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Events for March 18, 2019
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Meet USC: Admission Presentation, Campus Tour, and Engineering TalkMon, Mar 18, 2019
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.
Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.
Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!
RSVPLocation: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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CS Colloquium: Gang Wang (Virginia Tech) - Human Augmentation for Internet Security
Mon, Mar 18, 2019 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Gang Wang, Virginia Tech
Talk Title: Human Augmentation for Internet Security
Series: CS Colloquium
Abstract: Human factors are playing a critical role in the security of today's Internet systems. On one hand, human factors are constantly exploited by attackers to launch serious attacks, leading to massive data breaches and ransomware infections. On the other hand, human (expert) intelligence is instrumental in detecting and combating new threats (e.g., zero-days) that automated methods such as machine learning often fail to capture.
In this talk, I will describe our efforts to improve security through human augmentation. Human augmentation includes (1) reducing the security risks introduced by human factors, and (2) integrating human intelligence to build more robust security defenses. First, I will describe our progress to reduce the risk of human factors by detecting and mitigating flawed system designs that severely weaken user-level defenses. Using spear phishing as an example, I will illustrate how data analytics and active measurements can make a key difference in this process. Second, I will share our recent results on improving the trust and robustness of security systems by generating "human-interpretable" outputs. By building an "explanation system" for deep learning based security applications, we allow security analysts to diagnose classification errors and patch model weaknesses. Finally, I conclude by highlighting my future plans of using data-driven approaches to augmenting security defenses for both humans and algorithms.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Gang Wang is an Assistant Professor of Computer Science at Virginia Tech. He obtained his Ph.D. from UC Santa Barbara in 2016, and a B.E. from Tsinghua University in 2010. His research focuses on human (user) aspects of Internet security. His work takes a data-driven approach to addressing emerging security threats in massive communication systems (social networks, email services), crowdsourcing systems, mobile applications, and enterprise networks. He is a recipient of the NSF CAREER Award (2018), Google Faculty Research Award (2017), ACM CCS Outstanding Paper Award (2018), and SIGMETRICS Best Practical Paper Award (2013). His research has appeared in a diverse set of top-tier venues in Security, Measurement, Networking, and HCI. His projects have been covered by media outlets such as MIT Technology Review, The New York Times, Boston Globe, CNN, ACM TechNews, and New Scientist.
Host: Aleksandra Korolova
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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ECE Seminar: Communication Algorithms via Deep Learning
Mon, Mar 18, 2019 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hyeji Kim, Researcher/Samsung AI Research Cambridge, UK
Talk Title: Communication Algorithms via Deep Learning
Abstract: The design of codes for communicating reliably over a statistically well-defined channel is an important endeavor involving deep mathematical research and wide-ranging practical applications. In this talk, we demonstrate that the discovery of decoding and coding algorithms can be automated via deep learning. We first show that creatively designed and trained Recurrent Neural Network (RNN) architectures can decode well known sequential codes such as convolutional and turbo codes with close to optimal performance on the additive white Gaussian noise (AWGN) channel, which itself is achieved by the Viterbi and BCJR algorithms. We also demonstrate that the neural network based decoders are much more robust and adaptive to deviations from the AWGN setting compared to existing decoders. Next, we present the first family of codes obtained via deep learning which significantly outperforms state-of-the-art codes. By integrating information theoretic insights into our design of recurrent-neural-network based encoders and decoders, we are able to construct the first set of practical codes for the Gaussian noise channel with feedback. Up until now, feedback has been known to theoretically improve the reliability of communication, but no practical codes have been able to do so.
Biography: Hyeji Kim is a researcher at Samsung AI Research Cambridge in the United Kingdom. Before she joined Samsung AI Research, she worked as a postdoctoral research associate at the University of Illinois at Urbana-Champaign. She received her Ph.D. and M.S. degrees in Electrical Engineering from Stanford University in 2016 and 2013, respectively, and her B.S. degree with honors in Electrical Engineering from KAIST in 2011. Her research interests include information theory, machine learning, and the interplay between the two areas. She is a recipient of the Stanford Graduate Fellowship and participant of the Rising Stars in EECS Workshop in 2015.
Host: Professor Salman Avestimehr, avestime@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Mar 18, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Margareta Stefanovic, University of Denver
Talk Title: Robust stabilization with guaranteed performance in heterogeneous multi-agent systems with nonlinear uncertain couplings
Abstract: Systems of physically interconnected multiple agents cooperating toward a common goal have received considerable attention lately, with applications in large-scale and cyber-physical systems. Distributed consensus ideas have been recognized as a more attractive approach compared to the centralized and decentralized ones. In this talk I will present recent results on stabilization, decoupling, and cooperative tracking in multi-agent systems subject to various types of challenges, such as mixed order linear dynamics, mixed matched/unmatched state-coupled nonlinear uncertainties in the agents dynamics. A unifying, easy-to-implement framework is developed using graph theory and optimal control formulation, to provide stability and guaranteed cost of the distributed communication topologies.
This is a joint work with the former PhD student and current postdoctoral DU research associate, Dr. Vahid Rezaei.
Biography: Margareta Stefanovic received a Ph.D. degree in Electrical Engineering (Control Systems) from the University of Southern California and is currently an Associate Professor of Electrical Engineering at the University of Denver. Her main research interests are in the areas of data-driven robust adaptive control, and distributed control of multi-agent systems. She serves as an Editor-at-Large for Journal of Intelligent and Robotic Systems and as an Associate Editor of ISA Transactions. Prof. Stefanovic is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
Host: Prof. Michael Safonov, msafonov@usc.edu
More Info: http://csc.usc.edu/seminars/2019Spring/stefanovic.html
More Information: 190318 Margareta Stefanovic CSCUSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Spring/stefanovic.html
