I recently graduated summa cum laude with B.S. in Computer Science from Washington University. During my undergraduate studies, I conducted research at the AI for Health Institute (AIHealth) , led by Prof. Chenyang Lu, and collaborated with Prof. Joanna Abraham at WashU Medicine. I was fortunate to work closely with Prof. Yu Li at Chinese University of Hong Kong for several projects on AI4BIO. And I worked in Prof. Sheng Wang’s group at the University of Washington.
Research Interests
- Computational Biology and Drug Discovery
- LLMs & Foundation Models in Biology (protein, genome, etc.)
🔥 News
- 2024.12 “A Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients” accepted by Journal of the American Medical Informatics Association (JAMIA)
- 2024.5 Received B.S. in Computer Science with Summa Cum Laude (GPA 3.98/4.00)
- 2024.4 Received Outstanding Senior Award at WashU McKelvey School of Engineering
- 2023.12 “Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model” accepted by Nature Computational Science
📝 Selected Publications & Manuscripts (first/co-first authorship)
Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model
Junbo Shen*, Qinze Yu*, Shenyang Chen*, Qingxiong Tan, Jingchen Li, Yu Li#
Nature Computational Science, 2023. [Paper] [Code]A Novel Generative Multi-Task Representation Learning Approach for Predicting Postoperative Complications in Cardiac Surgery Patients
Junbo Shen, Bing Xue, Thomas Kannampallil, Chenyang Lu, Joanna Abraham#
Journal of the American Medical Informatics Association (JAMIA), 2024. [Paper] [Preprint] [Code]Deep Learning Predicts Synergy Effect of Antibacterial Drug Combinations
Co-first Author, In Preparation, 2024+. [Paper]
(* equal contribution)
🎖 Research Experience
Unbiased Signal Peptide Prediction with Deep Protein Language Model
Supervised by Prof. Yu Li
2022.06 - 2023.12
- Developed USPNet, a deep protein language model for predicting signal peptides, achieving state-of-the-art performance.
- Developed the pipeline using USPNet to screen and identify 347 novel signal peptides from metagenomic data.
Representation Learning for High-Risk Surgery Outcome Prediction
Supervised by Prof. Joanna Abraham & Prof. Chenyang Lu
2023.08 - Present
- Introduced surgVAE, a novel VAE-based framework for multi-outcome predictions in cardiac surgery.
Deep Learning Predicts Synergy Effect of Antibacterial Drug Combinations
Supervised by Prof. Yu Li
2023.09 - Present
- Predicting the synergy effects of drug combinations on bacterial strains leveraging Genomic LLMs, GNNs for drug SMILEs, etc., for better interpretability.
AI for Computational Pathology
Supervised by Prof. Sheng Wang
2024.06 - Present
- Working on pretraining foundation models for Whole Slide Images (WSIs) in pathology, and medical imaging.
Deep learning in broadband spectrum reconstruction (Submitted to KDD 2025)
Supervised by Prof. Chenyang Lu
2023.02 - 2024.01
- Optical attention-based conv2seq architecture for spectrum reconstruction, achieving near-perfect spectral imaging recovery from crystal responses. [Code]
Antimicrobial resistance prediction
Supervised by Prof. Yu Li
2024.10 - Present
🎓 Education
Washington University in St. Louis, MO, USA
B.S. in Computer Science, Summa Cum Laude
2022.08 - 2024.05
- Selected Honors: Outstanding Senior Award (Awarded to 2 seniors at WashU CSE dept.), Dean’s Lists, Tau Beta Pi Selected Member
Chinese University of Hong Kong, HK, China
Major in Computer Science, ELITE Stream (Transferred to Washington University)
2020.09 - 2022.06
- Selected Honors: Academic Excellence Scholarship (Top Year GPA at each dept.), ELITE Stream Scholarship, Dean’s List (Top 10%)