CS-Can|Info-Can is pleased to announce the winners of the 2020 Lifetime Achievement Award, which recognizes current or former faculty members in Canadian Computer Science Departments, Schools or Faculties who have made outstanding and sustained contributions to computing over their careers. The awards can be for achievement in research, teaching, service, or any combination of these.

Kellogg S. Booth

Kellogg S. Booth

University of British Columbia

Dr. Kellogg Booth, a much-loved and accomplished researcher in computer graphics and human-computer interaction (HCI), has been an amazing leader nationally in building research capacity, in enabling interdisciplinary research, and in mentoring students and junior colleagues.

Kelly obtained a BSc at Caltech (1968) and MA (1970) and PhD (1975) at the University of California at Berkeley. He worked eight years in interactive graphics as a programmer at Lawrence Livermore Laboratory before taking a position at the University of Waterloo in 1977 where he co-founded the Computer Graphics Laboratory and later served as the third director of the Institute for Computer Research. He moved to The University of British Columbia in 1990 as founding director of the Media and Graphics Interdisciplinary Centre (MAGIC) and member of the Imager Computer Graphics Laboratory. He has been Professor Emeritus since 2017.

His doctoral studies co-developed the novel PQ- tree data structure and linear-time algorithm for the consecutive ones problem that has been used extensively in bioinformatics. Over the decade that followed he worked on algorithms for graph-theoretic problems but eventually his core interests converged on computer graphics, interaction techniques, and collaboration technology.

Both a visionary and a selfless advocate for the field, Kelly took on increasingly significant roles at departmental, university, and national levels. At Waterloo and UBC, he fostered research collaborations between computer scientists and researchers across campus in a variety of disciplines by exploring applications of interactive computer graphics and visualization. He also built links to non-academic institutions. During the 1980s, he and his colleagues and students collaborated extensively with the National Research Council, the National Film Board, and almost all of the early Canadian animation software start-ups, training a generation of graphics and interaction experts who played critical roles in Canadian graphics and computer animation companies. During the 1990s, he helped initiate projects with Science World BC and BC Children’s Hospital, and he led research collaborations with other universities. Under his guidance, MAGIC thrived as the “go-to” centre at UBC for collaborations involving emerging digital media that touched on nearly every facet of academic research and teaching.

Nationally, Kelly was a researcher in the Institute for Robotics and Intelligent Systems (IRIS) network of centres of excellence (NCE), theme leader and director of technology in the TeleLearning NCE, associate director in the NECTAR strategic network, and founding scientific director of the Graphics, Animation, and New Media (GRAND) NCE, arguably his most significant contribution to Canadian computer science.

GRAND was a unique community of 250+ researchers at 33 Canadian universities in nine provinces with over 160 industry partners and receptor organizations. Theoretical and applied problems in computer graphics, visualization, and human-computer interaction were explored by computer scientists and engineers working with social scientists and humanists to understand the cultural, economic, legal, and social consequences of emerging digital media technologies. A key aspect Kelly built into GRAND was inclusion of top Canadian art and design universities as equal partners in the research. Many collaborations initiated in GRAND are still in place.

Kelly has a keen insight into both the scholarly and non-scholarly aspects of building top-notch research environments. He is an unwavering advocate for teaching as an essential part of a research faculty member’s portfolio. He has taught at all levels of the curriculum, ranging from discrete mathematics to introductory programming for engineers to advanced undergraduate and graduate courses in HCI and computer graphics. He received two honorable mentions for “Incredible Instructor” awards in UBC CS. He stands out for his excellence in mentoring, his selfless effort building the careers of others, and his contagious sense of adventure. His students are leaders in Canada and abroad in academia and in industry. He served as president of the Canadian Human-Computer Communications Society and as secretary on the CS- Can/Info-Can Board of Directors.

It is hard to overstate the extent of Kelly’s lifetime of contributions to Canadian computer science. He has elevated and inspired those who work with him, and continues to do so.

Ming Li

Ming Li

University of Waterloo

Professor Ming Li has made major contributions to the creation of a modern information theory (Kolmogorov complexity) and in shaping the field of Computational Biology. Li completed his PhD at Cornell University in 1985, followed by a postdoctoral fellowship at Harvard. A University Professor at the University of Waterloo, he won Killam Prize in 2010 for his contributions in Computer Science.

We live in an information society. What is information? Is there a theory that governs information carrying entities similar to that of Newtonian mechanics to the classical world? The answer is Kolmogorov complexity. Kolmogorov complexity provides a universal measure of information, information content, and randomness. Li and his colleagues have extended Kolmogorov complexity to two sequences that lead to a universal metric of information distance. They have also connected information to thermodynamics and computed the ultimate thermodynamics cost of creating or erasing a sequence. This has actually led to zero-shot learning. In a SIGKDD04 paper (pp. 206-215), Keogh, Lonardi and Ratanamahatana demonstrated that Li’s parameter-free information distance method was better than all 51 methods for time series clustering found in the seven top data mining conferences. Over 1,000 papers have applied Li’s method to language classification, question and answer, cancer cell line identification, music classification, phylogeny, anomaly detection, software measurement and obfuscation, malware detection, nucleosome occupancy, protein sequence/structure classification, fetal heart rate tracing, COVID-19 analysis, deep learning, and many more.

Expected-case analysis of algorithms is a major challenge in Computer Science, as one has to average over all possible inputs. A Kolmogorov random string holds the key to this problem. It turns out that if one analyzes an algorithm on one typical Kolmogorov random input, then that automatically gives the average case over all inputs. Li and his colleagues used this method to solve many open questions in theoretical computer science.

The complete history and theory of Kolmogorov complexity, together with these works and many applications were digested in Li and Vitányi’s book “An Introduction to Kolmogorov Complexity and its Applications”. The book is considered a classic text in Computer Science and widely read. It won the McGuffey Longevity Award in 2020.

Li has worked in many other scientific areas, including his pioneering contributions to the field of Computational Biology. In particular, he has made substantial contributions to the area of Bioinformatics. Currently very relevant, some of his recent work is related to COVID-19 neutralizing antibody sequencing. DNA sequences have pairing mechanisms; hence, one can use PCR to sequence them, as in COVID-19 RNA tests. Protein sequences, on the other hand, cannot use PCR. In 2016, Li and his team published first complete protocol to sequence a complete monoclonal antibody in Nature Scientific Report. They then improved the process in PNAS’2017, Nature Methods’2019, then in Nature Machine Intelligence 2021 (accepted). These intensive research studies have created an industry of antibody sequencing. During the COVID-19 pandemic, Li’s team has helped to process and analyze many antibody sequences.

Li has been awarded the prestigious NSERC E.W.R. Steacie Memorial Fellowship and the Killam Research Fellowship. He is a Tier I Canada Research Chair in Bioinformatics and is a Fellow of the Royal Society of Canada, ACM, and IEEE.  He has also won the Ontario Premier’s Discovery Award for Innovation Leadership.

Renée J. Miller

University of Toronto

Professor Renée Miller is world-renowned as a pioneer in data management, especially for the creation of tools to integrate, transform, query and analyze information. Her contributions to data integration, schema mapping, and data exchange have established her as one of the seminal thinkers in database systems.

Overall, Professor Miller’s scholarly and applied research has been outstanding in quality, quantity, and breadth. Her research profile is unique in that it combines theoretical elegance, reflected by citations and scholarly awards, with industrial impact, reflected by patents and successful industrial products.

Her work stands out for its originality and elegance, while being at the same time one of those rare and much-needed instances of academic research that bridges in a principled way theory and practice.

At the same time, Professor Miller has been a leader among her peers in Canada and abroad, spearheading research with seminal results.  Recently, inspired by the Open Data movement, she has been studying and creating open source data discovery and data preparation solutions. Her goal is to develop the scientific foundations to ensure that data can be used, curated and integrated in an open, transparent way so as to support the goals of transparent institutional decision-making.

Professor Miller was the second Bell Canada Chair of Information Systems at the University of Toronto,  a fellow of the Royal Society of Canada, and a Fellow of the Association for Computing Machinery.  Her students are a constant priority and have received many awards including but not limited to the SIGMOD Jim Gray Doctoral Dissertation Award and an Ontario Early Researcher Award.

Jonathan Schaeffer 

Jonathan Schaeffer

University of Alberta

Jonathan Schaeffer is Distinguished Professor of Computing Science at the University of Alberta.  In a career spanning over 35 years, Jonathan has had impact locally in Edmonton, nationally in Canada, and internationally. He has excelled in research, teaching, and service.

Jonathan’s research is in artificial intelligence (AI). As a graduate student, he was advised to work on AI applications of societal benefit, such as medical. But as Jonathan’s non-academic passion was playing games, he decided to combine his pastime with his career. His AI research was concentrated in the areas of search (looking for solutions) and knowledge (assessing “goodness”), both areas of importance to building high-performing game-playing programs. He developed a chess program that tied for first in the 1986 World Computer Chess Championship. He wrote a checkers program that made computing science history by being the first program to earn the right to play for the human World Championship. In 1992 his program narrowly lost, but in 1994 it became World Champion — a feat recognized by the Guinness Book of World Records .

He continued work on checkers and in 2007 announced that checkers was solved — his program would never lose. He led an effort to create the first strong poker-playing program in 2003. In 2008, the University of Alberta’s Poker Research Group achieved AI history by defeating world-class human players — another feat in the Guinness Book of World Records . In the 2000s he also worked on video games, helping develop software that was deployed by major games companies.

Jonathan’s research has been recognized nationally and internationally -with over 12,000 citations and an impressive H-index of 58. He has trained over 75 graduate students and worked with many undergraduates. He is a popular teacher.

Jonathan was one of the architects for the building of a national vision for high-performance computing (HPC) in Canada. As a co-author of the national long-range plan for Canadian HPC, in 2005 Jonathan brought the country together to successfully make the case for almost $250 million of funding to build this infrastructure of national importance.

Jonathan is a co-founder of the world-famous Alberta Machine Intelligence Institute (Amii). His first startup company, BioTools (1995-2009), built world-class bioinformatics software. He is the co-owner of Onlea (onlea.org, 2014-present), which builds engaging online learning experiences.

John Tsotsos

John Tsotsos

York University

John Konstantine Tsotsos received his Hons. BASc in Engineering Science, MSc in Computer Science and PhD in Computer Science all from the University of Toronto in 1974, 1976 and 1980 respectively. He then joined the University of Toronto on faculty in both Departments of Computer Science and of Medicine. He founded the internationally respected computer vision group at the University of Toronto in 1980. He moved to York University in 2000 where he is Distinguished Research Professor of Vision Science, while maintaining Adjunct Professorships at the University of Toronto in the Departments of Computer Science and in Ophthalmology and Vision Sciences. He directed York’s renowned Centre for Vision Research from 2000-2006 and is the founding Director of York’s Centre for Innovation in Computing at Lassonde.

Tsotsos’ research has always focused on how images are processed, understood and used. He recognized the importance of  interdisciplinarity in computer science research early, well before it became widely appreciated. One major contribution addressed the understanding of the limits of visual information processing. He provided the first formal theorems regarding the computational complexity of human vision. Using these, he defined a neural architecture and theory of human visual attention termed Selective Tuning, including counterintuitive predictions for human vision. These predictions have been strongly supported experimentally, forming a new basis for vision science. For example, one of these predictions that went against current thinking, was that top-down attention suppresses local interfering context. This is now supported by dozens of experiments. His 2011 MIT Press monograph, A Computational Perspective on Visual Attention, details his theory. He and his lab have examined many aspects of attentional processing in machines and in humans and he is best known internationally for this body of work. His lab is also well-recognized as a pioneer in active object recognition and visual search. Both research threads led to embodiments on practical robots, notably an early children’s autonomous wheelchair project named PLAYBOT. Overall, his seminal contributions to computational vision span early and intermediate visual representations, computational complexity of perception, visual attention, robotic active perception, and medical image analysis, particularly in cardiology.

Tsotsos trained the future of Canadian computer vision and robotics researchers.  His trainees have gone on to strong research careers of their own or founded successful startups, with many in advanced leadership positions in academia and industry, nationally and internationally.

An interest in applied computing pervades his career. He is a co-inventor on 4 patents, was co-recipient of the 1997 CITO Innovation Award for Leadership in Product Development, and has co-founded 5 companies. He was an IBM Center for Advanced Studies Visiting Scientist for several years.

He has served on the editorial boards of several top journals of various mandates, spanning AI, computer vision, human vision, cognition, and applications in medicine. He has been on the organizing committees of over 100 workshops and conferences, including General Chair of computer vision’s most prestigious conference, the International Conference on Computer Vision, in 1999.

Additional honours include: Canadian Heart Foundation Scholar 1981-1984; Fellow, Artificial Intelligence and Robotics Program of the Canadian Institute for Advanced Research 1985-1995; Tier I Canada Research Chair of Computational Vision 2003-2024; Fellow of the Royal Society of Canada, 2010; Fellow IEEE, 2018; Canadian Image Processing and Pattern Recognition Society Award for Research Excellence and Service, 2006; 1st President’s Research Excellence Award from York University, 2009; Geoffrey J. Burton Memorial Lectureship in 2011 from the United Kingdom’s Applied Vision Association for significant contribution to vision science; the Royal Society of Canada’s 2015 Sir John William Dawson Medal for sustained excellence in multidisciplinary research, the first computer scientist so honored; and 10 conference paper recognitions.

Tsotsos’ trainees celebrated his 65th birthday with a Verbal Festschrift and Banquet in May 2018 with over 100 attendees and a day’s worth of excellent presentations (http://jtl.lassonde.yorku.ca/2018/08/jkt65-celebration/).


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