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Dr. Alexander Ioannidis (PhD, MPhil) earned his Ph.D. from Stanford University in Computational and Mathematical Engineering, where he teaches machine learning and data science as an Adjunct Professor in the School of Engineering. He also has an M.S. in Mgmt. Sci. and Eng. (Optimization) from Stanford. Prior to Stanford, he worked in superconducting computing logic and quantum computing at Northrop Grumman. He graduated summa cum laude from Harvard University in Chemistry and Physics and earned an M.Phil in Computational Biology and Diploma in Greek from the University of Cambridge. As a current research fellow in the Stanford School of Medicine (Department of Biomedical Data Science), his work focuses on the design of algorithms and application of computational methods for problems in genomics, clinical data science, and precision health with a particular focus on underrepresented populations in Oceania and Latin America.