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Artificial Intelligence is an important tool in realizing the higher level autonomy in process industries. An important sub-sect of this is Reinforcement/Deep Reinforcement Learning. This session showcases its latest advancements using a high fidelity Primary separation vessel model. Insights into the bottlenecks for adaptation of this scheme from a platform and theoretical perspective are touched upon. Also, the future steps that the RL team with Dr. Biao is planning also gets emancipated.
Post Doctoral Fellow, University of Alberta
Kiru obtained his undergraduate degree in Electronics and Instrumentation (2004) followed by graduate degree in Process Control and Instrumentation (2006). He began his career as an "Embedded Software Engineer" catering to product development in Automotive domain. He later worked on product development for the Residential HVAC systems. In 2015, he completed his PhD in Explicit MPC's. He joined University of Alberta as a Postdoctoral Fellow in October 2016. He has worked on development and deployment of soft sensors for Dr. Biao Huang's IRC partners. His current research interests mainly focus on adapting Reinforcement learning as one of the tools in the quest towards autonomous process industries.