Welcome!
Email: jjian [at] scripps [dot] edu
Hi there! I’m Jinglin Jian (简靖琳), a PhD student at The Scripps Research Institute by the beautiful ocean 🏖️ at San Diego, CA. I’m deeply grateful to be supported by the Kellogg Fellowship, a three-year endowed award generously funded by the Kellogg family and The ALSAM Foundation. I received my master degree from the School of Information Sciences at the University of Illinois at Urbana-Champaign, where I had the opportunity to work close with Professor Qingyun Wang, Professor Haohan Wang, and Professor Ge Liu. Previously, I studied at Beijing Normal University, with a dual B.Econ. degree in Economics from Peking University.
Publications and Conferences
Patient Outcome Predictions via A Multimodal Lan- guage Model for Electronic Health Records
Zihan Li, Jinglin Jian, Chundian Li, Jinxia Yao, Jin Chen, Yang Zhang
Early prediction of mortality risk and hospital length of stay is critical. We propose a multimodal framework that integrates full-text clinical note embeddings and time-stamped physiological data to jointly model patient outcomes.
Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data
Haoyang Liu, Yijiang Li, Jinglin Jian, Yuxuan Cheng, Jianrong Lu, Shuyi Guo, Jinglei Zhu, Mianchen Zhang, Miantong Zhang, Haohan Wang
ML can discover disease-predictive genes from gene expression data. We introduced the Team of AI-made Scientists (TAIS), a LLM-based framework for automatic streamlining ML analysis. TAIS consists of simulated roles, including a project manager, data engineer, and domain expert.
Selected Projects
The Impact of Productive Failure on Learning Performance and Cognitive Load: Using Hypervideo to Facilitate Online Interactions
Xiaojie Niu, Jingjing Zhang, Kate M. Xu, Xuan Wang
Productive failure is an instructional approach that uses students’ cognitive conflicts to enhance their learning. This experimental study investigated the effect of productive failure in a hypervideo environment.
