Li Shen

Li Shen is a Professor in Neuroscience at Mount Sinai, leading the Shen Laboratory. The lab focuses on two major areas: machine learning applications to biomedical data science and large-scale next-generation sequencing (NGS) data analysis. His team has developed innovative tools like ngs.plot and diffReps for NGS data mining and differential analysis, respectively, and contributed to deep learning models for breast cancer detection and genome annotation.

• Current Role: Course Director for BDS 3002 – Machine Learning for Biomedical Data Science (2023–2024), continuing as lecturer from 2025 onward
• Research Collaborators: Mount Sinai (Eric Nestler, Scott Russo, Yasmin Hurd, etc.), University of Minnesota/ASU (Jonathan Gewirtz, Andrew Harris), and bioinformaticians like Aarthi Ramakrishnan

Dr. Shen’s research bridges machine learning with neuroscience and genomics. Key projects include Siamese networks for mammogram analysis, Transformer-based 3D chromatin prediction, and automated genome annotation. Software tools like GeneOverlap and NGS-Data-Charmer demonstrate his commitment to open-source bioinformatics platforms.

Scientific Contributions span top-tier journals (Nature, Science, Neuron) with over 30,000 NGS samples analyzed since 2009. His work on stress susceptibility mechanisms, HDAC6 inhibition for chronic pain, and neuroepigenetic studies on drug addiction reveals interdisciplinary depth.

Dr. Shen actively engages in teaching, emphasizing artificial neural networks, support vector machines, and deep learning. His lab website hosts educational resources, including a book on Mathematics for Machine Learning used in coursework.