Alexander Zadorojniy

Biography

Sasha is a research scientist in the Wearable and IoT Solutions group at IBM Research – Haifa. He holds a Ph.D. from Tel-Aviv University and a B.Sc. and M.Sc. in electrical engineering from the Technion - Israel Institute of Technology. His research involved the development of efficient optimization algorithms for discrete time stochastic control problems, and solving real life design and management problems. Sasha’s awards for scientific publications include INFORMS Wagner finalist, GYSS finalist, CSER first runner-up theoretical award, INFORMS Nicholson finalist, and ORSIS winner. He has 10 years of hardware design experience at Intel IDC specializing in verification and validation across multiple disciplines within leading edge Intel processors, and in leading unit designs and designing complex clock networks. At IBM he developed a constrained Markov Decision Process based algorithm for operational optimization of waste water treatment plants (WWTPs). Recently Sasha worked on gesture recognition using a Hidden Markov Model (HMM) framework, and he is currently working on solving problems with partial observability using a Partially Observable Markov Decision Process (POMDP) framework. Sasha is a research scientist in the Wearable and IoT Solutions group at IBM Research – Haifa. He holds a Ph.D. from Tel-Aviv University and a B.Sc. and M.Sc. in electrical engineering from the Technion - Israel Institute of Technology. His research involved the development of efficient optimization algorithms for discrete time stochastic control problems, and solving real life design and management problems. Sasha’s awards for scientific publications include INFORMS Wagner finalist, GYSS finalist, CSER first runner-up theoretical award, INFORMS Nicholson finalist, and ORSIS winner. He has 10 years of hardware design experience at Intel IDC specializing in verification and validation across multiple disciplines within leading edge Intel processors, and in leading unit designs and designing complex clock networks. At IBM he developed a constrained Markov Decision Process based algorithm for operational optimization of waste water treatment plants (WWTPs). Recently Sasha worked on gesture recognition using a Hidden Markov Model (HMM) framework, and he is currently working on solving problems with partial observability using a Partially Observable Markov Decision Process (POMDP) framework.

Research Interest

electrical engineering