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Events for October 31, 2018
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Meet USC: Admission Presentation, Campus Tour, and Engineering TalkWed, Oct 31, 2018
Viterbi School of Engineering Undergraduate Admission
University Calendar
This half day program is designed for prospective freshmen (HS seniors 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: Rebecca Kinnon
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Resilient Distributed Inference in Cyber-Physical Systems
Wed, Oct 31, 2018 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Soummya Kar, Carnegie Mellon University
Talk Title: Resilient Distributed Inference in Cyber-Physical Systems
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: In applications such as large-scale cyber-physical systems (CPS) and Internet-of-Things (IoT), as the number of devices or agents continues to grow, the integrity and trustworthiness of data generated by these devices becomes a pressing issue of paramount importance. An adversary may hijack individual devices or the communication channel between devices to maliciously alter data streams. In numerous IoT applications, we deploy physical devices throughout an environment, and we are interested in using the stream of sensor measurements to make inferences about the environmental state. Due to the large-scale and distributed nature of devices and data it might be infeasible to carry out computation and decision-making in a classical centralized fashion as well as to prevent attacks and intrusions on all data sources. As a result, reactive countermeasures, such as intrusion detection schemes and resilient inference algorithms become a vital component of security in distributed IoT-type setups.
As an alternative to traditional fusion-center based cloud setups, in this talk we focus on fog-type architectures in which devices themselves perform the necessary computations using local data and peer-to-peer information exchange with neighboring devices to make inferences about an environment. In the first part of the talk, we review distributed inference approaches and algorithms based on the consensus+innovations paradigm. We discuss performance metrics such as rates of convergence, communication complexity, and optimality. The second part of the talk focuses on recent work on secure and resilient variants of these algorithms in adversarial environments. Specifically, focusing on the case of data integrity attacks on the device network, we characterize fundamental trade-offs between resilience, quantified in terms of achievable inference performance and ability to detect intrusions and threats, and model properties such as observability and connectivity of the inter-device communication network.
Biography: Soummya Kar received a B.Tech. in electronics and electrical communication engineering from the Indian Institute of Technology, Kharagpur, India, in May 2005 and a Ph.D. in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, PA, in 2010. From June 2010 to May 2011, he was with the Electrical Engineering Department, Princeton University, Princeton, NJ, USA, as a Postdoctoral Research Associate. He is currently an Associate Professor of Electrical and Computer Engineering at Carnegie Mellon University, Pittsburgh, PA, USA. His research interests include decision-making in large-scale networked systems, stochastic systems, multi-agent systems and data science, with applications to cyber-physical systems and smart energy systems. Recent recognition of his work includes the 2016 O. Hugo Schuck Best Paper Award from the American Automatic Control Council and a 2016 Dean's Early Career Fellowship from CIT, Carnegie Mellon.
Host: Professor Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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CS Tech Talk: AI for Content Creation and Interaction
Wed, Oct 31, 2018 @ 04:00 PM - 06:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Lei Li & Dr. Jianchao Yang, ByteDance AI Lab
Talk Title: AI for Content Creation and Interaction
Abstract: In the mobile era, we are being presented an exciting opportunity to shape the way people acquire and consume information. In this talk, we will reveal the roles of AI technologies in the information consumption platforms. We will share several recent work at ByteDance AI Lab towards more efficient creation of and interaction with content. We will introduce a robot writer, Xiaomingbot, which has produced more than 60k articles since August 2016, some of them in multiple languages including English, Chinese and Portuguese. It relies on state-of-the-art representation learning for sentences and generative models from data, text, and images. We will also introduce our latest research in visual understanding of objects and scene in short videos, and how these technologies assist authors to create better content. The talk will be accompanied with interactive demos of these technologies in Tiktok(Douyin), Vigo(Huoshan), and Toutiao apps.
Biography: Dr. Lei Li is Director of ByteDance AI Lab. Lei received his B.S. in Computer Science and Engineering from Shanghai Jiao Tong University (ACM class) and Ph.D. in Computer Science from Carnegie Mellon University, respectively. His dissertation work on fast algorithms for mining co-evolving time series was awarded ACM KDD best dissertation (runner up). His recent work on AI writing received 2nd-class award of WU Wenjun AI prize of China. Before Toutiao, he worked at Baidu's Institute of Deep Learning in Silicon Valley as a Principal Research Scientist. Before that, he was working in EECS department of UC Berkeley as a Post-Doctoral Researcher. He has served in the Program Committee for ICML 2014, ECML/PKDD 2014/2015, SDM 2013/2014, IJCAI 2011/2013/2016, KDD 2015/2016, 2017 KDD Cup co-Chair, KDD 2018 hands-on tutorial co-chair, and as a lecturer in 2014 summer school on Probabilistic Programming for Advancing Machine Learning. He has published over 40 technical papers and holds 3 US patents.
Dr. Jianchao Yang is Director of ByteDance AI Lab US. Before joining ByteDance, Jianchao was a manager and principal research scientist at Snap, where he led the computer vision area. He obtained his Ph.D. degree under supervision of Prof. Thomas Huang from University of Illinois at Urbana-Champaign. He has published over 80 technical papers on top conferences and journals, which have attracted over 15k citations from the research community. He is the receipt of Best Student Paper Award in ICCV 2011. He and his collaborators are multiple winners of international competitions and challenges, including PASCAL VOC 2009, ImageNet 2014, WebVision 2017, and NTIRE Super-resolution Challenge 2018.
Host: Xiang Ren
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 116
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
