Deep Reinforcement Learning
Deep reinforcement learning for autonomous decision-making, with applications in autonomous overtaking and contact-rich robot learning.
Research Themes
My work centers on learning-based autonomy, practical reinforcement learning, and data-driven modeling.
Robot Learning and Contact-rich Manipulation
Current PhD research titled Deep Reinforcement Learning in Contact-Rich Robotic Manipulation Tasks, including peg-in-hole, insertion, and assembly-style robot learning problems.
Autonomous Systems and Autonomous Driving
Research on autonomous overtaking as a sequential decision-making problem using deep reinforcement learning and curriculum learning.
Machine Learning for Biological Data
Applied machine learning and deep learning for crayfish sex identification and disease detection using image and tabular data.
Data Engineering and Applied Machine Learning
Teaching and applied academic work connected to programming, data structures, database management systems, machine learning, and deep learning.