I am a Ph.D. student in Computer Science and Engineering at The Ohio State University, working at the intersection of computer vision, multimodal learning, deep learning, and medical image. I am a member of the OSU Imaging Genomics Lab, advised by Dr. Golrokh Mirzaei. I collaborate closely with Dr. Ping Zhang and his research group, as well as with Dr. Changchang Yin, Dr. Weidan Cao, and Dr. Pierre Giglio.

My research focuses on developing robust and interpretable learning frameworks for complex, real-world data. I have worked on longitudinal modeling of glioblastoma using follow-up MRI, multimodal representation learning for EEG-based source separation.

Broadly, I am interested in designing models that can effectively integrate heterogeneous signals across modalities and time, with the goal of enabling reliable, data-driven decision-making in high-stakes environments.

Research Interests

• Computer vision: image classification, segmentation, generation, enhancement, and recognition
• Multimodal learning: vision-language models and image captioning
• Medical AI: deep learning for MRI analysis and clinical prediction tasks

Current Highlights

• Deep learning benchmark study for glioblastoma follow-up MRI, currently under revision for submission
• EEG-based music source extraction using attention and temporal convolution models
• Publications spanning medical AI, multi-agent reinforcement learning, trading under uncertainty, and NLP

Education

• Ph.D. in Computer Science and Engineering, The Ohio State University, 2024-current
• M.S. in Computer Science and Engineering, The Ohio State University, 2024-2026
• B.S. (Hons) in Data Science, Hong Kong Baptist University, 2020-2024

Please feel free to reach out by email if you would like to discuss research, collaboration, or graduate opportunities.