Events for the 5th week of January
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Mon, Jan 27, 2020 @ 03:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mihai Udrescu, Department of Computer & Information Technology at the Politehnica University of Timisoara (UPT), Romania
Talk Title: From Quantum Computing to Complex Networks: Addressing Tough Questions in Biological and Social Systems
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: There is a fundamental difference between a technological and a natural system. While the former is the product of an intelligent designer, the latter is the result of an emerging process where randomness, volatility, and environment aggression play an important role. This talk will approach several hard problems in natural systems with computer-based complex network analysis, from drug repurposing and patient phenotype identification to specific patterns of opinion spreading in social networks. The talk will also cast light on the presenter's academic journey, from quantum computing to network science.
Biography: Mihai Udrescu is a Professor with the Department of Computer and Information Technology at the Politehnica University of Timisoara (UPT), Romania, and a Fulbright Visiting Scholar at the Electrical and Computer Engineering Department, Carnegie Mellon University (September 2019 - February 2020). He received his Ph.D. in Computer Engineering from UPT in 2005. Mihai Udrescu's research is targeting the physics of computation and the design of emerging computer systems such as quantum circuits and bio-inspired hardware. Recently, he got involved in research projects that focus on network science, online social networks, and network medicine.
Host: Paul Bogdan, pbogdan@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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AI for Software and Software for AI
Fri, Jan 31, 2020 @ 10:00 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Lin Tan, Purdue University
Talk Title: AI for Software and Software for AI
Abstract: This talk will present research focuses in two directions: (1) using software testing approaches to improve the dependability of machine learning systems, and (2) leveraging machine learning and natural language processing techniques to improve software dependability. Machine learning software is widely used in domains including aircraft collision avoidance systems, Alzheimers disease diagnosis, and autonomous driving cars. Despite the requirement for high reliability, machine learning software is difficult to test and debug. This talk will describe CRADLE, a new approach that (1) performs cross-implementation inconsistency checking to detect bugs in deep learning software, and (2) analyzes anomaly propagation to localize faulty functions in deep learning software. On the other hand, machine learning and natural language processing techniques have unique advantages in completing and automating challenging software development tasks. This talk will present techniques that automatically analyze software text, such as code comments, API documentation, and processor specifications, to extract specifications, generate test cases, and detect software bugs. In addition, this talk will discuss how to build machine learning models to produce specifications and bug patterns automatically from existing bugs and their commit messages to find new bugs.
Biography: Lin Tan is an Associate Professor of Computer Science at Purdue University. She received her PhD from the University of Illinois, Urbana-Champaign. Her research interests include software dependability and software text analytics. Dr. Tan co-authored papers have received ACM SIGSOFT Distinguished Paper Awards at MSR in 2018 and FSE in 2016; and IEEE Micros Top Picks in 2006. Dr. Tan was a recipient of Canada Research Chair, an NSERC Discovery Accelerator Supplements Award, an Ontario Early Researcher Award, an Ontario Professional Engineers Award -” Engineering Medal for Young Engineer, two Google Faculty Research Awards, a Facebook research award, and an IBM CAS Research Project of the Year Award.
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 200131_Lin Tan_CENG.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Brienne Moore