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  • PHD Defense - Weiwei Duan

    Fri, Aug 04, 2023 @ 01:00 PM - 02:30 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Dissertation Title:
    Efficient and Accurate Object Extraction from Scanned Maps by Leveraging External Data and Learning Representative Context

    Venue: Zoom meeting link: https://usc.zoom.us/j/2332986718

    Time: 1 pm - 2:30 pm (PT), August 4th

    Abstract:
    Scanned historical maps contain valuable information about environmental changes and human development over time. For instance, comparing historical waterline locations can reveal patterns of climate change. Extracting geographic objects in map images involves two main steps: 1. obtaining a substantial amount of labeled data to train extraction models, and 2. training extraction models to extract desired geographic objects. However, the extraction process has two difficulties. One difficulty is generating a large amount of labeled data with minimal human effort, as manual labeling is expensive and time-consuming. The other difficulty is ensuring that the extraction model learns representative and sufficient knowledge for the accurate extraction of geographic objects. The success of subsequent analyses, like calculating the shortest paths after extracting railroads, heavily depends on the accuracy of the extractions.

    To generate labeled data with minimal human efforts, this thesis presents semi- and fully automatic approaches to generate labeled desired geographic objects by leveraging external data. The semi-automatic approach requires one or a few manually labeled desired objects to collect all desired objects from candidates provided by the external data. In contrast, existing methods require more than a few manually labeled desired objects to achieve the same goal. On the other hand, the proposed automatic approach aims to label the desired objects in close proximity to external data. Using the location and shape information fully from the external data, the proposed automatic approach can accurately label the desired objects on the maps. On the contrary, existing methods that do not utilize shape information may lead to false labels. The novel approaches introduced in this thesis significantly reduce the need for manual labeling while ensuring accurate results.

    Extracting accurate geographic objects is the other difficulty due to the ambiguous appearances of objects and the overlapping objects in maps. The extraction model presented in this thesis captures cartographic symbols to differentiate desired objects from other objects with similar appearances. When the desired objects overlap with other objects on maps, the extracted results could be broken. The proposed extraction model captures sufficient spatial context to reduce broken extraction. For example, the proposed extractor learns the long and continuous structure of linear objects to reduce the gaps in the extracted lines. On the contrary, existing extractors lack the ability to learn sufficient spatial context, resulting in the broken extraction of linear objects. In summary, the proposed extractor learns representative cartographic symbols and sufficient spatial context to accurately extract desired objects.

    The results of the experiment demonstrate the superiority of both the labeling and extraction approaches compared to the existing methods. Accurately labeled data generated by the proposed methods significantly improve the quality of training data for extraction models. The extraction results from the proposed extractor have much less false extraction and better continuity than state-of-the-art baselines. The combination of precise labeling and accurate extraction allows us to extract geographic objects in scanned historical maps. Therefore, we can analyze and interpret historical map data effectively.

    Committee: Craig A. Knoblock Chair), Yao-Yi Chinag, Ram Nevatia, and John Wilson

    Location: https://usc.zoom.us/j/2332986718

    Audiences: Everyone Is Invited

    Contact: Asiroh Cham

    Event Link: https://usc.zoom.us/j/2332986718

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  • DEN@Viterbi - 'Limited Status: How to Get Started' Virtual Info Session

    Thu, Aug 10, 2023 @ 05:00 PM - 06:00 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi for our upcoming Limited Status: How to Get Started Virtual Information Session via WebEx to learn about the Limited Status enrollment option. The Limited Status enrollment option allows individuals with an undergraduate degree in engineering or related field, with a 3.0 GPA or above to take courses before applying for formal admission into a Viterbi graduate degree program.

    USC Viterbi representatives will provide a step-by-step guide for how to get started as a Limited Status student and enroll in courses online via DEN@Viterbi as early as the Fall 2023 semester.

    Register Now!

    WebCast Link: https://uscviterbi.webex.com/weblink/register/r22a9c300f29584e0e375002ae826fea9

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/r22a9c300f29584e0e375002ae826fea9

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  • PhD Thesis Defense - Aaron Ferber

    Fri, Aug 11, 2023 @ 09:30 AM - 11:30 AM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Aaron Ferber

    Committee Members: Bistra Dilkina (Chair), Yan Liu, and Phebe Vayanos

    Title: Artificial Decision Intelligence: Integrating Deep Learning and Combinatorial Optimization

    Abstract: Artificial Intelligence (AI) has the potential to impact many facets of our society largely due to its ability to quickly make high quality data driven decisions at scale. We consider Artificial Decision Intelligence (ADI) to be a paradigm for building artificial intelligence methods geared explicitly toward automatic decision making. In the rapidly evolving paradigms of machine learning (ML) and combinatorial optimization (CO), remarkable progress has been made in different directions, revolutionizing how we synthesize insights from data as well as how to best act on those insights. Machine learning, specifically deep learning, with its ability to learn intricate patterns from seemingly unstructured data, has seen profound success across diverse applications. Simultaneously, combinatorial optimization has made significant strides, efficiently performing industrial scale decision-making by searching for optimal solutions from combinatorially large and highly structured search spaces. This thesis explores different perspectives on the tight integration of these two paradigms: machine learning and combinatorial optimization, developing new tools that demonstrate the strengths of both approaches for solving complex tasks. Taking different perspectives on machine learning, combinatorial optimization, and how they can be combined in a cohesive and complementary manner, we propose new methodologies that enable end to end data driven decision making, deep predictive models that respect combinatorial constraints, methods that solve complex problems by learning to formulate simpler surrogate optimization problems, and optimization algorithms that learn from historical data to improve solver performance. The proposed methodologies contribute to the advancement of our capability in handling new and complex real world problems. Specifically, we demonstrate the impact of our methodologies in several domains, such as identifying wildlife trafficking routes, designing photonic devices, large scale recommendation systems, financial portfolio optimization, generating game levels, and smart energy grid scheduling. Thus, this thesis serves as a step forward in artificial decision intelligence by solving complex tasks and providing decision support tools that leverage machine learning and combinatorial optimization.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/my/aaron.ferber

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  • Repeating EventSix Sigma Green Belt for Process Improvement

    Tue, Aug 15, 2023 @ 09:00 AM - 05:00 PM

    Executive Education

    University Calendar


    USC Viterbi School of Engineering's Six Sigma Green Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results.

    Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Green Belt, you will be equipped to support and champion a Six Sigma implementation in your organization.

    To earn the USC Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's green belt exam.

    Location: Olin Hall of Engineering (OHE) -

    Audiences: Registered Participants

    View All Dates

    Contact: Karen Escobar

    Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/

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  • PhD Thesis Defense - Basileal Yoseph Imana

    Tue, Aug 15, 2023 @ 11:00 AM - 01:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Basileal Yoseph Imana

    Committee Members: John Heidemann (Chair), Aleksandra Korolova, Bistra Dilkina, Phebe Vayanos

    Title: Platform Supported And Privacy Preserving Auditing of Social Media Algorithms For Public Interest

    Abstract:
    Social media platforms are entering a new era of increasing scrutiny by public interest groups and regulators. One reason for the increased scrutiny is platform induced bias in how they deliver ads for life opportunities with legal protections against discrimination. Platforms use relevance estimator algorithms to optimize the delivery of ads. Such algorithms are proprietary and therefore opaque to outside evaluation, and early evidence suggests these algorithms may be biased or discriminatory. In response to such risks, the U.S. and the E.U. have proposed policies to allow researchers to audit platforms while protecting users privacy and platforms proprietary information. Currently, no technical solution exists for implementing such audits with rigorous privacy protections and without putting significant constraints on researchers. In this work, our thesis is that relevance estimator algorithms bias the delivery of opportunity ads, but new auditing methods can detect that bias while preserving privacy.

    We support our thesis statement through three studies. In the first study, we propose a black box method for measuring gender bias in the delivery of job ads with a novel control for differences in job qualification, as well as other confounding factors that influence ad delivery. Controlling for qualification is necessary since qualification is a legally acceptable factor to target ads with, and we must separate it from bias introduced by platforms algorithms. We apply our method to Meta and LinkedIn, and demonstrate that Metas relevance estimators result in discriminatory delivery of job ads by gender. In our second study, we design a black box methodology that is the first to propose a means to draw out potential racial bias in the delivery of education ads. Our method employs a pair of ads that are seemingly identical education opportunities but one is of inferior quality tied with a historical societal disparity that ad delivery algorithms may propagate. We also develop a method for auditing ad delivery using inferred race that handles uncertainty in inference. Using inferred race is useful to address the lack of access to race attributes that is a growing challenge for auditing racial bias in ad delivery. We evaluate Metas delivery of education ads with both known and inferred race. When race is known, we demonstrate Metas relevance estimators racially bias the delivery of education ads. We then show, when race is inferred, inference error makes the test for bias in ad delivery less sensitive to small amounts of bias. Going beyond the domain specific and black box methods we used in our first two studies, our final study proposes a novel platform supported framework to allow researchers to audit relevance estimators that is generalizable to studying various categories of ads, demographic attributes and target platforms. The framework allows auditors to get privileged query access to platforms relevance estimators to audit for bias in the algorithms while preserving the privacy interests of users and platforms. Overall, our first two studies show relevance estimator algorithms bias the delivery of job and education ads, and thus motivate making these algorithms the target of platform supported auditing in our third study. Our work demonstrates a platform supported means to audit these algorithms is the key to increasing public oversight over ad platforms while rigorously protecting privacy

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/93768511444?pwd=dDZTVjdyM0trSE1Qc2dqQ2hMcWNxUT09

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  • DEN@Viterbi - Online Graduate Engineering Virtual Information Session

    Tue, Aug 15, 2023 @ 05:00 PM - 06:00 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi School of Engineering for a virtual information session via WebEx, providing an introduction to DEN@Viterbi, our top-ranked online delivery system. Discover the 40+ graduate engineering and computer science programs available entirely online.

    Attendees will have the opportunity to connect directly with USC Viterbi representatives during the session to discuss the admission process, program details, and the benefits of online delivery.

    Register Today!


    WebCast Link: https://uscviterbi.webex.com/weblink/register/r8c2ba133bd76ff602b3631382b60a9b0

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/r8c2ba133bd76ff602b3631382b60a9b0

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  • Repeating EventSix Sigma Green Belt for Process Improvement

    Wed, Aug 16, 2023 @ 09:00 AM - 05:00 PM

    Executive Education

    University Calendar


    USC Viterbi School of Engineering's Six Sigma Green Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results.

    Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Green Belt, you will be equipped to support and champion a Six Sigma implementation in your organization.

    To earn the USC Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's green belt exam.

    Location: Olin Hall of Engineering (OHE) -

    Audiences: Registered Participants

    View All Dates

    Contact: Karen Escobar

    Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/

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  • PhD Thesis Defense - Guillermo Baltra

    Wed, Aug 16, 2023 @ 09:00 AM - 11:00 AM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Guillermo Baltra

    Committee Members: John Heidemann (Chair), Ramesh Govindan, Antonio Ortega


    Title: Improving network reliability using a formal definition of the Internet core

    Abstract: After 50 years, the Internet is still defined as a collection of interconnected networks. Yet seamless, universal connectivity is challenged in several ways. Political pressure threatens fragmentation due to de peering, architectural changes such as carrier grade NAT, the cloud makes connectivity indirect, firewalls impede connectivity, and operational problems and commercial disputes all challenge the idea of a single set of interconnected networks. We propose that a new, conceptual definition of the Internet core helps disambiguate questions in analysis of network reliability and address space usage.
    We prove this statement through three studies. First, we improve coverage of outage detection by dealing with sparse sections of the Internet, increasing from a nominal 67 percent responsive 24 blocks coverage to 96 percent of the responsive Internet. Second, we provide a new definition of the Internet core, and use it to resolve partial reachability ambiguities. We show that the Internet today has peninsulas of persistent, partial connectivity, and that some outages cause islands where the Internet at the site is up, but partitioned from the main Internet. Finally, we use our definition to identify ISP trends, with applications to policy and improving outage detection accuracy. We show how these studies together thoroughly prove our thesis statement. We provide a new conceptual definition of the Internet core in our second study about partial reachability. We use our definition in our first and second studies to disambiguate questions about network reliability and in our third study, to ISP address space usage dynamics.

    Location: Charles Lee Powell Hall (PHE) - 325

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/93940091161?pwd=S0tzNms2OW5EWTgzWFhtd3lSUlNudz09

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  • PhD Thesis Proposal - Nicolaas Weideman

    Wed, Aug 16, 2023 @ 10:00 AM - 11:30 AM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Proposal - Nicolaas Weideman

    Committee Members: Jelena Mirkovic (chair), Christophe Hauser, William Halfond, Mukund Raghothaman, Srivatsan Ravi, Peter Beerel

    Title: Improving the Security of Modern Software Systems through Binary Program Analysis with Semantic Understanding, Automated Vulnerability Discovery and Non-disruptive Patching


    Abstract: With the ever increasing reliance of the modern world on software systems, the frequency and impact of cyberattacks have greatly increased as well. Software must be analyzed thoroughly to evaluate its security, as vulnerabilities in software can have devastating consequences such as compromised privacy of users, shutdown of infrastructure and significant business losses, and even pose threat to human life. In this thesis we introduce our contributions toward addressing the challenges existing in software security evaluation. It is widely accepted that when evaluating the security of software, analyzing the source code is insufficient. We leverage and extend the field of binary program analysis in three key domains crucial for software security. These domains are semantic understanding, automated vulnerability discovery and nondisruptive patching. Jointly our contributions improve the field of binary program analysis in a threefold manner. We enable analysts to gain a deeper understanding of the program under analysis through extracting high level semantics. We design and implement a new approach for automated and precise vulnerability discovery. We automate vulnerability patching to secure software. Each of these directions independently pushes the boundaries of what is possible in defending modern software, leading to a more secure digital environment

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/91332871311?pwd=TmhuUyttWEJqMWQ5NTd1cGlpZVk1QT09

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  • Repeating EventSix Sigma Green Belt for Process Improvement

    Thu, Aug 17, 2023 @ 09:00 AM - 05:00 PM

    Executive Education

    University Calendar


    USC Viterbi School of Engineering's Six Sigma Green Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results.

    Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Green Belt, you will be equipped to support and champion a Six Sigma implementation in your organization.

    To earn the USC Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's green belt exam.

    Location: Olin Hall of Engineering (OHE) -

    Audiences: Registered Participants

    View All Dates

    Contact: Karen Escobar

    Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-green-belt-process-improvement/

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  • CS Colloquium: Jivko Sinapov - Multimodal Learning, Interaction, and Perceptions: The Path Towards Intelligent Collaborative Robots

    Thu, Aug 17, 2023 @ 02:00 PM - 03:30 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jivko Sinapov, Tufts University

    Talk Title: Multimodal Learning, Interaction, and Perceptions: The Path Towards Intelligent Collaborative Robots

    Abstract: Robots have the potential to transform the way we live and are increasingly deployed in applications ranging from assistive care settings to collaborative manufacturing. Enabling such robots to adapt in real time when facing novel situations, and problems, however, remains a challenge. In this talk, I will argue for a multimodal approach to learning, interaction, and perception for achieving robot autonomy in ever changing environments. First, I will describe how robots can transfer embodied knowledge across modalities e.g., touch, sound, and vision so that new robots, with different embodiments, sensors, and behaviors can still make use of the knowledge learned by other, more experienced, robots. Next, I will present results on how learned skills can be transferred from simple to complex environments as to afford the use of reinforcement learning methods that typically scale poorly in robotics domains. Finally, I will highlight multimodal approaches to interaction with people, including augmented reality and language, that help robots learn skills and concepts in order to be better partners and collaborators. We will conclude with a discussion on open questions and problems, along with our ongoing efforts to address them

    Biography: Jivko Sinapov is an assistant professor in Computer Science at Tufts University where he leads the Multimodal Learning, Interaction, and Perception MuLIP lab. He received his Ph.D. in computer science and human computer interaction at Iowa State University in 2013 and subsequently worked as a postdoctoral associate at UT Austin prior to joining Tufts in 2017. His research interests include cognitive and developmental robotics, creative problem solving, human robot interaction, and reinforcement learning. Jivko received the NSF CAREER award in 2023 and is also the recipient of the Tufts ROUTE award for undergraduate research advising in 2022

    Host: Jesse Thomason

    Location: Seaver Science Library (SSL) - 202

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

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  • Quantum Science & Technology Seminar - Zheshen Zhang - Friday, August 18th at 10am in EEB 248

    Fri, Aug 18, 2023 @ 10:00 AM - 11:30 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Zheshen Zhang, University of Michigan-Ann Arbor

    Talk Title: Entanglement-Enhanced Sensing and Data Processing

    Series: Quantum Science & Technology Seminar Series

    Abstract: The 20th century has witnessed the rise of quantum mechanics and its fueled scientific and technological revolution. The humankind is now on the verge of a second quantum revolution sparked by quantum information science and engineering (QISE). Entanglement as a quintessential quantum resource lies at the heart of QISE, giving rise to a plethora of quantum-enabled or enhanced capabilities that shift the landscape of communication, sensing, and computing. In this talk, I will present our recent experimental advances in entanglement-enhanced sensing and data processing. I will first describe entangled sensor networks for precise radiofrequency and optomechanical sensing beyond the standard quantum limit. Building on entangled sensors, I will introduce quantum-enhanced machine learning for data classification at a physical layer. Next, I will discuss a major endeavor to foster the transition from basic quantum research to near-term, widely impactful real-world quantum technologies: the construction of a quantum-network testbed as a distributed infrastructure to advance convergent QISE research and education.

    Biography: Dr. Zheshen Zhang is an Associate Professor of Electrical Engineering and Computer Science at University of Michigan-Ann Arbor. Prior to joining University of Michigan, Dr. Zhang was an Assistant Professor at University of Arizona from 2017 to 2022, a Research Scientist, and a Postdoctoral Associate both at MIT from 2012 to 2017. Dr. Zhang received his PhD degree in Electrical and Computer Engineering from Georgia Tech. Dr. Zhang's research encompasses a broad spectrum of quantum networks, quantum communications, quantum sensing, and quantum computing. His team harnesses unique quantum resources such as entanglement to develop quantum sensors surpassing the classical measurement limits, quantum communication systems with enhanced security and capacity, quantum networks for long-range entanglement distribution, and quantum processors capable of tackling problems intractable on classical computers. His work was recognized by an NSF CAREER Award in 2022. Dr. Zhang currently serves on the Editorial Board of Communications Physics of Nature Portfolio and Progress in Quantum Electronics of Elsevier.

    Host: Quntao Zhang, Wade Hsu, Mengjie Yu, Jonathan Habif & Eli Levenson-Falk

    More Information: Zheshen Zhang Seminar Flyer.pdf

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Contact: Marilyn Poplawski

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  • PhD Thesis Defense - Zunchen Huang

    Mon, Aug 21, 2023 @ 02:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Zunchen Huang

    Committee Members: Chao Wang (chair), Srivatsan Ravi, and Pierluigi Nuzzo

    Title: Constraint Based Analysis for Persistent Memory Programs

    Abstract: Emerging persistent memory technologies are beginning to bridge the gap between volatile memory and nonvolatile storage in computer systems, by allowing high speed memory access, byte addressability, and persistency at the same time. However, PM programming remains a challenging and error prone task due to reliance on ordinary developers to write correct and efficient PM software code. In this dissertation, I propose a framework to detect and repair PM bugs automatically using a set of new symbolic analysis techniques. Unlike existing techniques that rely on patterns and heuristics to detect and repair a small subset of PM bugs, the proposed techniques can handle a wide range of PM bugs. This is achieved by first encoding the program semantics, correctness properties, and PM requirements as a set of logical constraints, and then solving these constraints using off the shelf SMT solvers. By reasoning about these logical constraints symbolically, the proposed techniques can detect, diagnose, and repair PM bugs efficiently. Furthermore, I propose a new method to automatically infer PM requirements using a combination of static and dynamic analysis techniques. Finally, I demonstrate the feasibility of applying the proposed techniques to programs that rely on both PM and multi threading, by reasoning about persistency and concurrency simultaneously.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/4326990557

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  • PhD Thesis Defense - Umang Gupta

    Tue, Aug 22, 2023 @ 10:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Umang Gupta

    Committee Members: Greg Ver Steeg (Chair), Paul Thompson, Bistra Dilkina, Fred Morstatter

    Title: Controlling Information in Neural Networks for Fairness and Privacy

    Abstract: As machine learning becomes more prevalent in mission critical domains, the harms of unintended information captured by these models are becoming more apparent. These models can inadvertently introduce biases and memorize training data, leading to potential unfairness, inequitable outcomes, or risking privacy. These phenomena are especially alarming in applications where data privacy needs to be upheld, such as medical imaging, or where unfairness can lead to disparate outcomes, such as hiring decisions. This thesis examines ways to control and limit information in deep learning models, focusing on fairness and privacy. Specifically, we discuss ways to ensure fairness in decision making by learning fair data representations and preventing unfair language generation by correctly modulating information in neural networks. Concerning privacy, we demonstrate that releasing neuroimaging models may reveal private information about the individuals participating in the training set and discuss ways to mitigate these privacy leakages. Among these methods, differential private training is promising as it protects against all possible privacy attacks. However, differential private training can drastically hurt utility since the magnitude of noise in the outputs scales with the model parameters. To this end, we explore techniques to reduce effective model parameters during training.

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/7354464916

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  • Epstein Institute, ISE 651 Seminar Class

    Tue, Aug 22, 2023 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Yigal Arens, Research Professor, Daniel J. Epstein Dept. of Industrial & Systems Engineering

    Talk Title: Introduction/First Class

    Location: SOS Building, B2

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • test test test

    Tue, Aug 22, 2023 @ 06:00 PM - 07:00 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars


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    Location: Sign into EngageSC to View Location

    Audiences: Everyone Is Invited

    Contact: Kevin Giang

    Event Link: https://engage.usc.edu/viterbi/rsvp?id=390216

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  • Computer Science General Faculty Meeting

    Wed, Aug 23, 2023 @ 11:30 AM - 01:00 PM

    Thomas Lord Department of Computer Science

    Receptions & Special Events


    By-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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  • AME Seminar

    Wed, Aug 23, 2023 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Pradeep Sharma, Chair of Mechanical Engineering Department of Mechanical Engineering University of Houston

    Talk Title: Flexoelectricity and Electrets

    Abstract: The ability of certain materials to convert electrical stimuli into mechanical deformation, and vice versa, is a prized property. Not surprisingly, applications of such so-called piezoelectric materials are broad-”ranging from energy harvesting to self-powered sensors. In this presentation, I will highlight a relatively understudied electromechanical coupling called flexoelectricity that appears to have implications in topics ranging from biophysics to the design of next-generation soft multifunctional materials. Specifically, I will argue, through computational examples, the tantalizing possibility of creating apparently piezoelectric materials without piezoelectric materials-”e.g. graphene, emergence of giant piezoelectricity at the nanoscale, and (among others) the mechanisms underpinning magnetoreception in certain animals.

    Biography: Pradeep Sharma is the Hugh Roy and Lillie Cranz Cullen Distinguished University Professor and Chair of Mechanical Engineering at the University of Houston. He also has a joint appointment in the Department of Physics. He received his Ph.D. in mechanical engineering from the University of Maryland at College Park in the year 2000. Subsequent to his doctoral degree, he was employed at General Electric R & D for more than three years as a research scientist. He joined the department of mechanical engineering at University of Houston in January 2004. He is a member of the US National Academy of Engineering. His other honors and awards include the Young Investigators Award from Office of Naval Research, Thomas J.R. Hughes Young Investigator Award from the ASME, Texas Space Grants Consortium New Investigators Program Award, the Fulbright fellowship, the Melville medal, the James R. Rice medal from the Society of Engineering Science, ASME Charles R. Russ medal, the Guggenheim, and the University of Houston Research Excellence Award. He is a fellow of the ASME, the associate editor of the Journal of the Mechanics and Physics of Solids, chief-editor of the Journal of Applied Mechanics and serves on the editorial board of several other journals. He specializes in the broadly defined fields of continuum mechanics of solids and theoretical and computational materials science.



    Host: AME Department

    More Info: https://ame.usc.edu/seminars/

    Location: Seaver Science Library (SSL) - 202

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

    Event Link: https://ame.usc.edu/seminars/

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  • PhD Thesis Defense - Sarik Ghazarian

    Wed, Aug 23, 2023 @ 04:00 PM - 06:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Sarik Ghazarian

    Committee Members:Aram Galstyan, Nanyun Peng, Kallirroi Georgila, Gaurav Sukhatme, Morteza Dehghani

    Title: Automatic Evaluation of Open Domain Dialogue Systems

    Abstract: With the rapid development of open domain dialogue systems in recent years, it is imperative to have precise evaluation metrics that correctly assess the quality of these systems. To this end, many researchers resort primarily to human evaluation which is time consuming, expensive and it does not facilitate the model comparisons across research papers. Therefore, the existence of accurate automatic evaluation metrics that can accelerate the development cycle by assisting the process of architecture search and hyperparameter tuning is necessary. Reference based metrics such because BLEU or ROUGE fail to correlate well with human judgment in open domain settings as there can be potentially many plausible generations that do not overlap significantly with the limited set of given references. This failure leads the research towards learning based evaluation metrics that are more sophisticated and reliable.
    Automatic evaluation of open domain dialogue systems has a multifaceted nature with many fine grained quality aspects. This dissertation explores both turn level and conversation level facets of open-domain dialogue evaluation. We train models that automatically assess the relevance, engagement, coherence, and commonsense aspects of the responses generated by dialogue models. We formulate the evaluation as a classification task to identify the quality of the responses. To this end, we focus on training data and model architecture of these metrics as two main components that metrics quality strongly relies on them. We start with heuristic text level manipulations such as random swapping of utterances to create negative samples for training evaluation metrics. Then, we show that such manipulations are insufficient to appropriately reflect the issues that occur in interactions between advanced dialogue models and human. To tackle this issue, we move forward toward proposing advanced semantic level perturbations of human written responses to generate challenging negative responses that are more likely to be generated by state of the art dialogue models. Next, we complete our investigation on dialogue evaluation by concentrating on the model architecture of these metrics by incorporating knowledge from knowledge bases and leveraging prompt based generative models in a low resource setting. Finally, in addition to dialogue assessment, the main goal of automatic evaluation metrics, we leverage them as influential control factors to guide dialogue models and generate higher quality responses.

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/97105095544?pwd=Q05tWTdLSFdhNS9EY2JRMklWbHRkUT09

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  • PhD Thesis Defense - Jingbo Wang

    Thu, Aug 24, 2023 @ 10:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Jingbo Wang

    Committee Members: Prof. Chao Wang (chair), Prof. Nenad Medvidovic, Prof. Jyotirmoy Deshmukh, Prof. Mukund Raghothaman, and Prof. Pierluigi Nuzzo

    Title: Side channel Security Enabled by Program Analysis and Synthesis

    Abstract: The objective of my dissertation research is to develop rigorous methods and analysis tools for improving the security of software systems. I focus on a class of emerging security threats called side channel attacks. During a side channel attack, the adversary relies on exploiting statistical dependencies between the secret data e.g. passwords or encryption keys and seemingly unrelated non functional properties e.g. power consumption or execution time of the computer. In particular, power side channel leaks are caused by statistical dependencies instead of syntactic or semantic dependencies between sources and sinks. Thus, existing techniques that focus primarily on information flow security e.g. taint analysis would not work. To detect and then automatically remove these statistical dependencies in software code, I have developed a set of type inference rules to capture and quantify the leaks, and then a set of transformation based methods to mitigate the leaks. To adapt these type inference rules to constantly evolving program characteristics, I have also proposed a data driven method for learning provably sound side channel analysis rules from annotated programs. To ensure the correctness of the mitigation, I have developed new methods to help prove the equivalence of the original and mitigated programs. All of these methods aim to identify and then eliminate the side channel related statistical dependencies, which in turn leads to more secure software for critical applications.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

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  • Viterbi Mandarin Students Welcome Fall 2023

    Thu, Aug 24, 2023 @ 05:30 PM - 06:30 PM

    USC Viterbi School of Engineering

    Student Activity


    Announcing the USC Mandarin Discussion Forum for Viterbi Students!

    Join us for an engaging session where Mandarin-speaking students come together to mingle together. Hosted by the VASE office, USC CSSA, and USC CGSA, this exclusive event provides a platform for networking, support, and insightful discussions. Enhance your academic journey and reserve your spot now!

    Seize this golden opportunity to make your first semester a truly memorable one! We can't wait to welcome you to the USC Mandarin Discussion Forum. Don't miss this opportunity to connect with your Mandarin-speaking peers and make your first semester unforgettable!

    Location: Sign into EngageSC to View Location

    Audiences: Everyone Is Invited

    Contact: Experience USC Viterbi

    Event Link: https://engage.usc.edu/viterbi/rsvp?id=389590

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  • DEN@Viterbi: How to Apply Virtual Info Session

    Thu, Aug 24, 2023 @ 05:30 PM - 06:30 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi representatives for a step-by-step guide and tips for how to apply for formal admission into a Master's degree or Graduate Certificate program. The session is intended for individuals who wish to pursue a graduate degree program completely online via USC Viterbi's flexible online DEN@Viterbi delivery method.

    Attendees will have the opportunity to connect directly with USC Viterbi representatives and ask questions about the admission process throughout the session.

    Register Now!

    WebCast Link: https://uscviterbi.webex.com/weblink/register/r43071aaaa4efe0760b5558e0f148c1b1

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/r43071aaaa4efe0760b5558e0f148c1b1

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  • Alfred E.Mann Department of Biomedical Engineering - Seminar series

    Fri, Aug 25, 2023 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Ajit Yoganathan, Professor and the Wallace H. Coulter Distinguished Faculty Chair Wallace H. Coulter School of Biomedical Engineering Georgia Institute of Technology & Emory University

    Talk Title: Cardiovascular Engineering - A 'Personal' Journey from Bench to Bedside

    Abstract: Over the past few decades, significant contributions have been made by engineers to healthcare. The successful translation of fundamental engineering concepts has helped improve patient care and diagnosis. This impact has been particularly evident in the field of cardiovascular medicine where the roles of fluid and solid mechanics, and imaging are critical. In ~45 years of pioneering research, Professor Ajit Yoganathan's Cardiovascular Fluid Mechanics Laboratory at the Georgia Institute of Technology & Emory University, has been in the vanguard of this movement: advancing knowledge and technology in native and replacement heart valves, cardiovascular diagnostic techniques, and pediatric surgical/interventional planning. Using state-of-the-art fluid dynamic measurement techniques, Dr.Yoganathan and his group have developed methods to enable the optimization of replacement heart valve designs. Novel techniques in the assessment of native heart valve function have provided clinicians with improved tools to assess disease severity and helped identify effective treatment options. For the treatment of congenital heart defects, the development of novel computational modeling tools to simulate surgical procedures and their fluid dynamics outcomes have provided clinicians with new ways to plan for treatments for individual patients to increase the probability of success. Combined, these advances have helped bridge the lab bench to the patient's bedside/bassinet and integrate engineering science with the art of medicine.



    Biography: For over 45 years Dr. Ajit Yoganathan has been a pioneer in basic and translational cardiovascular research, especially experimental and computational fluid mechanics as it pertains to artificial heart valves, the whole heart, and congenital heart diseases. His work involves the use of optical techniques such as laser Doppler velocimetry, digital particle image velocimetry, and clinical tools such as cardiac ultrasound and magnetic resonance imaging to non-invasively study and quantify blood flow patterns and parameters in the cardiovascular system, both on the bench and in vivo. In his effort to take an interdisciplinary and translational approach to his research, Dr. Yoganathan has established collaborations with clinicians, scientists, and industry professionals world-wide and has played an important role in the development of U.S. and international standards for cardiovascular devices as Chair of the Cardiovascular Sub-Committee (SC2), International Standards Organization Technical Committee (TC 150) on Implants for Surgery since 2005. He has published over 40 book chapters and 450 peer reviewed articles in leading scientific journals; has given over 300 invited talks around the world; has more than 20 issued patents; and has mentored more than 50 doctoral students, 35 masters' students, and 40 post-doctoral trainees. Dr. Yoganathan has received a number of high honors and awards including membership to the prestigious National Academy of Engineering, the ASME H. R. Lissner Award in Bioengineering; the ASEE Theo Pilkington Award for Biomedical Engineering Education; the BMES Robert A. Pritzker Distinguished Lectureship Award; the AIMBE Professional Impact Award for Education; the Heart Valve Society's Inaugural HVS Lifetime Achievement Award; and AAMI Foundation's Laufman-Greatbatch Award. He is also a Founding Fellow of the American Institute of Medical and Biological Engineering (AIMBE), an Honorary Fellow of the American Association of Thoracic Surgery (AATS), and a Fellow of both the American Society of Mechanical Engineers (ASEE) and the Biomedical Engineering Society (BMES). It is noteworthy to mention that since 1975, all prosthetic heart valves implanted in the U.S. -“ more than two dozen valve designs - have been studied and evaluated in Dr. Yoganathan's Cardiovascular Fluid Mechanics lab.


    Host: Peter Yingxiao Wang- Chair of Alfred E. Mann Department of Biomedical Engineering

    More Info: zoom link available upon request

    Location: 136

    Audiences: Everyone Is Invited

    Contact: Carla Stanard

    Event Link: zoom link available upon request

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  • Where are the Jobs? Uncovering the Hidden Job Market

    Sat, Aug 26, 2023 @ 02:00 PM - 03:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions



    THIS EVENT WILL BE HOSTED HYBRID: IN-PERSON & ONLINE SIMULTANEOUSLY

    Increase your career and internship knowledge on networking by attending this professional development Q&A moderated by Viterbi Career Connections staff.



    To access the ZOOM link and for more information on this workshop, log into Viterbi Career Gateway>> Events>>Workshops: https://shibboleth-viterbi-usc-csm.symplicity.com/sso/

    For more information about all workshops, please visit viterbicareers.usc.edu/workshops.

    For In-Person: Attendance is limited to room capacity

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Repeating EventCommunications Hub: Writing and Speaking for PhD Students - Drop In Hours

    Mon, Aug 28, 2023 @ 10:00 AM - 01:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    Viterbi Ph.D. Students!
    Need help with academic and professional writing and speaking tasks? Viterbi faculty at the Hub provide one-on-one help with journal and conference articles, dissertations, fellowship applications, and career communications!
    Drop by RTH 222A on MWF 10am-1pm or make an online appointment via email at eishub@usc.edu.

    Location: Ronald Tutor Hall of Engineering (RTH) - 222A

    Audiences: Graduate

    View All Dates

    Contact: Helen Choi

    Event Link: https://sites.google.com/usc.edu/eishub/home

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  • Find Your Dream Job or Internship

    Tue, Aug 29, 2023 @ 12:00 PM - 01:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    THIS EVENT WILL BE HOSTED HYBRID: IN-PERSON & ONLINE SIMULTANEOUSLY

    Increase your knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    To access the ZOOM link and for more information on this workshop, log into Viterbi Career Gateway>> Events>>Workshops: https://shibboleth-viterbi-usc-csm.symplicity.com/sso/

    For more information about all workshops, please visit viterbicareers.usc.edu/workshops.

    For In-Person: Attendance is limited to room capacity

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: Everyone Is Invited

    Contact: RTH 218 Viterbi Career Connections

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  • Epstein Institute, ISE 651 Seminar Class

    Tue, Aug 29, 2023 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Joseph Nuamah , Assistant Professor, Department of Industrial Engineering & Management, Oklahoma State University

    Talk Title: Improving Human-System Interaction via Wearable Physiological Monitoring

    Host: Dr. Andrea Belz

    Location: SOS Building, B2

    Audiences: Everyone Is Invited

    Contact: Grace Owh

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  • Repeating EventCommunications Hub: Writing and Speaking for PhD Students - Drop In Hours

    Wed, Aug 30, 2023 @ 10:00 AM - 01:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    Viterbi Ph.D. Students!
    Need help with academic and professional writing and speaking tasks? Viterbi faculty at the Hub provide one-on-one help with journal and conference articles, dissertations, fellowship applications, and career communications!
    Drop by RTH 222A on MWF 10am-1pm or make an online appointment via email at eishub@usc.edu.

    Location: Ronald Tutor Hall of Engineering (RTH) - 222A

    Audiences: Graduate

    View All Dates

    Contact: Helen Choi

    Event Link: https://sites.google.com/usc.edu/eishub/home

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  • Viterbi How to Get Hired Series: Employer Workshops

    Wed, Aug 30, 2023 @ 11:00 AM - 03:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Mark your calendar to attend the Employer/Alumni-led professional development series, How To Get Hired (HTGH), to prepare for this fall recruiting season. This is your opportunity to connect with employers & alumni and learn what it takes to Get Hired directly from industry experts!

    HTGH workshops will take place Virtually or On-Campus.

    Workshops schedule:

    Time: 11:00 am-12:00 pm | Who Gets Hired: How to Make the Most of the Career Fair - Presented by Lockheed Martin
    Time: 12:00 pm-1:00 pm | Writing a Strong Resume - Presented by Northrop Grumman Corporation
    Time: 2:00 pm-3:00 pm | Building Professional Connections - Presented by Qvest.US

    RSVP through Viterbi Career Gateway >>Events>>Workshops

    Log into Viterbi Career Gateway: https://shibboleth-viterbi-usc-csm.symplicity.com/sso

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi Students

    Contact: RTH 218 Viterbi Career Connections

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  • DEN@Viterbi - Online Graduate Engineering Virtual Information Session

    Wed, Aug 30, 2023 @ 12:00 PM - 01:00 PM

    DEN@Viterbi, Viterbi School of Engineering Graduate Admission

    Workshops & Infosessions


    Join USC Viterbi School of Engineering for a virtual information session via WebEx, providing an introduction to DEN@Viterbi, our top-ranked online delivery system. Discover the 40+ graduate engineering and computer science programs available entirely online.

    Attendees will have the opportunity to connect directly with USC Viterbi representatives during the session to discuss the admission process, program details, and the benefits of online delivery.

    Register Today!


    WebCast Link: https://uscviterbi.webex.com/weblink/register/r61d366365bab39d33af05b79385e52f8

    Audiences: Everyone Is Invited

    Contact: Corporate & Professional Programs

    Event Link: https://uscviterbi.webex.com/weblink/register/r61d366365bab39d33af05b79385e52f8

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  • AME Seminar - Laufer Lecture

    Wed, Aug 30, 2023 @ 12:00 PM - 02:00 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Howard Stone, Department of Mechanical and Aerospace Engineering Princeton University

    Talk Title: Thin-Film Flows: From Similarity Solutions to New Insights in Molecular Biology

    Abstract: Fluid mechanics has a rich history, as of course does mechanics more generally. The ideas bridge science and engineering disciplines, even as they generate new fundamental research questions in fluid mechanics. In this talk I sketch some recent themes* from my research group, which bridge a wide range of length scales. First, I give a brief survey of some of the fluid mechanics problems that we have been investigating in recent years. Second, whereas traditional similarity solutions in course work and research typically involve nonlinear equations with two independent variables, I will illustrate an experimentally motivated similarity solution involving three independent variables, for which we construct an analytical solution that can be compared with experimental measurements. Third, I discuss the formation of the spindle in a dividing cell, which is a fundamental aspect of molecular biology. Experiments documenting a condensed protein phase on growing microtubules are reported, followed by the appearance of the Rayleigh-Plateau instability, which produces discrete droplets along a microtubule: the drops drive branching nucleation, which is an important mechanism for the developing spindle.
    *The research described was performed by many people in my research group, as well as some external collaborations.

    Biography: Howard Stone received the B.S. degree in Chemical Engineering from UC Davis in 1982 and the PhD in Chemical Engineering from Caltech in 1988. Following a postdoctoral fellowship at the University of Cambridge, in 1989 Howard joined the faculty of the (now) School of Engineering and Applied Sciences at Harvard University, where he eventually became the Vicky Joseph Professor of Engineering and Applied Mathematics. In July 2009 Howard moved to Princeton University where he is Donald R. Dixon 1969 and Elizabeth W. Dixon Professor in Mechanical and Aerospace Engineering.

    Professor Stone's research interests are in fluid dynamics, especially as they arise in research and applications at the interface of engineering, chemistry, physics, and biology. He is a Fellow of the American Physical Society (APS), and is past Chair of the Division of Fluid Dynamics of the APS. Currently he is on the editorial or advisory boards of Physical Review Fluids, Langmuir, and Soft Matter, and is co-editor of the Soft Matter Book Series. He is the first recipient of the G.K. Batchelor Prize in Fluid Dynamics (2008) and in 2016 recipient of the Fluid Dynamics Prize of the APS. He was elected to the National Academy of Engineering in 2009, the American Academy of Arts and Sciences in 2011, the National Academy of Sciences in 2014, the Royal Society (United Kingdom) as a Foreign Member in 2022, and the American Philosophical Society in 2022.

    Host: AME Department

    Location: Ronald Tutor Campus Center (TCC) - 350 (Franklin Suite)

    Audiences: Everyone Is Invited

    Contact: Tessa Yao

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  • PhD Thesis Proposal - Kushal Chawla

    Wed, Aug 30, 2023 @ 02:00 PM - 03:30 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Proposal - Kushal Chawla

    Committee Members: Gale Lucas (Chair), Jonathan Gratch, Jonathan May, Peter Kim, Maja Mataric

    Title: Computational Foundations for Mixed Motive Human Machine Dialogue

    Abstract: Success in a mixed motive interaction demands a balance between self serving and other serving behaviors. For instance, in a typical negotiation, a player must balance maximizing their own goals with the goals of their partner so as to come to an agreement. If the player asks for too much, this can push the partner to walk away without an agreement, hence, hurting the outcomes for all the parties involved. Such interactions are ubiquitous in everyday life, from deciding who performs household chores to customer support and high stake business deals. Consequently, AI tools capable of comprehending and participating in such mixed motive or other social influence interactions such as argumentation or therapy find broad applications in pedagogy and conversational AI.

    In this thesis, we present our foundational work for enabling mixed motive human machine dialogue. I will discuss our progress in three key areas. 1.The design of a novel task and dataset of grounded human human negotiations that has fueled our investigations into the impact of emotion expression and linguistic strategies, 2.Techniques for end to end dialogue systems for mixed motive interactions that learn to strike a balance between self and partner interests, and 3.Promoting a research community for dedicated efforts and discussion in this area

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/98290954709?pwd=NndMZ0VlbkJ4L25lVllLYTZZbWgvQT09

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  • Tinker the Robot - Job/Volunteer Info Session

    Wed, Aug 30, 2023 @ 06:00 PM - 07:00 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars


    Tinker the Robot's mission is to ignite and cultivate a passion for science and engineering among the next generation of scientists and engineers, specifically targeting kids K-8 (elementary/middle school). Tinker the Robot is currently looking for passionate and energetic individuals who are either engineers, engineers-in-training, makers/DIYers, or creators to join the team. The teaching sessions will primarily take place after school hours, starting from 3 pm and onwards, in the central/south central Los Angeles area. Please note, this is not an on-campus job opportunity. This is a job/volunteer opportunity with a community partner.

    Location: Online Event

    Audiences:

    Contact: Noe Mora

    Event Link: https://engage.usc.edu/viterbi/rsvp?id=389952

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  • PhD Dissertation Defense - Baskin B. Senbaslar

    Thu, Aug 31, 2023 @ 11:00 AM - 01:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Dissertation Defense - Baskin B. Senbaslar

    Committee Members: Gaurav S. Sukhatme (Chair), Sven Koenig, Satish Kumar Thittamaranahalli, Mihailo R. Jovanovic

    Title: Decentralized Real Time Trajectory Planning For Multi Robot Navigation in Cluttered Environments

    Abstract: Multi robot collision free and deadlock free navigation in cluttered environments with static and dynamic obstacles is a fundamental problem for many real world applications. Dynamic obstacles can additionally be interactive, i.e., changing their behaviors depending on the behaviors of other objects. We focus on decision making algorithms, with a particular emphasis on decentralized real time trajectory planning, to enable multi robot navigation in such environments.
    Practicality of the developed approaches is a central focus of ours, such that we design our systems and algorithms under assumptions that can be realized in the real world. Central concerns of our treatment are embracing on board compute, memory, and storage limitations of robotic systems, not relying on communication for safe operation, and explicitly account for communication imperfections, allowing navigation with imperfect a priori knowledge, embracing controller trajectory tracking errors and accounting for them, working with minimal sensing and estimation capabilities, and achieving highly reactive collision avoidance behavior.

    We introduce i. two decentralized real time multi robot trajectory planning algorithms to allow static obstacle, interactive dynamic obstacle, and teammate avoidance, ii. a constraint generation, overconstraining, and constraint discarding scheme to ensure inter robot collision avoidance under asynchronous planning that is inherent in decentralized systems, which we use within one of the proposed planners, and iii. a multi robot aware planning and control stack that allows collision free and deadlock free navigation in diverse types of environments, which combines three qualitatively different decision making approaches in a hierarchical manner.

    Location: Ronald Tutor Hall of Engineering (RTH) - 406

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

    Event Link: https://usc.zoom.us/j/94985203072?pwd=Y3h6OTJIY244RU1LYlhlR0JFa3dMZz09

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  • NL Seminar - Phishing Emails, Improvised Explosive Devices and Quantum: A Natural Language Understanding Perspective

    Thu, Aug 31, 2023 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Mitch Mithun, USC/ISI

    Talk Title: Phishing Emails, Improvised Explosive Devices and Quantum: A Natural Language Understanding Perspective

    Series: NL Seminar

    Abstract: REMINDER:

    Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you are highly encouraged to use your USC account to sign into Zoom.

    If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we will be aware of your attendance and let you in.

    In this talk Mitch will present 3 projects he worked on in the past year as part of his post doctoral tenure at ISI. In the first project Mitch will explore his findings and discoveries in an effort to answer the question Why do humans still fall prey sometimes to Phishing emails. Specifically, he will talk about the recent collaborative effort between experts in cyber security and natural language processing in exploring several subtle signals typically found in phishing emails which fool humans and or AI models. He will also present a comparative analysis of performance between humans and AI models on these signals, providing insight into the learning ability of both.

    In the second part, Mitch will present his work on how to explain and ground the predictions of Large Language Models from a schema curation perspective. Large Language Models are extremely adept at predicting a novel future event or missing events from a given set of events in a complex event. For example, if you ask Chat GPT to predict what are the key events that happen when an Improvised Explosive Device attack occurs, it will start with A person buys huge amount of Ammonium Nitrate as the first event. However how is this result explainable (and verifiable) by human intuition, given that the training data and or the training process of these LLMs are not publicly available?

    In the third part, Mitch will present his work on using Quantum Natural Language Processing QNLP in low resource settings. QNLP is a very nascent field which deals with using quantum computers to solve natural language processing problems. QNLP these models are different than neural network-based models, including GPT, because they incorporate compositionality aka grammar fundamentally, while neural network based models rely on learning context through a bag of words approach. He will show that this advantage of QNLP models is more pronounced in few shot learning settings where the data to be trained on is very low.


    Biography: Mitch was a post doctoral researcher at ISI where he was working with Marjorie Freedman and Ralph Weischedel in the networking and cyber security division. Mitch, graduated from his PhD from University of Arizona, along with his Masters in Computer Science, before joining ISI as a postdoc. Before that, he worked in the software industry for 10 plus years as a product manager in a research lab. He also has a master degree in Physics from Birla Institute of Technology and Science BITS, Pilani, India. His research interests include natural language processing, cyber security and quantum computation.

    Host: Jon May and Justin Cho

    More Info: https://nlg.isi.edu/nl-seminar/

    Webcast: https://youtu.be/xPrATNWf-8E

    Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689

    WebCast Link: https://youtu.be/xPrATNWf-8E

    Audiences: Everyone Is Invited

    Contact: Pete Zamar

    Event Link: https://nlg.isi.edu/nl-seminar/

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