Speaker Profile

Ph.D., Machine Learning Scientist, RubrYc Therapeutics

Dr. Taguchi is an interdisciplinary scientist working at the intersection of biochemistry and artificial intelligence (AI). He is an author on more than 20 publications in peer-reviewed journals, an inventor on several machine learning patents, and has received a Ph.D. in Biophysics and Computational Biology for his research on magnetic resonance spectroscopy of protein complexes. Dr. Taguchi was awarded two postdoctoral fellowships, one from the National Institutes of Health to support his research at the Massachusetts Institute of Technology (MIT), and another from the Japan Society for the Promotion of Science for international studies in Japan. At MIT, Dr. Taguchi built machine learning algorithms for automating multi-dimensional signal processing tasks. He won two AI hackathon competitions hosted by MIT, leading him to co-found a startup called MatchLab that uses machine learning to standardize the dermatological image collection process. Dr. Taguchi currently develops AI technologies for antibody discovery at RubrYc Therapeutics.

 Session Abstract – PMWC 2020 Silicon Valley

Track 2, January 22

Epitopes are the foundation of efficacy in therapeutic antibody discovery. Antibody discovery is severely limited in the targets and epitopes that can be accessed with traditional practices. Advances in molecular simulation and machine learning can over-come these limitations and enable discovery of on-epitope antibodies for traditionally challenging targets.