Jun-En Ding
Jun-En Ding
Second-Year Ph.D. Student
Stevens institute of Technology 🇺🇸 NJ
Email: jding17@stevens.edu
Second-Year Ph.D. Student
Stevens institute of Technology 🇺🇸 NJ
Email: jding17@stevens.edu
Research Interests
- Hi, I am a Ph.D. student at Stevens Institute of Technology, advised by Prof. Feng Liu.
- My research interests involve the application of machine learning to medical images and clinical data. Specifically, my research areas include AI for computational neuroscience, EHR data, multimodal learning, and graph representation learning.
- [Grant]
I am also a research engineer currently leading an AI research team in collaboration with Taiwan's Far Eastern Memorial Hospital (FEMH). Our research is conducted under the collaborate with PI Dr. Fang-Ming Hung, alongside Prof. Chen Ling from National Yang Ming Chiao Tung University and Prof. Wen-Chih Peng from the Department of Computer Science. I am grateful to have secured funding and research support for this AI research project.
- We always welcome potential collaborations with our computational neuroscience lab and more academic connections!
Publications
- [05/2025]: One paper is accepted to ACL'25 Industry Track (acceptance rate: 25.1%, Average Rating: 7.00 [Min: 6, Max: 8]) [New!!]
- [05/2025]: One paper is accepted to ICML'25 (acceptance rate: 26.9%, 3,260/12,107) [New!!]
- [03/2025]: One paper is accepted to JMIR (IF:5.8) [New!!]
- [02/2025]: One paper is accepted to AAAI'25 AISI [New!!]
- [09/2024]: One paper is accepted to IEEE JBHI (IF:7.021)
- [08/2024]: One paper is accepted to Scientific Reports - Nature (IF:4.6)
- [07/2024]: One paper is accepted to CIKM'24 (Short paper, Acceptance Rate: 27%)
- [07/2024]: One paper is accepted to CIKM'24 (Demo paper)
- [04/2024]: One paper is accepted to CVPR'24 MMFM Workshop (Poster)
- [02/2024]: One paper is accepted to ISBI'24 (Oral presentation)
- [02/2023]: One paper is accepted to AAAI'23 (Student abstract)
- [08/2022]: One paper is accepted to JFMA (Correspondence paper)
- [05/2021]: One paper is accepted to MIUA 2021 (Oral paper)
- [04/2021]: One paper is accepted to SIGIR 2021 (Short paper)
MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation
Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding, Chun-Chieh Liao, Pengfei Hu, Xiaoxue Han, Chih-Ho Hsu, Dongsheng Luo, Wen-Chih Peng, Feng Liu, Fang-Ming Hung, Chenwei Wu
The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025)
NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
Jun-En Ding, Dongsheng Luo, Anna Zilverstand, Feng Liu
International Conference on Machine Learning (ICML 2025) [Code]
Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation
Yaxi Luo, Meng Jiao, Neel Fotedar, Jun-En Ding, Ioannis Karakis, Vikram R Rao, Melissa Asmar, Xiaochen Xian, Orwa Aboud, Yuxin Wen, Jack J Lin, Fang-Ming Hung, Hai Sun, Felix Rosenow, Feng Liu
Journal of Medical Internet Research (JMIR)
Spatial Craving Patterns in Marijuana Users:
Insights from fMRI Brain Connectivity Analysis
with High-Order Graph Attention Neural
Networks
Jun-En Ding, Shihao Yang, Anna Zilverstand, Kaustubh R. Kulkarni, Xiaosi Gu, and Feng Liu
Journal of Biomedical and Health Informatics (JBHI)
MEDFuse: Multimodal EHR Data Fusion with Masked Lab-Test Modeling and Large Language Models
Thao Minh Nguyen Phan, Cong-Tinh Dao, Chenwei Wu, Jian-Zhe Wang, Shun Liu, Jun-En Ding, David Restrepo, Feng Liu, Fang-Ming Hung, Wen-Chih Peng
33rd ACM International Conference on
Information and Knowledge Management (CIKM 2024)
Large Language Multimodal Models for New-Onset Type 2 Diabetes Prediction using Five-Year Cohort Electronic Health Records
Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng, Jian-Zhe Wang, Chun-Cheng Chug, Min-Chen Hsieh, Yun-Chien Tseng, Ling Chen, Dongsheng Luo, Chi-Te Wang, and Fang-Ming Hung
Parkinson's Disease Classification Using Contrastive Graph Cross-View Learning with Multimodal Fusion of SPECT Images and Clinical Features
Jun-En Ding, Chien-Chin Hsu, Feng Liu
International Symposium on Biomedical Imaging (ISBI 2024)
Sequential graph attention learning for predicting dynamic stock trends
Tzu-Ya Lai, Wen Jung Cheng, Jun-En Ding
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)
Hospital transfer risk scoring system for a Taiwan COVID-19 medicalized hotel based on graph convolutional networks
Fang-Ming Hung, Chih-Ho Hsu, Jun-En Ding, Ling Chen
Journal of the Formosan Medical Association (JFMA 2021)
https://www.sciencedirect.com/science/article/pii/S0929664622003230
(Covid-19 AI scoring system : http://med-ai-demo.lab.nycu.edu.tw/)
Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers
Jun-En Ding, Chi-Hsiang Chu, Mong-Na Lo Huang, and Chien-Ching Hsu
The 25th UK Conference on Medical Image Understanding and Analysis (MIUA 2021)
LSTPR: Graph-based Matrix Factorization with Long Short-term Preference Ranking
Chih-Hen Lee, Chih-Ming Chen, Jun-En Ding, Jing-Kai Lou, Ming-Feng Tsai and Chuan-Ju Wang
The 44th International ACM SIGIR Conference
on Research and Development in Information Retrieval (SIGIR 2021)CVPR 2024
IEEE International Symposium on Biomedical Imaging
The 37th AAAI Conference On Artificial Intelligence
Washington DC
The 28th Joint National Sun Yat-sen University and National University of Kaohsiung Workshop on Statistics
Research Descriptions
Far Eastern Memorial Hospital-Medical Research Department Clerk
Development of a platform for predicting disease risk based on deep learning from electronic medical records.
111/03-
E.SUN bank recommendation system
110/01-110/12
Intern
108/6-108/12
Asset Prices Effect of Monetary Policy and its Sectoral Difference
Work Experience
Research Assistant
Institute of Hospital and Health Care Administration
Our lab develops AI algorithms for CT scans and MRI images in collaboration with Far Eastern Hospital.
Research Assistant
Work on Research Center for Information Technology Innovation
Intern
Established in June 2016, Wellgen Medical Co., Ltd. has team members from academic, business, medical and technological fields. We have professional background, management expertise, and great execution. We focus on identification and analysis of medical microscopic images for disease detections. Using our revolutionary automated microscope, we are able to scan microscopic images at client side and analyze on the server by cloud computing using our artificial intelligence (AI) algorithm and big data analysis. Our automated microscope system and cloud computing service can improve diagnostic sensitivity and clinical outcome.
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