Michelle Li
Assistant Professor at Alexander Twilight Academy
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolMichelle Li is a research-focused scientist and educator with eight years of experience bridging biomedical research and STEM outreach, currently a Research Fellow at Harvard Medical School and soon-to-be tenure-track Assistant Professor at Carnegie Mellon. She completed a PhD at Harvard after a BS from Stanford and has a strong track record of translational lab work, industry internships (Microsoft, Genentech), and long-term research roles across multiple Stanford labs. As founder and director of Reroot STEM and a lead teacher, she combines rigorous research with proven leadership in education and community engagement. Her background spans wet-lab expertise, computational research during a Microsoft internship, and curriculum development—an uncommon mix that positions her to translate complex science into teachable, impactful programs. Based in Boston, she is building an academic career that emphasizes mentorship, public-facing STEM initiatives, and interdisciplinary collaboration.
9 years of coding experience
7 years of employment as a software developer
High School Diploma International Baccalaureate (IB) Diploma, High School Diploma International Baccalaureate (IB) Diploma at Brooklyn Friends SchoolDoctor of Philosophy - PhD Biomedical Informatics, Doctor of Philosophy - PhD Biomedical Informatics at Harvard UniversityB.S. Mathematical and Computational Science, B.S. Mathematical and Computational Science at Stanford University
English, Chinese, Spanish
Github Skills (26)
proteins10
graph-representation-learning10
few-shot-learning9
knowledge-graph9
medicine9
deep-learning8
bioinformatics8
geometric-deep-learning7
biology7
cheminformatics7
chemistry7
ai6
drug-discovery6
datasets6
subgraph5
Programming languages (3)
Github contributions (5)
mims-harvard/PINNACLE
Jul 2023 - Feb 2025
Contextual AI models for single-cell protein biology
Contributions:1 PR, 79 pushes, 1 branch in 1 year 7 months
aicontext-awarecontextualgeometric-deep-learninggraph-neural-networks
mims-harvard/SHEPHERD
Nov 2022 - Mar 2023
SHEPHERD: Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases
Contributions:44 commits, 47 pushes, 2 comments in 4 months
few-shot-learningdeep-learningembeddingsgraph-neural-networksgraph-representation-learning
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