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Mon 20 - Fri 24 September 2021

Keynote Speakers

Lionel Briand

Lionel Briand is professor of software engineering and has shared appointments between (1) The School of Electrical Engineering and Computer Science, University of Ottawa, Canada and (2) The SnT centre for Security, Reliability, and Trust, University of Luxembourg. He is the head of the SVV department at the SnT Centre and a Canada Research Chair in Intelligent Software Dependability and Compliance (Tier 1).

He holds an ERC Advanced Grant, the most prestigious European individual research award, and has conducted applied research in collaboration with industry for more than 25 years, including projects in the automotive, aerospace, manufacturing, financial, and energy domains. In 2010, he was elevated to the grade of IEEE fellow for his work on testing of object-oriented systems. He was also granted the IEEE Computer Society Harlan Mills award (2012) and the IEEE Reliability Society Engineer-of-the-year award (2013) for his work on model-based verification and testing. His research interests include: Model-driven development, testing and verification, search-based software engineering, requirements engineering, and empirical software engineering.

More information can be found on: https://www.lbriand.info/home


Amy Ko

Amy J. Ko is a Professor at the University of Washington Information School and an Adjunct Professor at the Paul G. Allen School of Computer Science and Engineering. She directs the Code & Cognition Lab, where she and her students study CS education, human-computer interaction, and humanity's individual and collective struggle to understand computing and harness it for equity and justice. Her earliest work included techniques for automatically answering questions about program behavior to support debugging, program understanding, and reuse. Her later work studied interactions between developers and users, and techniques for web scale aggregation of user intent through help systems; she co-founded AnswerDash to commercialize these ideas. Her latest work investigates effective, equitable, and inclusive ways for humanity to learn computing, especially how data, algorithms, APIs, and AI can both empower and oppress. Her work spans more than 130 peer-reviewed publications, with 12 receiving best paper awards and 4 receiving most influential paper awards. She is an ACM Senior Member, and member of ACM SIGCHI, SIGCSE, and SIGSOFT. She received her Ph.D. at the Human-Computer Interaction Institute at Carnegie Mellon University in 2008, and degrees in Computer Science and Psychology with Honors from Oregon State University in 2002.

More information can be found on: http://faculty.washington.edu/ajko


Pedro Domingos

Pedro Domingos is a professor of computer science at the University of Washington and the author of "The Master Algorithm". He is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI, and a Fellow of the AAAS and AAAI. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science. He helped start the fields of statistical relational AI, data stream mining, adversarial learning, machine learning for information integration, and influence maximization in social networks.

More information can be found on: https://homes.cs.washington.edu/~pedrod