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SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for April
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CS Colloquium: Amir Houmansadr (UMass Amherst) - The Road Not Taken: Towards Proactive Research on Internet Censorship
Wed, Apr 02, 2025 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Amir Houmansadr, UMass Amherst
Talk Title: The Road Not Taken: Towards Proactive Research on Internet Censorship
Abstract: Internet censorship poses a major threat to free speech and open access to information worldwide. While numerous tools exist to bypass censorship, they often fail to provide censored users with effective and reliable solutions. A key reason for this inefficacy is the reactive nature of circumvention tool development—developers modify their tools in response to censorship tactics, allowing censors to maintain the upper hand in this ongoing arms race. In this talk, I will make the case for a proactive approach to censorship circumvention research and share insights from our ongoing efforts towards proactive circumvention.
As AI continues to transform Internet services, I argue that the future of Internet security is inextricably linked to AI. I will also outline my vision for safeguarding online freedom and security in the age of AI, exploring both its potential and the challenges it presents.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Amir Houmansadr is an Associate Professor of computer science at UMass Amherst. He received his Ph.D. from the University of Illinois at Urbana-Champaign, and was a postdoctoral researcher at the University of Texas at Austin. Amir is broadly interested in the security and privacy of networked/AI systems. To that end, he designs and deploys privacy-enhancing technologies, analyzes network protocols and services (e.g., messaging apps and machine learning APIs) for privacy leakage, and performs theoretical analysis to derive bounds on privacy (e.g., using game theory and information theory). Amir has received several awards including the 2013 IEEE S&P Best Practical Paper Award, a 2015 Google Faculty Research Award, a 2016 NSF CAREER Award, a 2022 DARPA Young Faculty Award (YFA), the 2023 Best Practical Paper Award from the FOCI Community, the first place at CSAW 2023 Applied Research Competition, a Distinguished Paper Award from ACM CCS 2023, a 2024 Applied Networking Research Prize (ANRP), and a 2024 DARPA Directors Award.
Host: Harsha V. Madhyastha
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. -
CS Colloquium: Xia (Ben) Hu (Rice University) - Efficient LLM Serving via Lossy Computation
Wed, Apr 09, 2025 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Xia (Ben) Hu, Rice University
Talk Title: Efficient LLM Serving via Lossy Computation
Series: Computer Science Colloquium
Abstract: Large language models (LLMs) have exhibited human-like conversational abilities. Yet, scaling LLMs to longer contexts, such as extracting information from lengthy articles, one of the most fundamental tasks in healthcare applications, poses significant challenges. The primary issues are their inability to handle contexts beyond pre-training lengths and system constraints that make deployment difficult, as memory requirements for inference increase with context length. The key idea to overcome these challenges is that LLMs are extremely robust to noise from lossy computation, such as low-precision computation. Following this insight, we will discuss recent advancements in serving LLMs at scale, particularly in handling longer contexts. To address the algorithmic challenge, I will share our recent work on extending LLM context length to at least 8× longer by coarsening the positional information of distant tokens. To address the system challenge, I will discuss our recent efforts in quantizing the intermediate states of past tokens to 2-bit numbers, leading to a 8x memory efficiency and 3.5x wall-clock time speedup without harming performance. Finally, I will highlight our latest projects applying LLMs in healthcare, particularly how we utilize retrieval techniques for long contexts to mitigate the hallucination problem in healthcare chatbots. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Dr. Xia “Ben” Hu is an Associate Professor at Rice University in the Department of Computer Science. Dr. Hu has published over 200 papers in several major academic venues, including NeurIPS, ICLR, ICML, KDD, IJCAI, etc. An open-source package developed by his group, namely AutoKeras, has become the most used automated deep learning system on GitHub (with over 9,000 stars and 1,000 forks). Additionally, his work on LLM efficiency, deep collaborative filtering, anomaly detection, knowledge graphs, and fast interpretation has been incorporated into production systems at Hugging Face, TensorFlow, Apple, Bing, and Meta, respectively. His papers have received several Best Paper (Candidate) awards from venues such as ICML, WWW, WSDM, ICDM, AMIA, and INFORMS. He is the recipient of the NSF CAREER Award and the ACM SIGKDD Rising Star Award. His work has been cited more than 30,000 times with an h-index of 76. He served as General Co-Chair for WSDM 2020 and ICHI 2023, as well as Program Co-Chair for AIHC 2024 and CHASE 2025.
Host: Yan Liu
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. -
Remarkable Trajectory Lecture Honoring Dr. Ellis Horowitz
Mon, Apr 21, 2025 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Ellis Horowitz, Professor of Computer Science and Electrical and Computer Engineering - USC
Talk Title: Turing Award Winners I Have Known and Their Impact on My Research
Abstract: I have been involved with computers for the past 62 years ever since I programmed an IBM 1620 while a junior in college. My journey has witnessed the development of the field of Computer Science and its recognition as a legitimate field of study, the growth of journals to publish the growing body of work in the field, the development of computer science departments and the awarding of degrees including Bachelors, Masters and Ph.D.s (including my own). In this talk I plan to highlight just some of the changes I have witnessed, by focusing on the Turing award winners I have known that have impacted my research. Though many more computer scientists have influenced my work, for this talk I will stick to the Turing award winners that I actually met personally and in some cases did joint work.
VIRTUAL AUDIENCE: If you are unable to join us in-person, you will be missed, but you can still view the lecture using the Zoom link below.
https://usc.zoom.us/j/94418192726?pwd=CgniyXcDAgc63uxdb70EmNmASGzf6Z.1
Meeting ID: 944 1819 2726
Passcode: 04212025
Biography: Dr. Ellis Horowitz is currently Professor of Computer Science and Electrical Engineering at the University of Southern California. He received his B.S. degree from Brooklyn College and his Ph.D. in computer science from the University of Wisconsin - Madison. He was on the faculty there and at Cornell University. He has also been a visiting Professor at M.I.T. and the Israel Institute of Technology (Technion).
Dr. Horowitz has held numerous academic administrative jobs including Associate Chairman of Computer Science at the University of Wisconsin. At U.S.C. he was chairman of the Computer Science Department from 1990 to 1999. After completing his term as Computer Science department chairman, Dr. Horowitz was appointed Director of Information Technology and Distance Education in USC's Viterbi School of Engineering. Part of his responsibilities included the Distance Education Network (DEN). As Director he oversaw an operation that offers more than 200 graduate engineering courses per year to more than 1,000 students. Originally courses were delivered by closed circuit satellite broadcast, but under Dr. Horowitz DEN converted their course delivery to Internet webcast.
Dr. Horowitz is the author of ten books and over eighty journal articles and refereed conference proceedings on computer science subjects ranging from data structures, algorithms, and software design to computer science education. He has been a principal investigator on research contracts from NSF, AFOSR, ONR, and DARPA. He is a past associate editor for the journals Communications of the ACM and Transactions on Mathematical Software. He was an IBM Scholar from 1989-1993. His Erdos number is 4.
Dr. Horowitz is an active consultant to the legal community, specializing in intellectual property issues. He has participated in several landmark cases including Yahoo v Google, RIAA v Kazaa, and RIAA v LimeWire. He was the founder and CEO of Quality Software Products, a California Corporation, from 1983 - 1993. The company designed and developed UNIX application software that was sold worldwide.
For more information on Dr. Horowitz please visit: https://ellishorowitz.com/
Host: Thomas Lord Department of Computer Science
More Info: https://forms.gle/jFxiDEvrwBovEHw27
Webcast: https://usc.zoom.us/j/94418192726?pwd=CgniyXcDAgc63uxdb70EmNmASGzf6Z.1Location: Ginsburg Hall (GCS) - Auditorium (LL1)
WebCast Link: https://usc.zoom.us/j/94418192726?pwd=CgniyXcDAgc63uxdb70EmNmASGzf6Z.1
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
Event Link: https://forms.gle/jFxiDEvrwBovEHw27
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
Tue, Apr 22, 2025 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Davide Scaramuzza, Professor of Robotics and Perception at the University of Zurich
Talk Title: Vision-based Agile Robot Navigation
Abstract: Autonomous drones play a crucial role in inspection, agriculture, logistics, and search-and-rescue missions and promise to increase productivity by a factor of 10. However, they still lag behind human pilots in speed, versatility, and robustness. What does it take to fly autonomous drones as agile as or even better than human pilots? Autonomous, agile navigation through unknown, GPS-denied environments poses several challenges for robotics research regarding perception, learning, planning, and control. In this talk, I will show how the combination of model-based and machine-learning methods, united with the power of new, low-latency sensors, such as event cameras, can allow drones to achieve unprecedented speed and robustness by relying solely on onboard computing. This can result in better productivity and safety of future autonomous aircraft.
Biography: Davide Scaramuzza is a Professor of Robotics and Perception at the University of Zurich and currently distinguished visiting scientist at NASA JPL. He did his Ph.D. at ETH Zurich, a postdoc at the University of Pennsylvania, and was a visiting professor at Stanford University. His research focuses on autonomous, agile microdrone navigation using standard and event-based cameras. He pioneered autonomous, vision-based navigation of drones, which inspired the navigation algorithm of the NASA Mars helicopter and many drone companies. He contributed significantly to visual-inertial state estimation, vision-based agile navigation of microdrones, and low-latency, robust perception with event cameras, which were transferred to many products, from drones to automobiles, cameras, AR/VR headsets, and mobile devices. In 2022, his team demonstrated that an AI-powered drone could outperform the world champions of drone racing, a result published in Nature and considered the first time an AI defeated a human in the physical world. He is a consultant for the United Nations on disaster response and disarmament. He has won many awards, including an IEEE Technical Field Award, the elevation to IEEE Fellow, the IEEE Robotics and Automation Society Early Career Award, a European Research Council Consolidator Grant, a Google Research Award, two NASA TechBrief Awards, and many paper awards (TRO, CVPR, RAL, IROS). In 2015, he co-founded Zurich-Eye, today Meta Zurich, which developed the world-leading virtual-reality headset Meta Quest. In 2020, he co-founded SUIND, which builds autonomous drones for precision agriculture. Many aspects of his research have been featured in the media, such as The New York Times, The Economist, and Forbes.
Homepage: https://rpg.ifi.uzh.ch/people_scaramuzza.html
Host: Executive Vice Dean of USC Viterbi School of Engineering, Director of the USC School of Advanced Computing, Gaurav Sukhatme
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Raymond Duran
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. -
CS Bekey Lecture feat. Dr. Huan Liu
Fri, Apr 25, 2025 @ 01:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Huan Liu , Regents Professor and Ira A. Fulton Professor of Computer Science and Engineering - Arizona State University
Talk Title: Ceaseless Inquiries: From AI to AI - What I Learned During My Years at USC under Dr. Bekey and What Came After
Abstract: My time at USC as a graduate student, with Dr. George Bekey as my advisor, had an indelible impact on my career. In this talk, I will illustrate how my research career was shaped by Dr. Bekey’s supervision and the ambience at USC at the time. My research journey in AI began in Robotics, and evolved into Knowledge-based Systems, Machine Learning, Data Mining, Social Computing, and Social Media Mining with posts in Australia, Singapore, and finally in the US, where I now teach at ASU. On the shoulders of giants, I learned valuable lessons on how to be an effective advisor and what the essence of research is. With the swift development of AI, we will have many more research opportunities to make novel contributions at accelerating speeds.
Please RSVP by: Monday, April 21, 2025 (5:00 p.m., PST)
This lecture satisfies requirements for CSCI 591: Research Colloquium.
This will be a hybrid lecture, Zoom details coming soon.
Biography: Dr. Huan Liu is a Regents Professor and Ira A. Fulton Professor of Computer Science and Engineering at Arizona State University. He is the recipient of the ACM SIGKDD 2022 Innovation Award for his outstanding contributions to the foundation, principles, and applications of social media mining and feature selection for data Mining. He co-authored the textbook, Social Media Mining: An Introduction, by Cambridge University Press. He is a Fellow of AAAI, AAAS, ACM, and IEEE.
Host: Thomas Lord Department of Computer Science
More Info: https://forms.gle/phi3Gh2yogf9ABtX9
Webcast: TBDLocation: Ginsburg Hall (GCS) - Auditorium (LL1)
WebCast Link: TBD
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
Event Link: https://forms.gle/phi3Gh2yogf9ABtX9
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. -
CS Colloquium: Alessandro Vespignani (Northeastern University) - From Data to Decisions: Computational Approaches to Dynamics, Behavior, and Forecasting in Complex Systems
Mon, Apr 28, 2025 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Alessandro Vespignani, Northeastern University
Talk Title: From Data to Decisions: Computational Approaches to Dynamics, Behavior, and Forecasting in Complex Systems
Abstract: The behavior of complex socio-technical systems is shaped by dynamic interactions across multiple layers of data, infrastructure, and human behavior. Understanding and anticipating these dynamics is essential for improving resilience, governance, and societal well-being. In this talk, I will explore how advanced computational modeling—leveraging network science, dynamical systems, AI, and machine learning—can help decode, simulate, and forecast the behavior of large-scale interconnected systems. Starting from the study of contagion phenomena—biological, informational, and behavioral—I will highlight how data-driven modeling frameworks have advanced our ability to monitor and forecast collective dynamics in real time. I will then present applications in public health and infectious disease management, where such models have informed epidemic preparedness, intervention design, and decision-making. Moving beyond contagion, I will discuss the broader implications of these tools in understanding adaptive behavior, feedback mechanisms, and systemic risk in socio-technical systems. By integrating empirical data with mechanistic and machine learning models, we can begin to build predictive frameworks that support decision-making across domains—from public health to digital ecosystems—where complexity is the rule, not the exception.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Alessandro Vespignani is the Sternberg Family Distinguished University Professor at Northeastern University, where he directs the Network Science Institute. His research lies at the intersection of computational modeling, data science, and complex systems, with a focus on contagion phenomena such as epidemics, information diffusion, and collective behavior. Vespignani builds large-scale predictive models that integrate real-world data using mechanistic simulations and machine learning to understand and forecast the dynamics of interconnected systems. He currently leads the CDC-funded EPISTORM center, a national effort to build the next generation of epidemic forecasting infrastructure, integrating diverse data streams such as wastewater surveillance, viral genomics, and high-resolution mobility data. Vespignani has authored over 200 scientific publications in leading journals, including Nature, Science, and PNAS. He is also the author of several books and monographs on complex systems and network science. He is a Fellow of the American Physical Society, the AAAS, and the Network Science Society.
Host: Cyrus Shahabi
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. -
USC CAIS Seminar
Tue, Apr 29, 2025 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science, USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Shubham Singh, University of Illinois Chicago
Talk Title: Fair Scheduling and Resource Allocation for Public Services
Abstract: The efficient and equitable distribution of public resources—such as health inspectors, mail delivery, and street sweeping—is crucial for local governments. However, disruptions to these allocation processes often reflect deep-seated historical and social inequalities, disproportionately affecting vulnerable populations. In this talk, we examine how single-objective predictive models can exacerbate societal disparities, how different choices of efficiency and fairness objectives lead to divergent outcomes under the same allocation policy, and the limitations of ranking methods in achieving an optimal utility-fairness tradeoff.
Biography: Shubham Singh is a Ph.D. candidate in Computer Science at the University of Illinois Chicago, focusing on computational methods for tackling socio-technical challenges. His research spans resource allocation, fair machine learning, and privacy and security. An active member of the FAccT and EAAMO communities, he has published at EAAMO, USENIX, and workshops at ICML and NeurIPS. He has been recognized through the Google CS Research Mentorship Program and serves as the Working Groups Co-lead for EAAMO Bridges (formerly MD4SG), reflecting his dedication to socially impactful research. More of his work can be found at: https://shubhams.github.io.
Host: Swabha Swayamdipta
More Info: https://cais.usc.edu/events/fair-scheduling-and-resource-allocation-for-public-services/
Webcast: https://usc.zoom.us/webinar/register/WN_wWfmuzu-QjyCq-gEzETU5ALocation: Olin Hall of Engineering (OHE) - 120
WebCast Link: https://usc.zoom.us/webinar/register/WN_wWfmuzu-QjyCq-gEzETU5A
Audiences: Everyone Is Invited
Contact: Hailey Nadel/USC CAIS
Event Link: https://cais.usc.edu/events/fair-scheduling-and-resource-allocation-for-public-services/
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.
