School of Computing Seminar Schedule

Seminars are typically held each Friday from 2:30 to 3:30 in McAdams 114. For an abstract and specific info about a seminar, please click the details link following the title.

Fall 2022

Aug26		David de Hilster LexisNexis Intelligent Programming Using NLP++ David de Hilster has over 35 years experience in practical applications in natural language processing and is co-author of the computer language NLP++. He has a bachelor of science in mathematics and a masters in Linguistics from the Ohio State University. David has worked in AI research groups including at Battelle Memorial Institute in Columbus Ohio, Tecsis in Rio de Janeiro Brazil, and McDonnel Douglas & TRW in California. David also has worked for several startups companies including Text Analysis International where he and Amnon Meyers developed NLP++ and VisialText. David currently works in the Supercomputing Development Group at LexisNexis in Boca Raton Florida where he is integrating NLP++ into HPPC Systems. David is also an accomplished artist, filmmaker, and author having recently published a book with his father proposing a new physical model for the entire universe.
Sep2		Bo Li Assistant Professor Department of Computer Science University of Illinois at Urbana–Champaign Trustworthy Machine Learning: Robustness, Privacy, Generalization, and their Interconnections Dr. Bo Li is an assistant professor in the Department of Computer Science at the University of Illinois at Urbana–Champaign. She is the recipient of the IJCAI Computers and Thought Award, Alfred P. Sloan Research Fellowship, NSF CAREER Award, MIT Technology Review TR-35 Award, Dean's Award for Excellence in Research, C.W. Gear Outstanding Junior Faculty Award, Intel Rising Star award, Symantec Research Labs Fellowship, Rising Star Award, Research Awards from Tech companies such as Amazon, Facebook, Intel, and IBM, and best paper awards at several top machine learning and security conferences. Her research focuses on both theoretical and practical aspects of trustworthy machine learning, security, machine learning, privacy, and game theory. She has designed several scalable frameworks for trustworthy machine learning and privacy-preserving data publishing systems. Her work has been featured by major publications and media outlets such as Nature, Wired, Fortune, and New York Times.
Sep9		Yuan Hong Associate Professor Department of Computer Science and Engineering University of Connecticut Trustworthy Video Understanding Deep Learning Systems [details] Yuan Hong is an Associate Professor in the Department of Computer Science and Engineering at the University of Connecticut. He received his Ph.D. degree from Rutgers University in 2014. His research interests primarily lie in the fields of differential privacy, secure multiparty computation, applied cryptography, trustworthy machine learning, and cyber-physical systems security and privacy. He is a recipient of the NSF CAREER award, Cisco Research Award, and Meta (Facebook) Research award finalist. His research contributions are published in prestigious security and data science venues such as IEEE S&P (Oakland), CCS, PETS, KDD, ECCV, AAMAS, EMNLP, ICDE, CIKM, EDBT, ICDCS, TDSC, TIFS, TOPS, and TKDE. He regularly serves as the TPC or senior PC member for relevant top conferences such as CCS, USENIX Security, PETS, NeurIPS, ICML, CVPR, ICCV, ECCV, KDD, and AAAI. His research is supported by numerous NSF and AFOSR awards.
Sep16		Stanley Bak Assistant Professor Department of Computer Science Stony Brook University Proving Safety of Closed-Loop Systems with Neural Network Controllers using Quantized State Backreachability [details] Stanley Bak is an assistant professor in the Department of Computer Science at Stony Brook University investigating the verification of autonomy, cyber-physical systems, and neural networks. He received a PhD from the University of Illinois at Urbana-Champaign (UIUC) in 2013, worked at the Air Force Research Laboratory (AFRL) before joining Stony Brook University in 2020. He received the AFOSR Young Investigator Research Program (YIP) award in 2020.
Sep23		Xenofon Koutsoukos Professor and Chair Department of Computer Science Vanderbilt University Resilient Distributed Consensus, Optimization, and Learning in Networked Cyber-Physical Systems Dr. Xenofon Koutsoukos is a Professor and the Chair of the Department of Computer Science and a Senior Research Scientist with the Institute for Software Integrated Systems (ISIS), Vanderbilt University, Nashville, TN, USA. He was a Member of Research Staff with the Xerox Palo Alto Research Center (PARC) (2000–2002). His research work is in the area of cyber-physical systems with emphasis on learning-enabled systems, formal methods, distributed algorithms, security and resilience, diagnosis and fault tolerance, and adaptive resource management. He has authored or coauthored more than 300 journal and conference papers and he is coinventor of four US patents. Prof. Koutsoukos was the recipient of the NSF Career Award in 2004, the Excellence in Teaching Award in 2009 from the Vanderbilt University School of Engineering, and the 2011 NASA Aeronautics Research Mission Directorate (ARMD) Associate Administrator (AA) Award in Technology and Innovation. He was named a Fellow of the IEEE for his contributions to the design of resilient cyber-physical systems.