ABOUT US

Shie is a Professor at the Technion’ s Electrical Engineering department, working in the fields of machine learning, decision making, and control.

For the last 15 years, he was involved in cutting-edge research in these fields spanning from theoretical research to highly applied work.

Shie’s activities extend well beyond academia as the co-founder of 3 start-up companies and scientific consultant to many actors in the AI Space.

Assaf is a Professor at the Technion’ s Computer Science department, working in the realms of Distributed and Scalable Deep Learning, Internet of Things as well as privacy and Cyber Security. Assaf is an IEEE and ACM fellow and his work encompasses both theoretical and applied research.

Beyond his academic work, Assaf was instrumental in establishing the nascent Israeli Machine and Deep Learning eco-system as the co-founder of 2 start-up companies and as an advisory board member and consultant to multiple companies.

Shai is an Associate Professor at the Technion’s Faculty of Medicine, working in the fields of Computational Biology, Systems Immunology & Precision Medicine. He has been developing machine learning to study the drivers of immune variation, particularly in the context of aging, and to further Immune-based Precision Medicine.

Shai directs Tech.AI.BioMed and heads the Zimin Institute for AI solutions for healthcare. He is the founder and Chief Scientist of CytoReason, a PharmaAI company developing a machine learning model of human disease aimed at closing the data-insight gap in drug development.

Tamir is an Associate Professor at Technion’ s Data and Decision Sciences department, working in the fields of theoretical and practical aspects of machine learning. Professor Hazan research interests involve His research focuses on mathematically founded solutions to modern real-life problems that demonstrate non-traditional statistical behavior.

The practice of his work is motivated by many computer vision problems, as well as computational biology and language processing.