Alexander Ioannidis

I graduated summa cum laude in Chemistry and Physics from Harvard and completed an M.Phil in Computational Biology in the Dept. of Applied Math & Theoretical Physics at Cambridge. I earned my Ph.D. in Computational & Mathematical Engineering at Stanford and M.S. in Mgt. Science & Engineering (Numerical Optimization concentration). Prior to this I worked on novel superconducting computing logic and quantum computing at Northrop Grumman (Advanced Technology Lab).

My teaching has included introduction to machine learning algorithms, data science, AI in healthcare, and computational biology methods. My research group focuses on computational algorithm development and deep learning / AI for genomics & precision health with a particular focus on biobank-scale datasets, large tabular models, and phenotype/disease risk prediction, as well as population genetics with recent focus on large-scale cohorts across Oceania and across Latin America (Mexican Biobank).