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Events for March 29, 2022
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CS Colloquium: Lingjie Liu (Max Planck Institute for Informatics) - Neural Representation and Rendering of 3D Real-world Scenes
Tue, Mar 29, 2022 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Lingjie Liu , Max Planck Institute for Informatics
Talk Title: Neural Representation and Rendering of 3D Real-world Scenes
Series: CS Colloquium
Abstract: High-quality reconstruction and photo-realistic rendering of real-world scenes are two important tasks that have a wide range of applications in AR/VR, movie production, games, and robotics. These tasks are challenging because real-world scenes contain complex phenomena, such as occlusions, motions and interactions. Approaching these tasks using classical computer graphics techniques is a highly difficult and time-consuming process, which requires complicated capture procedures, manual intervention, and a sophisticated global illumination rendering process. In this talk, I will introduce our recent work that integrates deep learning techniques into the classical graphics pipeline for modelling humans and static scenes in an automatic way. Specifically, I will talk about creating photo-realistic animatable human characters from only RGB videos, high-quality reconstruction and fast novel view synthesis of general static scenes from RGB image inputs, and scene generation with a 3D generative model. Finally, I will discuss challenges and opportunities in this area for future work.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Lingjie Liu is Lise Meitner Postdoctoral Research Fellow working with Prof. Christian Theobalt in the Visual Computing and AI Department at the Max Planck Institute for Informatics. She received her Ph.D. degree at the University of Hong Kong in 2019. Before that, she got her B.Sc. degree in Computer Science at Huazhong University of Science and Technology in 2014. Her research interests include neural scene representations, neural rendering, human performance modeling and capture, and 3D reconstruction. Webpage: https://lingjie0206.github.io/.
Host: Jernej Barbic
Location: Olin Hall of Engineering (OHE) - 132
Audiences: By invitation only.
Contact: Assistant to CS chair
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Virtual First-Year Admission Information SessionTue, Mar 29, 2022 @ 11:00 AM - 12:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for high school students and their family members to learn more about the USC Viterbi undergraduate experience. Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life. Guests will be able to ask questions and engage in further discussion toward the end of the session.
Register Here!
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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CS Colloquium: Roopsha Samanta (Purdue University) - Semantics-Guided Inductive Program Synthesis
Tue, Mar 29, 2022 @ 01:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Roopsha Samanta, Purdue University
Talk Title: Semantics-Guided Inductive Program Synthesis
Series: CS Colloquium
Abstract: The dream of program synthesis seeks to automatically develop programs that conform to a user's intent. Classically, program synthesis has been framed as a problem of generation of correct-by-construction programs from complete, formal specifications of their expected behavior. An increasingly promising and more tractable paradigm of program synthesis, however, is inductive program synthesis. Broadly construed, inductive program synthesis can be framed as a problem of program discovery from partial specifications such as input-output examples, program traces, and natural language descriptions. While the last decade has witnessed several breakthroughs in improving the scalability and applicability of inductive program synthesis, the true potential of this synthesis paradigm remains to be unleashed.
In this talk, I will describe my group's ongoing endeavors to advance the frontiers of inductive program synthesis. Further, I will emphasize the need to tackle a fundamental, yet often neglected, challenge of inductive synthesis-”reliability. Because inductive synthesizers generalize from partial observations, they often suffer from overfitting, ambiguity, and brittleness-”the synthesized program may indeed conform to its partial specification, but it may not exhibit the intended behavior on all inputs. I will present my group's novel semantics-guided approach-”based on surprising notions of program semantics-”to improve the reliability of inductive program synthesis.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Roopsha Samanta is an Assistant Professor in the Department of Computer Science at Purdue University. Before joining Purdue in 2016, she completed her PhD at UT Austin in 2013, advised by E. Allen Emerson and Vijay K. Garg, and was a postdoctoral researcher at IST Austria from 2014-2016 with Thomas A. Henzinger. She is a recipient of 2019 NSF CAREER award and 2021 Amazon Research Award. Roopsha's research seeks to help programmers write programs that conform to their intent. She develop tools and techniques for algorithmic program verification, synthesis, and repair for a spectrum of application domains, correctness specifications, and programmer expertise. Her current research agenda is centered around two themes-”semantics-guided inductive program synthesis and repair and modular, bounded verification of unbounded distributed systems
Host: Mukund Raghothaman
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: By invitation only.
Contact: Assistant to CS chair
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CS Colloquium: Marco Pavone (Stanford University) - Towards safe, data-driven autonomy
Tue, Mar 29, 2022 @ 02:30 PM - 03:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Marco Pavone, Stanford University
Talk Title: Towards safe, data-driven autonomy
Series: Computer Science Colloquium
Abstract: *New time: 2:30 - 3:50 PM PT*
AI-powered autonomous vehicles that can learn, reason, and interact with people are no longer science fiction. Self-driving cars, unmanned aerial vehicles, and autonomous spacecraft, among others, are continually increasing in capability and seeing incremental deployment in more and more domains. However, fundamental research questions still need to be addressed in order to achieve full and widespread vehicle autonomy. In this talk, I will discuss our work on addressing key open problems in the field of vehicle autonomy, particularly in pursuit of safe, data-driven autonomy stacks. Specifically, I will discuss (1) robust human prediction models for both simulation and real-time decision making, (2) AI safety frameworks for autonomous systems, and (3) novel, highly integrated autonomy architectures that are amenable to end-to-end training while retaining a modular, interpretable structure. The discussion will be grounded in autonomous driving and aerospace robotics applications.
**Dr. Marco Pavone will give his talk in person at SGM 124 and we will also host the talk over Zoom.**
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_tR3q2DuTRwulhaNsexKXAw
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University, where he is the Director of the Autonomous Systems Laboratory and Co-Director of the Center for Automotive Research at Stanford. He is currently on a partial leave of absence at NVIDIA serving as Director of Autonomous Vehicle Research. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a number of awards, including a Presidential Early Career Award for Scientists and Engineers from President Barack Obama, an Office of Naval Research Young Investigator Award, a National Science Foundation Early Career (CAREER) Award, a NASA Early Career Faculty Award, and an Early-Career Spotlight Award from the Robotics Science and Systems Foundation. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40.
Host: Stefanos Nikolaidis
Webcast: https://usc.zoom.us/webinar/register/WN_tR3q2DuTRwulhaNsexKXAwLocation: Seeley G. Mudd Building (SGM) - 124
WebCast Link: https://usc.zoom.us/webinar/register/WN_tR3q2DuTRwulhaNsexKXAw
Audiences: Everyone Is Invited
Contact: Computer Science Department
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ISE 651 Epstein Seminar
Tue, Mar 29, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ignacio Grossmann, R.R. Dean University Professor, Dept. of Chemical Engineering, Carnegie Mellon
Talk Title: Global Optimization of Nonconvex Nonlinear Generalized Disjunctive Programs
Host: Dr. Phebe Vayanos
More Information: March 29, 2022.pdf
Location: Online/Zoom
Audiences: Everyone Is Invited
Contact: Grace Owh
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Mork Family Department Seminar - Julie Rorrer
Tue, Mar 29, 2022 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Julie Rorrer, Massachusetts Institute of Technology
Talk Title: From Trash to Treasure: Advancing the Catalytic Upcycling of Waste Plastics and Renewable Feedstocks
Host: Professor A.Hodge
Location: Social Sciences Building (SOS) - B46
Audiences: Everyone Is Invited
Contact: Heather Alexander
