Machine Learning for Biomedical Data Science

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As science continually seeks ways to improve the analysis and remedy of health conditions, bioinformatics - the union of biology and computer science - has emerged as a relatively new field in which the collection, processing, and application of data to biological questions unlock mysteries at the molecular level. Bioinformatics seeks to discover within data sets the relevant, "hidden" information needed to generate solutions that address current challenges in biological data science.Situated at the forefront of bioinformatics research, Dr. Yifeng Li's work in artificial intelligence (AI) and machine learning filters and identifies crucial genetic and physical information that is currently either buried in too much data or waiting to be discovered due to too little data. The key objective of Dr. Li's research program is to develop new algorithm-based machine learning approaches that:1. teach AI to better interpret complex biological data/biomedical image analysis;2. increase efficiencies in solving multi-objective design problems in biotechnology through optimization and reinforcement learning techniques;3. fill gaps created by insufficient biological data by using transfer learning techniques; and4. can be used for real-life applications and thereby advance the data science field across a variety of disciplines.From over-the-counter headache medications to cancer drugs, each treatment must be tested for its ability to reach the designated target within the body and have the desired effect. Dr. Li's research explores new methods of filtering through massive amounts of data by developing algorithms that literally "teach" software to better understand the biological information within a data set and then fulfill all required objectives, with the goal of improving and streamlining drug design. In cases with too little data - such as in x-rays, MRIs, and other medical technologies that require enough images to be an effective diagnostic technique - Dr. Li and his team are developing new algorithms to fill gaps in imaging and thereby improve biomedical image analysis.Dr. Li's research program focuses on creating new computer models and methods that address data science challenges in a variety of real-life applications. His work allows the emergent field of bioinformatics to maximize its effectiveness and ultimately advance the capacity of AI to support the health and well-being of all Canadians.