Curriculum Vitae
Jane Researcher · Assistant Professor · Computational Medicine
I am a computational researcher and faculty member working at the intersection of machine learning, causal inference, and health informatics. My goal is to develop rigorous methods that make AI systems safer, fairer, and more interpretable in high-stakes clinical and public-health settings.
Work Experience
Fictional University School of Medicine - Boston, MA
Leading the Computational Medicine Lab. Research focuses on federated learning, causal inference in EHR data, and AI safety for clinical decision support. Supervising 3 PhD students and 1 postdoctoral fellow.
- Awarded NIH R01 grant ($1.2M) on privacy-preserving machine learning in multi-site health networks
- Developed and teach COMP 712 (Graduate Statistical Learning) and COMP 850 (Causal Inference for Health Data)
- Mentoring 3 PhD students and 1 postdoc; committee member for 5 additional students
Harvard T.H. Chan School of Public Health - Cambridge, MA
Researched machine learning methods for causal effect estimation in large observational health datasets. Collaborated with clinical teams at BIDMC on sepsis prediction and antibiotic stewardship projects.
- Published 8 peer-reviewed papers; 4 as first author
- Developed the
causehealthopen-source Python library (800+ GitHub stars) - Co-led weekly methods seminar series in the Department of Epidemiology
Education
Ph.D. in Computer Science (Machine Learning Track)
Dissertation: Scalable Probabilistic Inference for Heterogeneous Health Networks
Advisor: Prof. Hypothetical Advisor
GPA: 4.0 · NSF Graduate Research Fellowship recipient