Introduction to the MERS Lab with Professor Brian Williams

Led by Professor Brian Williams, the Model-based Embedded and Robotic Systems Group develops “cognitive robots” - robots that are able to think and act much like humans do. There are three main thrusts to the research in the Model-Based Embedded and Robotics Systems (MERS) group: goal-driven interaction with robots, natural human/robot teaming, and robotic reasoning about the environment.

Jingkai Chen & Viraj Parimi: Robot Arm Assembly

Jingkai Chen is a Ph.D. student in the MIT department of Aeronautics and Astronautics.  His research interests are primarily in the areas of robotics, AI planning, and multi-agent systems with applications in interconnected robotic systems for manufacturing, logistics, and field operation. Before MIT, Jingkai obtained his B.E. degree in Control Science and Engineering from Chu Kochen Honors College at Zhejiang University in 2016. Previously, he worked in MIT McGovern Institute of Brain Research, UCLA Network Research Lab, and Zhejiang University NeSC Lab.

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Viraj Parimi is a Ph.D. student in in the Department of Electrical Engineering and Computer Science (EECS). He is advised by Professor Brian Williams and is currently working as a graduate research assistant in the MERS group. His research interest is the problem of safe skill-learning for robotic agents which spans diverse areas including robotics, AI planning, reinforcement learning and multi-agent systems.

Website | Publications 

Cyrus Huang: Planning for Autonomous Cars

Xin "Cyrus" Huang is a second year graduate student in the Department of Aeronautics and Astronautics at MIT. He received his B.S. in Engineering and Computer Science from Harvey Mudd College in 2016. His current research is focused on learning and predicting agent intentions in the context of multi-agent probabilistic planning. Before joining MERS, Cyrus did research on multi-agent SLAM and spent two summers at Mayfield Robotics as a robotics engineer intern.

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Marlyse Reeves: Autonomous Agents Reasoning

Marlyse Reeves is a first-year PhD student in the EECS department at MIT. She received her B.S. in Aeronautics and Astronautics from MIT in 2017. Her current research focuses on multi-vehicle online planning, incorporating complex dynamics and constraints. She is also interested in risk-aware planning, fault protection and diagnosis, and adaptive sampling. Outside of the lab, she enjoys playing soccer, dancing, and reading science fiction.

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