Postdoctoral Researchers
ude.csu@gihs Website
Guangyao mainly works on coordination and learning algorithms for multi-robot decision-making under uncertainty with an emphasis on information gathering applications.
PhD Students
ude.csu@artabss Website
Sumeet is interested in biologically plausible learning algorithms and models and their applications to robotics. Previously he worked on Quality Diversity Reinforcement Learning (QD-RL) and generative models for control. He is currently working on QD + language for open ended skill discovery, and planning as inference.
ude.csu@rraduihc Website
Darren is generally interested in multi robot systems that combine novel hardware design with unique algorithmic approaches. Currently, his research focuses on event based visual navigation through a swam of resource constrained quadrotors. Before coming to USC, Darren received my B.S.E in Electrical and Computer Engineering from Princeton University.
ude.csu@eejaytas
ude.csu@edgehk Website
Shashank’s research interests include deep reinforcement learning, machine learning, and robotics. Shashank is a strong believer in the power of AI to improve the quality of life of people around the world.
ude.csu@uhiuhehz Website
Zhehui’s goal is to build intelligent agents that with the ability to perform complex tasks robustly and safely within unstructured environments via autonomous and unsupervised adaptation to the environment. He focuses on reinforcement learning, robot learning and foundation models.
ude.csu@nauhsnuy Website
Yunshuang received a M.S from UPenn and a B.E. in both automatic control and Mechatronic Engineering from Chu Kochen Honors College, Zhejiang University. Her research interests are in robotics, machine learning, and computer vision, especially the applications of CV in robot perception.
ude.csu@uilnuhci Website
Arthur’s research interests lie in the fields of imitation learning and reinforcement learning for robotic manipulation. Currently, his research focuses on vision-based bimanual manipulation. Prior to joining USC, he completed a master’s degree in Computer Science from the University of California, Los Angeles (UCLA), and a bachelor’s degree in Computer Science from the University of Wisconsin-Madison.
ude.csu@ejnagrom Website
Jeremy’s research interests include developing novel Inverse Kinematics solvers and planning algorithms for manipulators. In the future he will transition to look at dexterous manipulation problems.
ude.csu@teijgnib Website
Bingjie is interested in learning-based approach for robot manipulation and simulation-to-reality transfer for contact-rich manipulation tasks. Before joining USC, Bingjie received an MS in Computer Science from Brown University and a bachelor degree in Computer Science from Huazhong University of Science and Technology.
ude.csu@zecarg Website
Grace is generally interested in efficient robot learning methods by using prior multi-task data or learned policies. Specifically, her research focuses on efficient multi-task learning through shared behaviors and efficient inverse reinforcement learning using multi-task data.
Master’s Students
ude.csu@inapurkr
Rahul’s fields of interest lie in Reinforcement Learning and Computer Vision. Currently Rahul is working on Deep RL for a drone control.
Ujjwal focuses on deep reinforcement learning for robotics.
ude.csu@06793rp Website
Prashanth is interested in reinforcement learning, classical controls, and robotics. Prashanth’s research efforts are geared towards the development of solutions that prioritize safety and the ability to generalize effectively in robotics, through the integration of learning-based and control theory strategies.
ude.csu@669gnayz
Zhaojing’s research interests lie at the intersection of Reinforcement Learning and Robotics. Zhaojing is interested in applying learning method for optimal robot policies in both simulator and real-world. Zhaojing has experience in Deep RL for quadrotor control and the model can be zero-transfered to the real world. Their current focus is on efficient robot learning with RLHF.
Yulun focuses on deep reinforcement learning for robotics.
Undergraduate Students
ude.csu@trapalap Website
Anisha is an undergraduate studying Computer Engineering and Computer Science. At RESL Anisha works on using quality diversity algorithms to improve performance and resilience in complex RL tasks. Her research interests lie at the intersection of evolutionary algorithms, reinforcement learning, and AI for robotics. Outside of research, she enjoys teaching fun CS concepts and exploring classic cinema.
