Paramjit Singh Baweja
Paramjit is a graduate student in the Robotic Systems Development program at Carnegie Mellon University. Majoring in Electrical and Electronics Engineering, he received his degree from Manipal Institute of Technology in 2023. His previous work as a researcher in the MEDCVR lab at the University of Toronto centered around autonomous soft tissue cutting using the dVRK. Moving forward, he is primarily interested in the application of technology within healthcare, with a particular focus on medical robotics.
Li-Wei Yang
Li-Wei is a Master’s student in the Master in Robotic Systems Development program at Carnegie Mellon University. He received his Bachelor’s degree in Biomechatronics Engineering at National Taiwan University. Before attending CMU, he worked as a research assistant at two different labs, focusing on Human-Robot Interaction and registration in medical robots. He is passionate about medical robotics, computer vision, reinforcement learning, and motion planning.
Shivangi Gupta
Shivangi is pursuing her Master’s in Robotics System Development at Carnegie Mellon. She received her undergraduate degree in Electronics and Instrumentation Engineering from BITS Goa, India, during which she pursued her undergraduate thesis at the Rehabilitation Robotics Lab at the University of Illinois Chicago. She has a strong interest in surgical robotics, prosthetics and exoskeletons.
Abhishek Warrier
Abhishek is a first year grad student at RI CMU pursuing the Masters in Robotic Systems Development (MRSD) program. He holds an undergraduate degree in Computer Science from SRMIST, India. Post graduation, he worked on sim2real RL as a Research Assistant at IITK and later joined a robotics startup where he was involved in developing the software stack for collaborative manipulators. His interest lies at the intersection of learning algorithms, vision and safe HRI.
Qilin Wu
Qilin is a Master’s student in the Master in Robotic Systems Development program at Carnegie Mellon University. In his previous research, he focused on developing new methods for robust global estimation and explainable graph neural networks. He is particularly interested in applying these techniques to robotic applications such as navigation, object manipulation, and scene understanding. His current research interests include explainable artificial intelligence (XAI) and deep reinforcement learning for robotics.