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Events for the 1st week of May
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PhD Thesis Defense - Ehsan Qasemi
Mon, May 01, 2023 @ 10:30 AM - 12:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Defense - Ehsan Qasemi
Title: Multi-Modal Preconditioned Inference of Commonsense Knowledge
Committee Members: Muhao Chen, Aiichiro Nakano, Daniel O Leary, Fred Morstatter, Luis Garcia
Abstract: Humans can seamlessly reason with circumstantial preconditions of commonsense knowledge. We understand that a glass is used for drinking water, unless the glass is broken or the water is toxic. Despite state-of-the-art (SOTA) models impressive performance in inferring commonsense knowledge, it is unclear whether they understand the circumstantial preconditions. In this dissertation, I initially propose a novel challenge of reasoning with preconditions attributed to commonsense knowledge, design three tasks based on the challenge in text-only setup, and show there is a significant gap between SOTA language models performance and humans on our tasks. I then use weak supervision in a combination of targeted fine-tuning strategies to improve the language models performance on the preconditioned inference task. Finally, I go beyond the text-only setup and investigate the problem of preconditioned inference in a multi-modal setup when the model is challenged to infer the preconditions from an image.
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/j/98769460750
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MoBI Seminar: Dr Daniel Toker
Mon, May 01, 2023 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr Daniel Toker, Post-doctoral Fellow, Department of Psychology | Department of Neurology, University of California, Los Angeles
Talk Title: Criticality supports thalamocortical information processing during conscious states
Series: MoBI Seminar Series
Abstract: Mounting evidence suggests that during conscious states, neural electrodynamics are poised near a critical point or phase transition, and that this near-critical behavior supports the vast flow of information through thalamocortical networks during waking states. We identify a mathematically specific critical point near which waking neural electrodynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. Our evidence suggests that both the information-richness of cortical activity and the transfer of information between the cortex and thalamus is disrupted during diverse states of unconsciousness because of a transition of low-frequency thalamocortical electric oscillations away from this critical point. Conversely, we show that psychedelics may increase the information-richness of cortical activity and enhance communication between the thalamus and cortex by tuning low-frequency thalamocortical electrodynamics closer to this critical point.
Biography: Daniel Toker, PhD is a post-doctoral fellow in UCLA's Departments of Psychology and Neurology. He uses human and animal electrophysiology, mathematical modeling, and human brain organoids to study mechanisms underlying the loss and recovery of consciousness from anesthesia, generalized seizures, and coma.
Host: Dr Richard Leahy, leahy@sipi.usc.edu | Dr Karim Jerbi, karim.jerbi.udem@gmail.com
Webcast: https://usc.zoom.us/j/99475118848?pwd=ekJELzlxR1FPamwxRFp4cEgrNktRZz09More Information: MoBI Seminar Flyer - 05.01.2023 Daniel Toker.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
WebCast Link: https://usc.zoom.us/j/99475118848?pwd=ekJELzlxR1FPamwxRFp4cEgrNktRZz09
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Atoms Bits & Cells Finals
Mon, May 01, 2023 @ 02:00 PM - 04:00 PM
Viterbi Technology Innovation and Entrepreneurship
Receptions & Special Events
Atoms Bit & Cells is an undergrad competition and program to innovation and develop solutions in three areas:
Atoms â“ engineering hardware products
Bits â“ digital projects, such as mobile and web apps, including AI, ML applications
Cells â“ biomedical or bioengineering projects
Come and hear from the ABC teams as they present their technology and business. While the compete for a 1k prize towards their business.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Viterbi TIE
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PhD Dissertation Defense - Wenxuan Zhou
Mon, May 01, 2023 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Dissertation Defense - Wenxuan Zhou
Title: Robust and Generalizable Knowledge Acquisition from Text
Committee members: Muhao Chen (chair), Laurent Itti, Tianshun Sun, Robin Jia, Jonathan May
Abstract: With large amounts of digital text generated every day, it is important to acquire structured knowledge automatically from the text. In my thesis, I will present my work during my Ph.D. from two perspectives: (1) Improving the robustness of knowledge acquisition, especially against bias from training corpus; and (2) building data-efficient knowledge acquisition models in low-resource scenarios, which is important for tasks in high-stake domains. After these, I will discuss challenges and future directions for both (1) and (2).Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/j/6915039300
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DEI: AME Town Hall
Tue, May 02, 2023 @ 11:30 AM - 01:30 PM
Aerospace and Mechanical Engineering
Receptions & Special Events
The AME department wants to hear from YOU! Take a break from studying and join us for lunch to brainstorm and construct initiatives the AME department can support to promote student wellness. This is a community approach to student advocacy, which will facilitate open communication between students, staff, and faculty so that barriers to wellness can be identified and overcome.
Location: Seeley G. Mudd Building (SGM) - 123
Audiences: Department Only
Contact: Victoria Sevilla
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2023 Gordon Prize Special Lecture by Azad M. Madni
Tue, May 02, 2023 @ 04:00 PM - 05:00 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Azad M. Madni, University Professor of Astronautics, Aerospace and Mechanical Engineering, and Education
Talk Title: Road to TRASEE: A Transdisciplinary Systems Engineering Education Paradigm
Abstract:
Attend a special lecture on Dr. Azad M. Madni's 2023 Bernard M. Gordon Prize for Innovation in Engineering & Technology Education Award-winning research.
Online only. Please use event password 954094 for access to the live stream.
Biography:
Azad M. Madni is a member of the National Academy of Engineering and Professor of Astronautical Engineering. He is the holder of the Northrop Grumman Foundation Fred O'Green Chair in Engineering. he has a joint appointment in Astani Department of Civil and Environmental Engineering. He is the Executive Director of USC's Systems Architecting and Engineering Program in the Viterbi School of Engineering. He is also the Director of the Distributed Autonomy and Intelligent Systems Laboratory. He is the chair and co-founder of the IEEE SMC Society's Systems Science and Engineering award-winning Technical Committee for Model Based Systems Engineering. He has served as General Chair of the Conference on Systems Engineering Research since 2008. He is a Life Fellow/Fellow of AAAS, AIAA, IEEE, INCOSE, IETE, SDPS, and Washington Academy of Science. He has received prestigious awards and honors from nine different societies. His research has been sponsored by several government agencies including DARPA, NSF, DHS S&T, DoD-SERC, NASA, DTRA, OSD, MDA, ONR, AFOSR, AFRL, ARI, ARL, RDECOM, CECOM, ERDC, NAVAIR, NAVSEA, SPAWAR, MARCOR, DOE, and NIST. His research has also been sponsored by major aerospace and automotive companies including Boeing, General Motors, Raytheon, Northrop Grumman Corporation, SAIC, and Lockheed Martin ORINCON.
He is also the 2023 Bernard M. Gordon Prize for Innovation in Engineering & Technology Education Awardee.
Host: USC Viterbi School of Engineering
More Info: https://usc.zoom.us/j/93216913796?pwd=Tm1kVEptS1puUVdOSnZVSW56UCt6dz09
Location: Online Live Stream
Audiences: Everyone Is Invited
Contact: Sheriden Smith
Event Link: https://usc.zoom.us/j/93216913796?pwd=Tm1kVEptS1puUVdOSnZVSW56UCt6dz09
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PhD Thesis Defense - Yu-Chuan Yen
Wed, May 03, 2023 @ 08:30 AM - 10:30 AM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Defense - Yu-Chuan Yen
Title: Constructing an unambiguous user-and-machine-friendly, natural-language protocol specification system
Committee Members: Barath Raghavan, Ramesh Govindan, Murali Annavaram
Abstract: Protocol specification has existed for decades to deliver the design and implementation of numerous protocols.
As the guideline and foundation of diverse advanced systems, the methods to process and compose protocol specification have not changed much despite emerging advanced techniques.
The production of specifications remains labor-intensive and involves rigorous discussion to avoid miscommunication via natural language media. A key reason behind these facts is the existence of ambiguities in natural language articles. Ambiguities could represent an unreasonable sentence, a multiple-meaning sentence, or any under-specified behaviors. However, identification of ambiguities is challenging to be applied in domain specific context. In addition, lack of studies applying advanced natural language processing techniques limits our understanding and practices of improving specification production. Motivated by the above observations, this thesis makes the first steps in introducing and building a prototype system that is user-and-machine-friendly and able to process natural language protocol specification while guaranteeing the ambiguous level of the specification. The contributions are four-fold. Firstly, it applies advanced natural language processing techniques called Combinatory Categorial Grammar to analyze protocol specification texts and identifies ambiguous sentences that could result in buggy implementations. Secondly, it parses unambiguous English specification and generates corresponding executable protocol codes that can interoperate with well-known third party code. Thirdly, it defines protocol behaviors with a math definition and introduces unambiguous configurations. The specification configuration is easy for authors to design and easy to automatically generate corresponding English specification and executable code. Lastly, it categorizes a set of verification rules that are able to assist in filtering unreasonable configurations which could not be turned into pieces of English paragraphs or code blocks
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/j/2553045376
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Mangan Power Distribution Trojan Talk (Virtual)
Wed, May 03, 2023 @ 12:00 PM - 02:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Mangan Power Distribution Group
Date: Wednesday, May 3rd, 2023
Time: 12:00 p.m. - 2:00 p.m.
Location: Zoom RSVP HERE
HIRING NOW!
Mangan Power Distribution is a division of Mangan Inc., a nationally recognized Specialty Engineering, Automation, and Integration company. Our engineers excel in providing state-of-the-art electrical engineering services to clients throughout the United States.
Mangan PDG is looking to hire Graduate and Undergraduate Electrical Engineers with Power Systems background. Students on CPT/OPT are welcome.Location: Zoom, please see below for details on how to RSVP
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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PhD Thesis Proposal - Arvin Hekmati
Wed, May 03, 2023 @ 03:00 PM - 04:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Proposal - Arvin Hekmati
Title: Correlation-Aware Neural Networks for DDoS Attack Detection In IoT Systems
Committee Members: Bhaskar Krishnamachari (Chair), Cyrus Shahabi, Aiichiro Nakano, Mohammad Rostami, Cauligi Raghavendra
Abstract: We present a comprehensive study on applying machine learning to detect distributed Denial of service (DDoS) attacks using large-scale Internet of Things (IoT) systems. While prior works and existing DDoS attacks have largely focused on individual nodes transmitting packets at a high volume, we investigate more sophisticated futuristic attacks that use large numbers of IoT devices and camouflage their attack by having each node transmit at a volume typical of benign traffic. We introduce new correlation-aware architectures that take into account the correlation of traffic across IoT nodes, and we also compare the effectiveness of centralized and distributed detection models. We extensively analyze the proposed architectures by evaluating five different neural network models trained on a dataset derived from a 4060-node real-world IoT system. We observe that long short-term memory (LSTM) and a transformer-based model, in conjunction with the architectures that use correlation information of the IoT nodes, provide higher performance (in terms of F1 score and binary accuracy) than the other models and architectures, especially when the attacker camouflages itself by following benign traffic distribution on each transmitting node. For instance, by using the LSTM model, the distributed correlation-aware architecture gives 81 percent F1 score for the attacker that camouflages their attack with benign traffic as compared to 35 percent for the architecture that does not use correlation information. We also investigate the performance of heuristics for selecting a subset of nodes to share their data for correlation-aware architectures to meet resource constraints.
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/j/92583528716?pwd=S01uOUlYQXU5Z0xudXZXbzgwOE0wQT09
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PhD Thesis Defense - Leili Tavabi
Wed, May 03, 2023 @ 03:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Defense - Leili Tavabi
Committee Members: Mohammad Soleymani (Chair), Maja Mataric, Shrikanth Narayanan, Stefan Scherer
Title: Computational Modeling of Mental Health Therapy Sessions
Abstract: Despite the growing prevalence of mental health disorders, there is a large gap between the needs and available resources for diagnosis and treatment. The recent advancements in machine learning and deep learning provide an opportunity for developing AI assisted assessment of therapy sessions through automated behavior analysis. In this dissertation, I present multiple approaches for modeling and analyzing client therapist dialogue from real world Motivational Interviews toward efficient and systematic assessment of the sessions. I present models for automatic recognition of client intent on a local utterance level, and quality metrics like therapist empathy at the global session level. I further explore the association of in session behaviors with subsequent outcomes, and provide interpretable insights on psychologically relevant features associated with the modeled constructs
Audiences: Everyone Is Invited
Contact: Melissa Ochoa
Event Link: https://usc.zoom.us/j/96609451060?pwd=YnhUOWxjY0ZCaWFadkR4S2srNmZKZz09
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PHD Defense - Su Lei
Thu, May 04, 2023 @ 01:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
University Calendar
PHD Defense: Su Lei
Committee: Jonathan Gratch (Chair), Laurent Itti, Shri Narayanan
Abstract: In this dissertation, I innovate automatic facial analysis methods and use them to yield fundamental insights into the source and function of facial expressions in face-to-face social interaction. Facial expressions play an essential role in shaping human social behavior. The ability to accurately recognize, interpret and respond to emotional expressions is a hallmark of human social intelligence, and automating this ability is a key focus of computer science research. Machines that possess this skill could enhance the capabilities of human-machine interfaces, help diagnose social disorders, improve predictive models of human behavior, or serve as methodological tools in social science research. My dissertation focuses on this last application. Specifically, I examine two competing perspectives on the social meaning of facial expressions and show that automated methods can yield novel insights. In terms of technical innovation, I develop novel methods to interpret the meaning of facial expressions in terms of facial expressivity. Within computer science, facial expression analysis has been heavily influenced by the "basic emotion theory" which claims that expressions reflect the activation of a small number of discrete emotions (e.g., joy, hope, or fear). Thus, automatic emotion recognition methods seek to classify facial displays into these discrete categories to form insights into how an individual is interpreting a situation and what they will do next. However, more recent psychological findings have largely discredited this theory, highlighting that people show a wide range of idiosyncratic expressions in response to the same event. Motivated by this more recent research, I develop supervised machine learning models to automatically measure perceived expressivity from video data. In terms of theoretical innovation, I demonstrate how automatic expressivity recognition yields insight into alternative psychological theories on the nature of emotional expressions in social tasks by analyzing a large corpus of people engaged in the iterated prisoner's dilemma task. This is a canonical task used to test theories of social cognition and the function of facial expressions. First, I explore the appraisal perspective which claims that expressions reflect an individual's appraisal of how actions within a social task relate to their goals. I find that by analyzing facial expressions produced by participants, a computer can reliably predict how actions in the task impact participants' appraisals (specifically, we predict if the action was unexpected). Further, we show that automatic expressivity recognition dramatically improves the accuracy of these predictions over traditional emotion recognition. This lends support to the theory that expressions are, in a sense, directly caused by the social task. Second, I explore a contrasting perspective, interpersonal-dynamics theory, which argues that expressions are, in a sense, directly caused by the partner's expressions. This perspective emphasizes processes such as synchrony, mimicry, and contagion to explain moment-to-moment expressions. The appraisal perspective counters that any observed synchrony simply reflects a shared appraisal of social actions. I use automatic expressivity recognition to contrast these perspectives. Specifically, I analyze synchrony in two experimental conditions: a "still" condition where dyads see only a still image of their partner, and a "video" condition with real-time visual access to their partner's facial reactions. Using Dynamic Time Warping, I evaluate synchrony in both real and randomly paired dyads. Results reveal that synchrony exists even without visual cues, suggesting that shared appraisals contribute to synchrony, but that synchrony significantly increases when the partner is visible. This suggests that both perspectives must be integrated to best explain facial displays. In conclusion, both appraisal and interpersonal-dynamics perspectives reinforce the significance of emotional expressivity in interpreting facial displays and fostering social coordination in cooperative and competitive contexts. These insights offer valuable contributions to affective computing and the understanding of social interaction mechanisms. I also discuss potential limitations and future research directions for further exploring the complexities of social interactions.Location: https://usc.zoom.us/j/6448851979?pwd=TThsRC96Vk9KZnVLV0RIc1g5NGVuQT09
Audiences: Everyone Is Invited
Contact: Asiroh Cham
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Ming Hsieh ECE Seminar - Prof. Jacob Nagel, Technion
Fri, May 05, 2023 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jacob Nagel, Professor, Technion
Talk Title: Israel National Security Challenges and its Impact on Force Buildup and Technological Developments, focusing on the Technion Center for Science Security and Technology
Abstract: This seminar (60-90 minutes) will combine topics from my past positions at the Israeli Ministry of Defense and as Israeli National Security Advisor, and in my current position as head of the Technion Center for Science Security and Technology (CSST).
I am continually changing and updating my presentation according to worldwide events and technological advances. This presentation includes current and past events, as well as some anecdotes during some interesting meetings in Israel and around the world. As part of the seminar, I will show movies, photos, and technological demonstrations. Moreover, I will discuss the US-Israel MOU agreement (worth $38B, led and signed by me in 2016) and the special relationship between Israel and the US. Additionally, I will highlight my Technion Center activities and options for cooperation.
Biography: Professor Jacob Nagel (Israel Brigadier General, Res.) is a visiting professor in Aerospace Engineering at the Technion, Haifa, Israel. At the Technion, he is head of the CSST and the Peter Munk Research Institute. He is a senior fellow at the Foundation for Defense of Democracies. With 40 years of experience in Israeli government and intelligence, he teaches defense R&D strategy and policy as well as systems engineering. His areas of interest include: robotics and micro vehicles, aeronautics, rocket engine, space (e.g., satellites and payloads), cyber security, data science, image analysis, energy, and lasers. He served as the Head of the Israel National Security Council (NSC) and as Israel's National Security Advisor (Acting) to the Prime Minister. He also led the negotiations with the US on the most recent ten-year MOU and signed the agreement worth $38B. Prof. Nagel served in various technological positions at the Israel Ministry of Defense - Directorate of Defense R&D. These include the Scientific Deputy and the Acting Head of the military R&D, which is sometimes called "Israel's DARPA".
Host: Alan Willner
More Information: Nagel_Willner_Seminar_5.5.23.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Corine Wong
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, May 05, 2023 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Matthew Borzage, Ph.D., Assistant Professor, Department of Pediatrics, KSOM, USC
Talk Title: "Approaches for Neurovascular Magnetic Resonance Imaging-Going Beyond BOLD"
Abstract:
Biography:
Host: Brent Liu
More Info: zoom link available upon request
More Information: Flyer Matthew Borzage.pdf
Location: Corwin D. Denney Research Center (DRB) - 145
Audiences: Everyone Is Invited
Contact: Carla Stanard
Event Link: zoom link available upon request
