Laura E. Brown

Laura E. Brown is Associate Professor of Computer Science at Michigan Technological University, also serving as Associate Dean for Data Science Initiatives in the College of Computing and Director of the university’s M.S. and B.S. Data Science programs. She is a core member of the Institute of Computing and Cybersystems (ICC), the Ecosystem Science Center (ESC), and the Center for Agile Interconnected Microgrids (AIM).

Education

• Ph.D., Biomedical Informatics — Vanderbilt University
• M.S., Biomedical Informatics — Vanderbilt University
• M.S.E., Electrical Engineering & Computer Science — University of Michigan
• B.S., Engineering — Swarthmore College

Research Interests

Laura’s scholarship spans artificial intelligence, machine learning, and data science, with theoretical advances tightly coupled to high-impact applications in energy systems (microgrids, power analytics), health and biomedical informatics, and computer science pedagogy. She is passionate about translating algorithmic innovations into real-world deployments that improve sustainability, clinical decision-making, and equitable education.

A second major strand of her work centers on educational innovation: developing automated code-critiquing systems, studying their influence on student self-efficacy—especially for women in engineering—and leading campus-wide initiatives such as Carpentries workshops and ICPC programming competitions.

Publication Trends

Brown’s 2018–2025 publication record reveals sustained productivity in three overlapping domains: (1) AI/ML methodology—hardware prefetching, neural architectures, transfer learning; (2) energy analytics—forecasting coincident peak load, solar irradiance, battery degradation; and (3) computing education—automated feedback, gender studies, curriculum design. Recent emphasis has shifted toward educational technology, with multiple 2023–2025 papers on code critiquers and their psychological impact.

Research Funding & Grants

• NSF Revolution through Evolution: $699 K, PI (2015–2019)
• DoD Distributed Agent-Based Management of Agile Microgrids: ~$1 M, co-PI (2013–2017)
• NSF Adaptive Memory Resource Management in a Data Center: $299 K, PI (2014–2017)
• NSF Microdevice for Rapid Blood Typing without Reagents: $300 K, co-PI (2016–2019)
• Google Explore CS Research Workshops: $18 K PI / $35 K co-PI (2018–2020)

Student Engagement & Leadership

Laura co-advises Women in Computing Science (WiCS), organizes Michigan Tech’s ICPC regional site, and has led Google-sponsored undergraduate research workshops, Summer Youth Programs, and multiple Carpentries training events.