CACS/AIC Outstanding Young Canadian Computer Science Researcher Prizes
The Canadian Association of Computer Science/Association informatique Canadienne is pleased to announce the winners of the Outstanding Young Canadian Computer Science Researcher Prize for 2013. Short summaries of their research contributions follow.
Dr. Kevin Leyton-Brown has demonstrated remarkable international leadership during the past decade in the areas of game theory, auction design, and empirical algorithmics. Game theory studies what happens when strategic interests collide. The internet facilitates a wide range of interactions and electronic commerce that are larger and more complex than traditional analysis can handle. Leyton-Brown's research aims to extend such analysis to internet scale. It focuses on computational tools, auctions, and fast algorithms for solving hard problems. His key contributions to computational game theory include the first representation language for describing large, general settings in which all players interact; algorithms for efficiently answering game theoretic questions; and novel methods for predicting human behavior in strategic situations. He has developed novel algorithms for complex multi-good auctions that have had wide impact in electronic commerce companies and government, including the top contender for use in the US FCC’s upcoming, $50 billion “incentive auction” of radio spectrum. He has also developed the first methods for using machine learning to characterize algorithm performance, as well as developing some of the world's fastest constraint-solving algorithms.
Kevin is the coauthor of two widely adopted and widely cited textbooks on multiagent systems and game theory. He has cotaught the most popular online course on Game Theory that enrolled a quarter-million students spanning 98% of the world’s countries. He has won 5 best paper awards in the past three years; two Google Faculty Research Awards; and 22 medals in 5 international SAT competitions (2003–2012). Kevin has worked for seven different startup companies since 1999, including Vancouver-based Zite, which was acquired by CNN. Kevin’s students have won over two dozen graduate fellowships and awards, including three best PhD thesis awards. He is currently associate editor at three top journals (AIJ, JAIR, ACM-TEAC) and was recently program co-chair of the ACM Conference on Electronic Commerce.
Professor Bianca Schroeder’s research addresses the reliability of Internet-scale systems. Despite our growing dependence on Internet-based services and the devastating impact of failures, our understanding of how Internet-scale services fail is poor. The lack of publicly available failure data, as well as the complexity of analysing failure at scale only exacerbate the challenge. Prof. Schroeder has addressed these challenges by combining large-scale data collection from production data-centers with statistical data analysis. Prof. Schroeder's seminal insights have had tremendous impact on both the research community, and on industry practice. Her research has dispelled long-standing misconceptions about systems failures and has produced system models that help identify principles for improved systems design. Her papers are widely cited and have received numerous awards. Prof. Schroeder’s work has been recognized by the highly prestigious Sloan Fellowship, as well as an NSERC Discovery Accelerator Supplement, a Connaught New Research Award, a NetApp Faculty Fellowship Award, and an IBM PhD Fellowship.
Dr. Sandra Zilles works in the area of computational learning theory, where she has made numerous important contributions. She is a Canada Research Chair (Tier 2) at the University of Regina with significant NSERC and CFI funding. One of her recent papers won the Best Paper award at the German AI conference in 2012. She is a regular contributor to the top conferences in her field (ALT and COLT) and she has been named a co-chair of the conference steering committee for ALT. She is a rare person who can bridge the gap between theory and practice. She has repeatedly demonstrated an enviable combination of breadth and depth, combining expertise in several areas to illuminate fundamental phenomena. Collaborations with other researchers, established and junior, are a prominent feature of Dr. Zilles’ publication record. Her colleagues come from Japan, Singapore, the United States, Germany, as well as from other Canadian universities. She has many publications in the top journals of her field. For example, she has three publications in Artificial Intelligence, which is often considered to be the leading journal in that area. Many of her conference publications have been rated highly enough to be amongst the select few invited to appear in an associated journal’s special issue – after being expanded and further reviewed. She also has further important publications currently under review. She is renowned as a communicator par excellence, able to make difficult concepts accessible with clarity and simplicity: one of many reasons why colleagues and students hold her in high regard. Within her excellent publication record, her important research advances include: the surprising and insightful integration of two seemingly unrelated learning models that had been studied independently from each other for almost 20 years; substantial improvements upon previous research through new models of cooperative teaching and learning; and the significant improvement of a solution for a classical search problem using an intuitively clear and easy to understand idea based on techniques from machine learning. Her research career demonstrates creativity, productivity, independence and leadership ability.