Welcome!
Hi there! I’m Jinglin Jian (简靖琳), a recent master graduate from UIUC. I’m thrilled to have been admitted to the PhD program at Scripps Research Institute by the beautiful ocean 🏖️ at San Diego, CA. Since 2023, I studied at the School of Information Sciences at UIUC, where I had the opportunity to work with Professor Haohan Wang. Previously, I received a bachelor’s degree in a computer-related field from Beijing Normal University, where I contributed as a research assistant in Professor Jingjing Zhang’s lab. Additionaly, out of personal interest, I also earned a second bachelor’s 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.
"Which Animal Would You Like to See on Your Flashcards?" Designing Visual Aids Together with Kids Using GIMs
Yiqi Xiao and Jinglin Jian
Visual aids enhance children’s learning. Educational theories emphasize student agency. We developed a platform based on image generative models, specifically tailored for children with autism.
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.
