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SUNMONTUEWEDTHUFRISAT
Events for April 03, 2019
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Philadelphia, PA - Admitted Student Reception
Wed, Apr 03, 2019
Viterbi School of Engineering Undergraduate Admission
University Calendar
These Admitted Student Programs, hosted by the Undergraduate Admission Office, provide admitted students and their families an opportunity to meet admission counselors, representatives from academic departments, alumni, and you will have the opportunity to meet other admitted students from your local area. Viterbi and University Admission counselors will be there to answer any questions you might have, tell you more about campus life and your specific academic program, and welcome you to the Trojan Family. The program will last approximately two hours.
We love seeing our newly admitted students in person! if you live in or near a city we will be visiting, we encourage you to join us!
Once admitted, students can find the RSVP link in their USC Applicant Portal.Audiences: Admitted Students & Family Members
Contact: Viterbi Admission
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Spring 2019 ITP Open House
Wed, Apr 03, 2019 @ 09:30 AM - 11:30 AM
Technology & Applied Computing Program (TAC)
Workshops & Infosessions
All current and prospective students are invited to attend. Learn about our classes, ask questions about our minor programs, and meet our faculty.
We'll have snacks from Porto's Bakery to enjoy with coffee and tea, and advisers will be available to answer questions about course planning and how to declare minors! Stop by whenever you are able to. No RSVP required.More Information: Spring 2019 ITP Open Houses.pdf
Location: Waite Phillips Hall Of Education (WPH) - 205
Audiences: Everyone Is Invited
Contact: Tim Gotimer
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PhD Defense - Shahrzad Gholami
Wed, Apr 03, 2019 @ 10:30 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
Ph.D. Defense - Shahrzad Gholami
Wed, April 3, 2019
10:30 AM - 12:00 Noon
Location: EEB 132
Title:
Predicting and Planning against Real-world Adversaries: An End-to-end Pipeline to Combat Illegal Wildlife Poachers on a Global Scale
PhD Candidate: Shahrzad Gholami
Date, Time, and Location: Wednesday, April 3, 2019 at 10:30 am in EEB 132
Committee: Prof. Milind Tambe (chair), Prof. Aram Galstyan, and Prof. Emilio Ferrara, Prof. Richard John, Prof. Sze-Chuan Suen
Abstract:
Security is a global concern and a unifying theme in various security projects is strategic reasoning where the mathematical framework of machine learning and game theory can be integrated and applied. For example, in the environmental sustainability domain, the problem of protecting endangered wildlife from attacks (i.e., poachers' strikes) can be abstracted as a game between defender(s) and attacker(s). Applying previous research on security games to sustainability domains (denoted as Green Security Games) introduce several novel challenges that I address in my thesis to create computationally feasible and accurate algorithms in order to model complex adversarial behavior based on the real-world data and to generate optimal defender strategy. My thesis provides four main contributions to the emerging body of research in using machine learning and game theory framework for the fundamental challenges existing in the environmental sustainability domain, namely (i) novel spatio-temporal and uncertainty-aware machine learning models for complex adversarial behavior based on the imperfect real-world data, (ii) the first large-scale field test evaluation of the machine learning models in the adversarial settings concerning the environmental sustainability, (iii) a novel multi-expert online learning model for constrained patrol planning, and (iv) the first game theoretical model to generate optimal defender strategy against collusive adversaries. In regard to the first contribution, I developed bounded rationality models for adversaries based on the real-world data that account for the naturally occurring uncertainty in past attack evidence collected by defenders. To that end, I proposed two novel predictive behavioral models, which I improved progressively. The second major contribution of my thesis is a large-scale field test evaluation of the proposed adversarial behavior model beyond the laboratory. Particularly, my thesis is motivated by the challenges in wildlife poaching, where I directed the defenders (i.e., rangers) to the hotspots of adversaries that they would have missed. During these experiments across multiple vast national parks, several snares and snared animals were detected, and poachers were arrested, potentially more wildlife saved. The algorithm I proposed, that combines machine learning and game-theoretic patrol planning is planned to be deployed at 600 national parks around the world in the near future to combat poaching. The third contribution in my thesis introduces a novel multi-expert online learning model for constrained and randomized patrol planning, which benefits from several expert planners where insufficient or imperfect historical records of past attacks are available to learn adversarial behavior. The final contribution of my thesis is developing an optimal solution against collusive adversaries in security games assuming both rational and boundedly rational adversaries. I conducted human subject experiments on Amazon Mechanical Turk involving 700 human subjects using a web-based game that simulates collusive security games.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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CS Colloquium: Mukund Raghothaman (University of Pennsylvania) - Precise Program Reasoning using Probabilistic Methods
Wed, Apr 03, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Mukund Raghothaman, University of Pennsylvania
Talk Title: Precise Program Reasoning using Probabilistic Methods
Series: CS Colloquium
Abstract: The enormous rise in the scale, scope, and complexity of software projects has created a thriving marketplace for program analysis and verification tools. Despite routine adoption by industry, developing such tools remains challenging, and their designers must carefully balance tradeoffs between false alarms, missed bugs, and scalability to large codebases. Furthermore, when tools fail to verify some program property, they only provide coarse estimates of alarm relevance, potential severity, and of the likelihood of being a real bug, thereby limiting their usefulness in software projects with large teams.
I will present a framework that extends contemporary program reasoning systems with rich probabilistic models. These models emerge naturally from the program structure, and probabilistic inference refines the deductive process of the underlying system. In experiments with large programs, such probabilistic graphical representations of program structure enable an order-of-magnitude reduction in false alarm rates and invocations of expensive reasoning engines such as SMT solvers.
To the analysis user, these techniques offer a lens by which to focus their attention on the most important alarms and a uniform method for the tool to interactively generalize from human feedback. To the analysis designer, they offer novel opportunities to leverage data-driven approaches in analysis design. And to researchers, they offer new challenges while performing inference in models of unprecedented size. I will conclude by describing how these ideas promise to underpin the next generation of intelligent programming systems, with applications in diverse areas such as program synthesis, differentiable programming, and fault localization in complex systems.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Mukund Raghothaman is a postdoctoral researcher at the University of Pennsylvania. His research spans the areas of programming languages, software verification, and program synthesis, with the ultimate goal to help programmers create better software with less effort. He previously obtained a Ph.D. in 2017, also from the University of Pennsylvania, where he developed programming abstractions for data stream processing systems.
Host: Jyotirmoy Deshmukh
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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AME Department Laufer Lecture
Wed, Apr 03, 2019 @ 12:00 PM - 02:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Bala Balachandran, University of Maryland
Talk Title: Nonlinear Dynamics with Noise
Abstract: Nonlinearity influenced dynamics occurs in a variety of mechanical and structural systems. For operations of many of these systems, noise is often viewed as being undesirable. However, the interplay between noise and nonlinearity in a system can result in significant response changes that can be beneficial to a systems performance. In this spirit, the work carried out to further our understanding on the constructive use of noise in a nonlinear system to realize noise-enhanced responses, noise-enabled stabilization, and noise-assisted response steering will be discussed. Efforts undertaken with partial control will be discussed. Representative physical systems that will be considered include coupled oscillator arrays at the micro-scale and macro-scale, flexible rotor systems, and pendulum systems. The findings of these studies are expected to be relevant to a variety of different nonlinear, mechanical and structural systems. Some thoughts on future directions in the realm of applied nonlinear dynamics will be presented to close the talk.
Bala Balachandran received his B. Tech (Naval Architecture) from the Indian Institute of Technology, Madras, India, M.S. (Aerospace Engineering) from Virginia Tech, Blacksburg, VA and Ph.D. (Engineering Mechanics) from Virginia Tech. Currently, he is a Minta Martin Professor of Engineering at the University of Maryland, where he has been since 1993. His research interests include nonlinear phenomena, dynamics and vibrations, and control. The publications that he has authored/co-authored include over ninety journal publications, a Wiley textbook entitled Applied Nonlinear Dynamics: Analytical, Computational, and Experimental Methods (1995, 2006), a third edition of a textbook entitled Vibrations (2019) by Cambridge University Press, and a co-edited Springer book entitled Delay Differential Equations: Recent Advances and New Directions (2009). He holds four U.S. patents and one Japan patent, three related to fiber optic sensors and two related to atomic force microscopy. He is a Contributing Editor of the International Journal of Non-Linear Mechanics and the Editor of the ASME Journal of Computational and Nonlinear Dynamics. He is a Fellow of ASME and AIAA.
Wednesday, April 3, 2019
Reception at 12:00 NOON
Seminar Immediately Following
The Franklin Suite, Third Floor of Tutor Campus Center
Host: AME Department
Location: Franklin Suite, 3rd floor, Tutor Campus Center
Audiences: Everyone Is Invited
Contact: Tessa Yao
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Viterbi Keynote Lecture
Wed, Apr 03, 2019 @ 04:00 PM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Leonard Kleinrock, Distinguished Professor of Computer Science/University of California, Los Angeles
Talk Title: On Some of My Simple Results
Series: Viterbi Lecture
Abstract: A number of interesting problems that I have addressed over the years which
yielded surprisingly simple results will be presented. Many of these had intuitively
pleasing interpretations or especially simple proofs and/or insights.
Biography: Professor Leonard Kleinrock is Distinguished Professor of Computer Science at UCLA.
He is considered a father of the Internet, having developed the mathematical theory of
packet networks, the technology underpinning the Internet as an MIT graduate student
in 1962. His UCLA Host computer became the first node of the Arpanet, predecessor
of the Internet, in 1969 and it was from his lab that he directed the transmission of the
first Internet message in October, 1969. Kleinrock received the 2007 National Medal
of Science, the highest honor for achievement in science bestowed by the President of
the United States.
Leonard Kleinrock received his Ph.D. from MIT in 1963. He has served as Professor of
Computer Science at UCLA since then, and was department Chairman from 1991-1995.
He received a BEE degree from CCNY in 1957 (Evening Session) and an MS degree from
MIT in 1959. He has received eight honorary degrees, has published over 250 papers,
authored six books, and has supervised the research for 50 Ph.D. students.
Professor Kleinrock is a member of the National Academy of Engineering, the American
Academy of Arts and Sciences, is an IEEE fellow, an ACM fellow, an INFORMS fellow,
an IEC fellow, an inaugural member of the Internet Hall of Fame, a Guggenheim fellow,
and an Eminent member of Eta Kappa Nu. Among his many honors, he is the recipient
of the National Medal of Science, the Ericsson Prize, the NAE Draper Prize, the Marconi
Prize, the Dan David Prize, the Okawa Prize, the BBVA Frontiers of Knowledge Award,
the ORSA Lanchester Prize, the ACM SIGCOMM Award, the IEEE Leonard G. Abraham
Prize Paper Award, the IEEE Harry M. Goode Award and the IEEE Alexander Graham
Bell Medal.
Host: Richard Leahy, leahy@sipi.usc.edu
More Info: https://bluejeans.com/734846093
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
Event Link: https://bluejeans.com/734846093
