AI for biomedicine & scientific discovery
About Me
Hi, I am Jifeng Song, a fourth-year Ph.D. student in Electrical and Computer Engineering at the University of Pittsburgh and also a research assistant in the Cancer Virology Program at UPMC Hillman Cancer Center, co-advised by Prof. Yufei Huang and Prof. Zhi-Hong Mao. I received my B.E. in Electrical Engineering and Automation from Huazhong University of Science and Technology.
My current research focuses on post-training and efficient inference for multimodal large language models (MLLMs), with applications in scientific discovery and cancer research. I am particularly interested in scientific document understanding and multimodal knowledge discovery.
I am actively seeking internship opportunities starting in 2027. You can find my CV here.
News
- [09/2026] ๐ Paper published in Patterns: Unifying AI-assisted scientific discovery around exploration, hypothesis generation, and testing.
- [08/2026] ๐ Paper accepted to EMNLP Main: FigEx2: Visual-Conditioned Panel Detection and Captioning for Scientific Compound Figures.
- [05/2026] ๐ Paper accepted to MLSys: Attribution-based Sparse Activation in Large Language Models.
- [04/2026] New preprint: spatiAlytica.
- [01/2026] New preprint: Aligning Findings with Diagnosis.
- [08/2025] ๐ Paper accepted to EMNLP Findings: FigEx: Aligned Extraction of Scientific Figures and Captions.
- [06/2024] New preprint: Achieving Sparse Activation in Small Language Models.
Selected Publications
Full list† Equal contribution.
EMNLP 2026![]() | Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing |
MLSys 2026![]() | Proceedings of Machine Learning and Systems (MLSys) 2026 |
EMNLP 2025![]() | Findings of the Association for Computational Linguistics: EMNLP 2025 |
Patterns![]() | Patterns, 2026 |
bioRxiv![]() | bioRxiv preprint 2026 |





