Jonathan Yang

Jonathan Yang is a Graduate Student Researcher at Stanford University, specifically affiliated with the Stanford Artificial Intelligence Laboratory (SAIL). He is currently pursuing a Ph.D. in Computer Science, focusing on artificial intelligence, robotics, and control systems.

Academic Background and Research

• Current Position: Jonathan has been working as an Artificial Intelligence Researcher at SAIL since August 2022. His research aims to develop robots that can understand and navigate diverse environments by utilizing large datasets for learning. He collaborates with Professors Chelsea Finn and Dorsa Sadigh on projects related to multi-robot systems and reinforcement learning.1
• Previous Experience: Before his current role, he served as a Teaching Assistant for various courses, including Deep Reinforcement Learning and Introduction to Artificial Intelligence at Stanford. He also conducted undergraduate research at UC Berkeley under Professor Sergey Levine, focusing on reinforcement learning and robotics.1

Achievements

Jonathan has received several accolades throughout his academic career, including:

• USA Physics Olympiad Semifinalist
• USA Computing Olympiad Platinum Division
• Siemens Research Competition Semifinalist These honors reflect his strong background in both mathematics and computer science.1

Goals

His overarching goal is to enhance the capabilities of robotic agents so they can learn effectively from their environments, which involves leveraging off-policy datasets to improve learning efficiency in real-world applications.1