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Adjunct Professor

Alexander Ioannidis

Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
Postdoctoral Scholar, Biomedical Data Sciences
Dr. Alexander Ioannidis (Ph.D., M.Phil) 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 Management Science and Engineering (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 from the Department of Applied Math and Theoretical Physics 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.

Education

Doctor of Philosophy, Stanford University, CME-PHD (2018)
Master of Science, Stanford University, MGTSC-MS (2018)
Master of Philosophy, University of Cambridge, Computational Biology (2005)
Bachelor of Arts, Harvard University, Chemistry and Physics (2003)