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Biswa Sengupta, PhD

Global Head of Machine Learning
Zebra Technologies

Dr. Sengupta has been a senior technical executive with broad-spectrum expertise in leading various ventures – from Artificial Intelligence startups to Fortune 500 (AXA, Huawei and Zebra) companies' AI divisions. He has hands-on experience in leading teams with expertise in incubating commercially viable products using computer vision, Natural Language Processing, reinforcement learning and robotics. He is currently a Technical Fellow and Global Head of Machine Learning at Zebra Technologies. At Zebra, he spearheads special projects (retail, warehouse and healthcare verticals) that sit at the intersection of sequential decision making and robotics (incl. collaborative and autonomous robotics). Biswa obtained his PhD in dynamical systems/optimisation/energy efficiency from the University of Cambridge, attaining further training on Bayesian statistics and differential geometry at the University College London. Dr Sengupta is a part of the ACM Steering group responsible for promoting dialogue on technology and computing policy issues with the European Commission and other governmental bodies in Europe and the informatics and computing communities.


Orchestration AI ​

Task management systems in a retail or warehouse logistic environment are often static, wherein tasks and workforce to execute the tasks are planned weeks in advance. Such deferred planning poses a problem where schedules must be changed in response to a dynamic event – like increased foot-fall due to online promotion, health and safety events that cannot be pre-planned, etc. This talk investigates sequential planning algorithms emerging from deep reinforcement learning to sense real-time drivers and constraints to operationalize agents, be it humans or co-bots, for a given task. The proposed framework – Orchestration AI (OAI) – can be used to organize and prioritize tasks and operationalize humans/robots for retail stores, fulfilment warehouses, dark stores, and back-of-store operations.