Teams at Harvard Business School

Manages interdisciplinary AI research projects spanning model evaluation, interpretability, research infrastructure, technology policy, trust and safety, and AI accountability. Coordinates collaborators, workflows, deliverables, grants, publications, and stakeholder events. Supervises junior researchers and supports technical and policy-oriented research outputs, including academic papers, policy briefs, essays, and presentations. The role also requires machine learning experimentation on GPU clusters, research reproducibility, proposal development, and engagement with policymakers, industry, academia, and civil society.

Acquires and develops 15–20 education-focused books annually, including soliciting and evaluating proposals, commissioning titles, managing peer review, presenting proposals to an advisory board, and guiding authors from contract through publication. Maintains publishing lists, identifies new areas, collaborates with production, marketing, and sales teams, and manages interns and freelance support.

Leads data science, software development, and technical product work for interdisciplinary research on data centers and AI infrastructure. Designs statistical, machine-learning, and geospatial analyses; develops scalable pipelines, databases, APIs, research software, and decision-support tools; co-leads studies through peer-reviewed publication; and translates research into technical products. Coordinates contributors, mentors junior researchers, ensures reproducibility and data governance, and communicates findings to academic, policy, industry, and public audiences.