University Professor Ming Li is the 2024 recipient of the IEEE Computer Society W. Wallace McDowell Award, a prestigious honour conferred for his pioneering and enduring contributions to modern information theory and bioinformatics.
Named after W. Wallace McDowell, director of engineering at IBM during the development of the landmark IBM 701 computer, the award has been conferred annually since 1966 by the IEEE Computer Society for outstanding theoretical, design, educational, practical, or other innovative contributions.
“Congratulations to Ming on receiving the 2024 Wallace McDowell Award,” said Raouf Boutaba, Professor and Director of the Cheriton School of Computer Science. “This recognition is richly deserved. Ming has not only been a pioneer in Kolmogorov complexity and in doing so has laid the foundation for a modern information theory, but he is also an innovator in computational biology by applying machine learning to develop personalized immunotherapies to treat cancer and infectious diseases.”
About University Professor Ming Li
University Professor Li completed his PhD at Cornell University in 1985, followed by a postdoctoral fellowship at Harvard. In 1989 he joined the University of Waterloo as an Associate Professor in what was then the Department of Computer Science, and was promoted to Full Professor in 1994. He was named the Canada Research Chair in Bioinformatics, a prestigious position he has held continuously since 2002. In 2009 he was named a University Professor, a title conferred to University of Waterloo faculty to recognize exceptional scholarly achievement and international pre-eminence.
Over his career, University Professor Li has made many pioneering and enduring contributions to modern information theory and bioinformatics, the highlights of which are described below.
With his colleagues Charles Bennett, Peter Gacs, Paul Vitányi and Tao Jiang, University Professor Li systematically developed Kolmogorov complexity, a central theory and powerful tool in information science that deals with the quantity of information in individual objects. In a paper titled “Information Distance,” presented at the 25th Annual ACM Symposium on the Theory of Computing in 1993, University Professor Li together with Charles Bennett, Peter Gacs, Paul Vitányi and Wojciech Zurek extended Kolmogorov complexity to measure not just information within one sequence, but also information between two sequences. He also developed the incompressibility method to solve several long-standing open problems in average-case analysis of algorithms.
His textbook with Paul Vitányi, titled An Introduction to Kolmogorov Complexity and its Applications, has helped educate a generation of researchers and practitioners about what information is, as well as provide a foundation for many research fields including deep learning and large language models. This widely read and celebrated computer science classic received a McGuffey Longevity Award in 2020.
University Professor Li has contributed immensely to other scientific fields most notably to bioinformatics, a field that uses computational techniques to deduce the structure and function of DNA, RNA, protein and peptide molecules. University Professor Li’s 1994 paper titled Linear approximation of shortest superstrings, with Avrim Blum, Tao Jiang, John Tromp and Mihalis Yannakakis, provided the fundamental background used in shotgun DNA sequencing techniques and is described in detail in well-known computational biology books.
In 2016 University Professor Li and his team published in Nature Scientific Report the first complete protocol to sequence a monoclonal antibody protein. They have since improved their computational techniques and published results to sequence peptides, neoantigens and glycoproteins from mass spectrometry data for novel immunotherapies in a variety of top-tier journals, among them the Proceedings of the National Academy of Sciences, Nature Methods, Nature Communications and Nature Machine Intelligence.
University Professor Li co-founded and served as an editor-in-chief for Journal of Bioinformatics and Computational Biology. Through this journal and his innovations, he played a major role in reshaping the early heuristic bioinformatics into the current computer science–based computational biology. Furthermore, his elegant algorithms and ideas have led to commercially viable products that have made a tremendous impact on proteomics research and therapies. The bioinformatics software he and his students have developed have been commercialized successfully by Bioinformatics Solutions Inc., a Waterloo-based company he founded.