About Me
I'm a PhD candidate at Stanford University, focusing on the intersection of artificial intelligence and robotics. My research explores novel approaches to machine learning that can enhance robot perception and decision-making in complex environments.
Previously, I worked as a research engineer at DeepMind, where I contributed to projects involving reinforcement learning and computer vision. I received my BS in Computer Science from MIT.
Research
Adaptive Robot Learning
Developing new algorithms for robots to learn and adapt to changing environments through real-time sensor data and reinforcement learning.
Multi-Agent Systems
Investigating coordination strategies for multiple robots working together in dynamic environments using distributed algorithms.
Featured Projects
Project Title 1
Brief description of the project and its impact on the field of robotics and AI.
Project Title 2
Brief description of the project and its impact on the field of robotics and AI.
Project Title 3
Brief description of the project and its impact on the field of robotics and AI.
Publications
Novel Approach to Robot Learning in Dynamic Environments
Chen, A., Smith, J., Johnson, K.
International Conference on Robotics and Automation (ICRA) 2024
Novel Approach to Robot Learning in Dynamic Environments
Chen, A., Smith, J., Johnson, K.
International Conference on Robotics and Automation (ICRA) 2024
Novel Approach to Robot Learning in Dynamic Environments
Chen, A., Smith, J., Johnson, K.
International Conference on Robotics and Automation (ICRA) 2024
Letters
Letter to the Future
A reflection on the role of robotics and AI in shaping the world of tomorrow.
Open Letter to Researchers
Discussing collaboration and ethics in the field of machine learning.