Date: Tuesday, June 17th, 2025 | 2:00p - 3:30p
Location: EEB 631
Committee Members: Kristina Lerman (Chair), Fred Morstatter, Emilio Ferrara, Lindsay Young, and Pablo Barbera
Abstract:
The thesis investigates how emotional dynamics shape ideological divisions in online discourse, particularly in the wake of issue politicization. By integrating social network analysis with cutting-edge natural language processing techniques, the study addresses three central questions: What emotions do individuals express in online discussions? How do others respond to these emotional expressions? And do these emotional exchanges influence opinion formation over time? Analyzing large-scale social media data, the thesis identifies patterns of emotional expression and reception and traces the role of affective in opinion formation. The findings illuminate the emotional undercurrents of polarization, highlighting how networked emotional exchanges can both reflect and intensify political divides in contemporary digital communication environments.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 631
Audiences: Everyone Is Invited
Contact: Ashwin Rao
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
PhD Dissertation Defense - Siyi Guo
Wed, Jun 18, 2025 @ 02:00 PM - 03:30 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Learning Social Representations for Causal Understanding of Heterogeneous and Dynamic Online Behavor
Date and Time: Wednesday, June 8th, 2025 | 2:00pm
Location: RTH 114
Committee Members: Kristina Lerman, Emilo Ferrara, Urbashi Mitra
Abstract: Social media has become a dominant force in shaping public discourse, civic engagement, and individual behavior, offering a rich but challenging environment for studying human beliefs, behaviors, and decision-making at scale. However, modeling user behavior on these platforms is complicated by multiple challenges---the massive volume of data, multi-modality, heterogeneity across users and platforms, rapidly evolving dynamics, scarcity of annotations, and difficulty in causal analysis from observational data.
This dissertation presents a framework for monitoring, explaining, modeling, and intervening in online user behavior, that addresses the challenges of handling complex and dynamic social media data. First, to understand users' reactions to real-world events in a dynamic online environment, we propose an unsupervised methodology for detecting and explaining collective emotional reactions to events, leveraging transformer-based affect modeling and topic-guided explanations. Second, we introduce SoMeR, a self-supervised, multi-view user representation learning framework that captures diverse user behaviors across text, temporal patterns, profiles, and networks, and generalizes across platforms and tasks. Third, we develop DAMF, a domain-adaptive moral foundation inference model that enables robust supervised language modeling from heterogeneous annotated datasets through adversarial training and label distribution balancing. Finally, we propose CausalDANN, a novel framework for estimating causal effects of direct text interventions using LLM-generated counterfactuals and domain adaptation to mitigate distributional shifts.
Together, these contributions advance computational social science by addressing core challenges in tracking and modeling the temporal dynamics and heterogeneity of online user behavior. The methods developed in this thesis integrate causal inference, representation learning, and time series analysis to enable scalable, generalizable, and causally grounded understanding of social media data. In this thesis, I demonstrate their utility by applying the tools to detect and explain online reactions to offline events, identify and forecast harmful behaviors such as coordinated campaigns and hateful speech, understand the evolution of polarized discussions, infer moral values expressed in online language, and evaluate the causal impact of language on moral judgment. This work offers practical tools for researchers and policymakers seeking to better understand and engage with digital populations in complex, polarized, and fast-changing online environments.Location: Ronald Tutor Hall of Engineering (RTH) - 114
Audiences: Everyone Is Invited
Contact: Siyi Guo
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
PhD Thesis Proposal - Zhonghao Shi
Wed, Jun 18, 2025 @ 02:30 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Enabling Personalized Multimodal Interaction for Socially Assistive Robots and Agents
Date and Time: 6/18 2:30pm-4pm
Location: Ronald Tutor Hall (RTH) Room 406
Committee Members:
- Prof. Maja MatariÃÂÃÂ (Committee Chair)
- Prof. Gale Lucas
- Prof. Erdem Biyik
- Prof. David Traum
- Prof. Jonathan Tarbox (external)
Abstract:
Socially assistive robots and agents have shown great promise in providing cost-effective support across domains such as education and healthcare. However, existing socially assistive AI systems still lack the ability to engage users in real-time interactions while effectively supporting users’ cognitive learning goals and socio-emotional needs. This dissertation proposal outlines both completed and remaining work toward enabling personalized, multimodal, real-time interaction capabilities between the robots/agents and human users, particularly for users with diverse needs. The work consists of two main research directions: personalized human perception and individualized interaction design. In the area of personalized human perception, the proposal presents completed work on applying domain adaptation methods to enable personalized multimodal affect recognition for children on the autism spectrum [1], and personalized child speech recognition [2]. It also includes work on benchmarking vision-language models to better understand the performance-latency tradeoffs of frontier models for real-time human perception [3]. In the area of individualized interaction design, the proposal discusses the development of an open-source socially assistive robot learning module for accessible and personalized AI and robotics education [4], as well as work on evaluating and personalizing text-to-speech voices for delivering mental health support [5]. Finally, this proposal will present an ongoing efforts developing a personalized multimodal AI tutor to support speech therapy and learning [6].
[1] Shi, Z., Groechel, T. R., Jain, S., Chima, K., Rudovic, O., & MatariÃÂÃÂ, M. J. (2022). Toward personalized affect-aware socially assistive robot tutors for long-term interventions with children with autism. ACM Transactions on Human-Robot Interaction (THRI), 11(4), 1-28.
[2] Shi, Z., Shi, X., Feng, T., Xu, A., Narayanan, S., & MatariÃÂÃÂ, M. (2025). Examining test-time adaptation for personalized child speech recognition. Paper accepted for presentation at Interspeech 2025.
[3] Shi, Z., Zhao, E., Dennler, N., Wang, J., Xu, X., Shrestha, K., Seita, D., & MatariÃÂÃÂ, M. (2025). HRIBench: Benchmarking vision-language models for real-time human perception in human-robot interaction. Paper accepted for presentation at the International Symposium on Experimental Robotics (ISER) 2025.
[4] Shi, Z.*, O'Connell, A.*, Li, Z.*, Liu, S., Ayissi, J., Hoffman, G., ... & MatariÃÂÃÂ, M. J. (2024, March). Build your own robot friend: An open-source learning module for accessible and engaging AI education. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 21, pp. 23137-23145).
[5] Shi, Z.*, Chen, H.*, Velentza, A. M., Liu, S., Dennler, N., O'Connell, A., & Mataric, M. (2023, March). Evaluating and personalizing user-perceived quality of text-to-speech voices for delivering mindfulness meditation with different physical embodiments. In Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction (pp. 516-524).
[6] Shi, Z.*, Chung, D.*, Du, Y., Zhang, J., Raina, S. & MatariÃÂÃÂ, M. J. (2025) Is AI Ready to Support Speech Therapy for Children? A Systematic Review of AI-Enabled Mobile Apps for Pediatric Speech Therapy. Accepted to Interaction Design and Children (IDC) Conference.
Location: Ronald Tutor Hall of Engineering (RTH) - 406
Audiences: Everyone Is Invited
Contact: Zhonghao Shi
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Ahmed H. Qureshi (Purdue University) - Harnessing Physics Priors for Efficient and Scalable Robot Motion Learning
Thu, Jun 19, 2025 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ahmed H. Qureshi, Purdue University
Talk Title: Harnessing Physics Priors for Efficient and Scalable Robot Motion Learning
Abstract: This talk will outline the use of physics priors towards creating efficient plug-and-play algorithms for robot motion learning. These algorithms require minimal to no expert data and achieve high efficiency in both training and inference while effectively operating in complex, high-dimensional environments under various constraints. Recent advancements in robot motion learning include methods based on imitation and offline reinforcement learning, which are known to necessitate a significant amount of expert trajectories and entail high training times. In contrast, this presentation will introduce a new class of self-supervised, physics-informed neural motion policy learners. These methods aim to directly solve Partial Differential Equations (PDEs) that govern robot motion without depending on expert data or requiring extensive training resources. Additionally, the talk will discuss how these PDEs can create a new robot-motion-friendly mapping feature. We demonstrate that this new mapping feature is better suited for fast robot motion generation than existing mapping features, such as occupancy maps or Sign Distance Fields. This talk will demonstrate that these new physics-informed approaches outperform state-of-the-art imitation learning and offline reinforcement learning methods in terms of scalability, training efficiency, data efficiency, computational planning speed, path quality, and success rates.
Biography: Ahmed Qureshi is an Assistant Professor in the Department of Computer Science at Purdue University. Dr. Qureshi is also currently serving as an Associate Editor for IEEE Transactions on Robotics (TRO) and IEEE Robotics and Automation Letters (RA-L). In 2024, he received the Outstanding Associate Editor award from IEEE RA-L. He has previously served on the program committees of RSS, ICRA, IROS, and CoRL. At Purdue University, Dr. Qureshi directs the Cognitive Robot Autonomy and Learning (CoRAL) Lab. His group conducts fundamental and applied research in robot motion planning and control with the aim of developing robots that can understand the general laws of physics and plan their movements in real time with minimal to no expert demonstrations. His work addresses problems such as scalable and fast motion planning, dexterous manipulation, active perception, and multiagent task and motion planning. Dr. Qureshi's contributions have been recognized with spotlight and best paper awards at various academic venues. Prior to his current roles, he earned his B.S. in Electrical Engineering from NUST, Pakistan, an M.S. in Engineering from Osaka University, Japan, and a Ph.D. in Intelligent Systems, Robotics, and Control from the University of California San Diego.
Host: Daniel Seita
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone (USC) is invited
Contact: CS Faculty Affairs
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
CA DREAMS - Technical Seminar Series
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Fri, Jun 20, 2025 @ 12:00 PM - 01:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Puneet Gupta, Professor, UCLA
Talk Title: Scale-out Chiplet Based Systems: Design, Architecture and Pathfinding
Series: CA DREAMS - Technical Seminar Series
Abstract: As conventional technology scaling becomes harder, 2.5D integration provides a viable pathway to building larger systems at lower cost. Waferscale chiplet-based systems, as much as 100X larger than largest modern SoCs pose new opportunities and challenges in their architecture and design. We describe a waferscale GPU concept and discuss our experience designing a 2000 chiplet waferscale processor system, pointing out key challenges and solutions. Next, we describe our ongoing work on developing a cross-stack pathfinding framework for large distributed 2.5D/3D systems, identifying areas where technology development would help design metrics substantially, especially for the important class of distributed machine learning training applications.
Biography: Puneet Gupta received the B.Tech. degree in electrical engineering from the Indian Institute of Technology Delhi, New Delhi, India, in 2000, and the Ph.D. degree from the University of California at San Diego, San Diego, CA, USA, in 2007. He is currently a Faculty Member with the Electrical and Computer Engineering Department, University of California at Los Angeles. He Co-Founded Blaze DFM Inc., Sunnyvale, CA, USA, in 2004 and served as its Product Architect until 2007. He has authored over 200 papers, 18 U.S. patents, a book and two book chapters in the areas of system-technology co-optimization as well as variability/reliability aware architectures. Dr. Gupta is an IEEE Fellow and was a recipient of the NSF CAREER Award, the ACM/SIGDA Outstanding New Faculty Award, SRC Inventor Recognition Award, and the IBM Faculty Award. He currently leads the system benchmarking thrust within SRC JUMP 2.0 CHIME packaging center.
Host: Dr. Steve Crago
More Info: https://www.isi.edu/events/5810/scale-out-chiplet-based-systems-design-architecture-and-pathfinding/
Webcast: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addonWebCast Link: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addon
Audiences: Everyone Is Invited
Contact: Amy Kasmir
Event Link: https://www.isi.edu/events/5810/scale-out-chiplet-based-systems-design-architecture-and-pathfinding/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Quantum/Physics Joint Seminar Series - Francesco Anna Mele, Friday, June 20th at 1:30pm in EEB 132 & Zoom
Fri, Jun 20, 2025 @ 01:30 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Francesco Anna Mele, Physics at the Scuola Normale Superiore Pisa, Italy
Talk Title: From Tomography of CV Systems to a New Measure of Non-Gaussianity: The Symplectic Rank
Series: Quantum/Physics Joint Seminar Series
Abstract: Quantum state tomography, aimed at deriving a classical description of an unknown state from measurement data, is a fundamental task in quantum physics. In parallel, non-Gaussianity serves as a crucial resource for quantum information processing in continuous-variable (CV) systems.In this work, we investigate the fundamental limits of quantum state tomography for CV systems, revealing a deep connection between the efficiency in tomography and the degree of non-Gaussianity. Specifically:
We first show that tomography of general non-Gaussian states is extremely inefficient;
In contrast, we demonstrate that tomography of Gaussian states is efficient. To accomplish this, we introduce new tools of independent interest: tight bounds on the trace distance between CV states in terms of the norm distance between their first moments and covariance matrices.
We then explore the intermediate regime, establishing that tomography becomes progressively harder as the level of non-Gaussianity increases.
The latter result naturally leads to the concept of symplectic rank: a novel non-Gaussianity monotone that satisfies remarkable operational and resource-theoretic properties. Mathematically, the symplectic rank of a pure state is the number of symplectic eigenvalues of the covariance matrix that are strictly larger than the ones of the vacuum. Importantly, the symplectic rank is non-increasing under post-selected Gaussian operations, leading to strictly stronger no-go theorems for Gaussian conversion than those previously known.
The talk will be based on: https://arxiv.org/pdf/2405.01431, https://arxiv.org/pdf/2411.02368, and https://arxiv.org/pdf/2504.19319 .
Biography: Francesco Anna Mele was born in Italy in 1997. He received the B.Sc. and M.Sc. degrees in physics from the University of Pisa, Italy, in 2021, and the Diploma degree in physics from Scuola Normale Superiore of Pisa, Italy, in 2021. He is currently pursuing a Ph.D. in Physics at the Scuola Normale Superiore of Pisa, Italy, under the supervision of Vittorio Giovannetti and Ludovico Lami. He is currently visiting the California Institute of Technology (Caltech) until August 15. His research interests include all aspects of quantum information and computation.
Host: Quntao Zhuang, Eli Levenson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo,k Todd Brun, Tony Levi, Stephan Haas
More Info: https://usc.zoom.us/j/91779790215?pwd=ZlygfD3dO1htFllfQ0n8HyIaLNnYjL.1
More Information: Francesco Mele -June 20, 2025.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/91779790215?pwd=ZlygfD3dO1htFllfQ0n8HyIaLNnYjL.1
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Robotics and Autonomous Systems Center (RASC) Seminar
Fri, Jun 20, 2025 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering, Thomas Lord Department of Computer Science, USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Prof. Dinesh Jayaraman, University of Pennsylvania
Talk Title: Engineering Better Robot Learners: Exploration and Exploitation
Abstract: Industry is placing big bets on "brute forcing" robotic control, but such approaches ignore the centrality of resource constraints in robotics on power, compute, time, data, etc. Towards building a true engineering discipline of robotics, my research group has been "exploiting and exploring" robot learning: exploiting to push the limits of what can be achieved with today's prevalent principles at various resource constraints, and "exploring" better design principles for efficient and minimalist robots in the future. As examples of “exploit”, we have trained quadruped robots to perform circus tricks on yoga balls and robot arms to perform household tasks in entirely unseen scenes with unseen objects. As examples of “explore”, we are studying the sensory requirements of robot learners: what sensors do they need and when do they need them during training and task execution? In this talk, I will highlight these examples and discuss some lessons we have learned in our research towards better-engineered robot learners.
Biography: Dinesh Jayaraman is an assistant professor at the University of Pennsylvania's CIS department and GRASP lab. He leads the Perception, Action, and Learning (Penn PAL) research group, which works at the intersections of computer vision, robotics, and machine learning. Dinesh received his PhD (2017) from UT Austin, before becoming a postdoctoral scholar at UC Berkeley (2017-19). Dinesh's research has received a Best Paper Award at CORL '22, a Best Paper Runner-Up Award at ICRA '18, a Best Application Paper Award at ACCV '16, the NSF CAREER award '23, an Amazon Research Award '21, and been covered in The Economist, TechCrunch, and several other press outlets. His webpage is at: https://www.seas.upenn.edu/~dineshj/
Host: Prof. Erdem Biyik
Webcast: https://usc.zoom.us/j/97616702619?pwd=aiV4aX7mgVCUO3qUVmJ5DIWipZBy12.1Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/97616702619?pwd=aiV4aX7mgVCUO3qUVmJ5DIWipZBy12.1
Audiences: Everyone Is Invited
Contact: ERDEM BIYIK
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Green Belt for Process Improvement
Tue, Jun 24, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Green Belt for Process Improvement
Wed, Jun 25, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Six Sigma Green Belt for Process Improvement
Thu, Jun 26, 2025 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Black Belt
Abstract: USC Viterbi School of Engineering's Six Sigma Black Belt program, offered in partnership with the Institute of Industrial and Systems Engineers, enables professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of our Six Sigma Black Belt course in order to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certification. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
Host: USC Viterbi Corporate and Professional Programs
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/
Audiences: Six Sigma Black Belt Students
Contact: VASE Executive Education
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Robotics and Autonomous Systems Center (RASC) Seminar
Thu, Jun 26, 2025 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering, Thomas Lord Department of Computer Science, USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Dr. Naman Shah, Brown University
Talk Title: Autonomously Learning World-Model Representations For Efficient Robot Planning
Abstract: In recent years, it has been clear that planning is an essential tool for robots to achieve complex goals. However, robots often heavily rely on humans to provide "world models" that enable long-horizon planning. It is not only expensive to create such world models as it requires human experts who understand the domains as well as limitations of the robot, but these human-generated world models are often biased by human intuition and kinematic constraints. In this talk, I will present my research focusing on autonomously learning plannable world models. The talk would involve discussing approaches on task and motion planning, neuro-symbolic abstractions for motion planning, and how we can learn world models for task and motion planning.
Biography: Naman is a Postdoctoral researcher in the Intelligent Robots Lab (IRL) with Prof. George Konidaris. He has completed his PhD from Arizona State University, supervised by Prof. Siddharth Srivastava. His research interest lies in investigating methods for autonomously inventing generalizable and plannable world models for robotics tasks. He has been an intern with Palo Alto Research Center, Amazon Robotics, and Toyota Research Institute. Naman has also achieved several graduate fellowships at ASU and a Best Demo Paper Award at AAMAS 2022.
Host: Prof. Erdem Biyik
Webcast: https://usc.zoom.us/j/93271412501?pwd=uYyZGnx1XgMS0i9JbEJpIx7Nz57Lbk.1More Information: Naman Shah's Visit - 6_26_25.pdf
Location: 248
WebCast Link: https://usc.zoom.us/j/93271412501?pwd=uYyZGnx1XgMS0i9JbEJpIx7Nz57Lbk.1
Audiences: Everyone Is Invited
Contact: ERDEM BIYIK
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
CA DREAMS - Technical Seminar Series
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Fri, Jun 27, 2025 @ 12:00 PM - 01:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Julia R Greer, Professor, Caltech
Talk Title: Intelligentsia of Nano-Architected Hierarchical Materials
Series: CA DREAMS - Technical Seminar Series
Abstract: Creation of reconfigurable and multi-functional materials can be achieved by incorporating architecture into material design. In our research, we design and fabricate three-dimensional (3D) nano-architected materials that can exhibit superior and often tunable mechanical, thermal, photonic, electrochemical, and biochemical pro¬¬¬per¬¬ties at ex¬tre¬me¬ly low mass densities, which renders them useful and enabling in tech¬no¬lo¬gi¬cal applications. Dominant properties of such meta-materials are driven by their multi-scale hierarchy: from characteristic material microstructure (atoms) to individual constituents (nanometers) to structural components (microns) to overall architectures (millimeters and above). Our research is focused on the fabrication, synthesis, and characterization of hierarchical materials using additive manufacturing (AM) techniques, as well as on investigating their mechanical, electrochemical, and chemo-mechanical properties as a function of architecture, constituent materials, and microstructural detail. AM represents a set of processes that fabricate complex 3D structures using a layer-by-layer approach, with some advanced methods attaining nanometer resolution and the creation of unique, multifunctional materials and shapes derived from a photoinitiation-based polymerization of custom-synthesized resins and thermal post-processing. A type of AM, vat polymerization, has allowed for using hydrogels as precursors to produce 3D nano- and micro-architected metals and metal oxides, and exploiting their nano-induced material and structural properties. We describe additive manufacturing via vat polymerization and function-containing chemical synthesis to create 3D nano- and micro-architected metals, ceramics, multifunctional metal oxides, and metal-containing polymer complexes with dynamic bonds, as well as demonstrate their potential in some biomedical, protective, and sensing applications. I will describe how the choice of architecture and material can elicit new microstructural orders and induce stimulus-responsive, reconfigurable, and multifunctional response.
Biography: Creation of reconfigurable and multi-functional materials can be achieved by incorporating architecture into material design. In our research, we design and fabricate three-dimensional (3D) nano-architected materials that can exhibit superior and often tunable mechanical, thermal, photonic, electrochemical, and biochemical pro¬¬¬per¬¬ties at ex¬tre¬me¬ly low mass densities, which renders them useful and enabling in tech¬no¬lo¬gi¬cal applications. Dominant properties of such meta-materials are driven by their multi-scale hierarchy: from characteristic material microstructure (atoms) to individual constituents (nanometers) to structural components (microns) to overall architectures (millimeters and above). Our research is focused on the fabrication, synthesis, and characterization of hierarchical materials using additive manufacturing (AM) techniques, as well as on investigating their mechanical, electrochemical, and chemo-mechanical properties as a function of architecture, constituent materials, and microstructural detail. AM represents a set of processes that fabricate complex 3D structures using a layer-by-layer approach, with some advanced methods attaining nanometer resolution and the creation of unique, multifunctional materials and shapes derived from a photoinitiation-based polymerization of custom-synthesized resins and thermal post-processing. A type of AM, vat polymerization, has allowed for using hydrogels as precursors to produce 3D nano- and micro-architected metals and metal oxides, and exploiting their nano-induced material and structural properties. We describe additive manufacturing via vat polymerization and function-containing chemical synthesis to create 3D nano- and micro-architected metals, ceramics, multifunctional metal oxides, and metal-containing polymer complexes with dynamic bonds, as well as demonstrate their potential in some biomedical, protective, and sensing applications. I will describe how the choice of architecture and material can elicit new microstructural orders and induce stimulus-responsive, reconfigurable, and multifunctional response.
Host: Dr. Steve Crago
More Info: https://www.isi.edu/events/5807/intelligentsia-of-nano-architected-hierarchical-materials/
Webcast: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addonWebCast Link: https://usc.zoom.us/j/97017422125?pwd=Dbrt8MNMrmBV3xalKQJcAiNsggFJjJ.1&from=addon
Audiences: Everyone Is Invited
Contact: Amy Kasmir
Event Link: https://www.isi.edu/events/5807/intelligentsia-of-nano-architected-hierarchical-materials/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
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