Alex Fried is a highly experienced data scientist leader, product innovator, and full stack machine learning expert with an impressive background in identifying product opportunities and enabling teams to move from research stage to fully deployed applications. Alex has a bachelor's degree in Mathematics and Physics from the University of Pennsylvania and a Ph.D. in Physics from Stanford University. His research interests include Machine learning with encrypted data, Federated learning, Differential privacy, and Partial-homomorphic encryption. He is also interested in Complex systems/ecosystems, Metrology and efficient utilization of sensor systems, ML-Ops / Auto-ML/ Auto-Remediation/ Interoperability, and Information theory applied to ML. Alex has held many leadership positions such as Director at EY-Parthenon and worked for several organizations such as International Consulting Associates, Inc., DataKind, Flybits, automotiveMastermind®, and Motiv Inc.