GenAI development on conversational chatbot
I worked as a GenAI developer and helped develop a LLM-driven conversational agent to simulate patient-doctor encounters for medical students to practice and refine their clinical communication skills.
I worked as a GenAI developer and helped develop a LLM-driven conversational agent to simulate patient-doctor encounters for medical students to practice and refine their clinical communication skills.
I built an analysis pipeline for multimodel single-cell sequencing data for Follicular Lymphoma, analyzed the results, and published a paper on a peer-reviewed journal.
I built an analysis pipeline for Fludigm single-cell sequencing data, analyzed the results, and published a paper on a peer-reviewed journal.
I benchmarked deep-learning-based methods (Cellpose, Mesmer) on spatial transcriptome IF images and set a good foundation for downstream analysis.
I developed a deep-learning-based approach based on U-Net as a noninvasive technique to provide information about bony changes and disease changing in CT images for temporomandibular joint osteoarthritis.
I designed a deep-learning-based approach based on U-Net for automatic brain glioma segmentation of multimodal MRI scans with high efficiency and accuracy and achieved the 4th place in the 2018 Multimodal Brain Tumor Segmentation Challenge.
Published in Computational and Structural Biotechnology Journal, 2020
Published in Radiology: Artificial Intelligence, 2020
Published in Journal of Clinical Oncology, 2024
Published in Cancer Cell, 2024
Published in Cancer Discovery, 2026
Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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