A man who would like to be a Doctor of Philosophy
About Me
I’m an AI Researcher at Lachesis (HK), where I develop medical AI systems and explore emerging technologies. My research lies at the intersection of AI for Science, healthcare intelligence, and generative modeling.
Publications
My publications with coworkers.
MOL-E3: Multi-Modal LLM with Reinforcement and Genetic Evolution
for Enhanced Molecular Design / Active
github url will be updated soon
NeurIPS 2026
Developed a multi-modal molecular design framework integrating large language models, reinforcement learning,
and genetic evolution to enhance molecular generation and optimization through fragment-level exploration and
multi-modal representation learning
A ML-Based Shared Bike Demand Prediction Based on Dynamic Golden Distance. / Master’s thesis
Msc thesis
Proposed a machine learning-based framework for shared bike demand prediction using dynamic golden distance,
integrating spatial and temporal factors to improve demand forecasting and support intelligent urban mobility
optimization.
Multi-modal
Collaborative Model Evolution: Automated Discovery and Refinement of Graph Augmentation Strategies / Submitted
ACM MM
Developed an automated framework for discovering and refining graph augmentation strategies through
multi-modal collaborative model evolution, improving adaptability and performance in graph representation
learning across diverse tasks and datasets.
Multi-Task Learning through the Lens of Causality / Submitted
NeurIPS 2026
Investigated multi-task learning from a causal perspective and contributed to a framework for modeling inter-task
relationships with improved interpretability and generalization
