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Dr. Alexander Ioannidis is an Adjunct Professor in Computational and Mathematical Engineering, where he teaches machine learning and data science, and a researcher and Instructor in the Department of Biomedical Data Science. He earned his Ph.D. from Stanford University in Computational and Mathematical Engineering together with an M.S. in Management Science and Engineering (Optimization). 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 at the University of Cambridge from the Department of Applied Math and Theoretical Physics in Computational Biology, and a Diploma in Greek. As a current researcher 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.