I'm a B.Sc. student in Artificial Intelligence interested in the intersection of machine learning, computer vision, robotics, human motion analysis, and quantitative medical imaging.

My work focuses on applying mathematical and computational methods to real-world scientific and engineering problems, with particular interest in perception, predictive modelling, statistical learning, and intelligent systems operating under uncertainty.

I am currently working on human-aware motion planning for collaborative robotics at Chung Yuan Christian University in Taiwan.

The project focuses on a FANUC CRX-10iA/L collaborative manipulator operating in a shared human–robot workspace. I am developing and evaluating the system in NVIDIA Isaac Sim, integrating:

• RGB-D perception and dynamic obstacle tracking
• Robot kinematics and full-body collision modelling
• Reactive motion generation
• Human and robot velocity estimation
• Predictive collision-risk assessment
• Short-horizon clearance prediction
• Safety behaviours such as avoidance, yielding, and retreat

The longer-term objective is to transfer the framework from simulation to the physical FANUC platform.

I also conduct research in quantitative MRI in collaboration with IRCCS Policlinico San Matteo Hospital in Pavia.

The work investigates whether information derived from IVIM-DWI diffusion MRI can be used to predict pharmacokinetic biomarkers obtained from DCE-MRI, with particular attention to (K^{trans}).

The project involves cross-modality image preprocessing, spatial alignment, statistical analysis, predictive modelling, and robust evaluation under small-sample clinical-data constraints. I have explored both statistical and deep-learning approaches, including regularised regression, gradient-boosted trees, and U-Net-based models.