Lauren Wheelock

Lauren Wheelock is a Clinical Assistant Professor in the Faculty of Computing & Data Sciences at Boston University. She brings a multidisciplinary background spanning mathematical optimization, machine learning, and applied data science to both her teaching and research. She holds a BS in Mathematics from Yale University and a PhD in Operations Research from MIT, where her dissertation focused on optimization algorithms for matrix completion problems and natural language processing.

Lauren’s research sits at the intersection of optimization, machine learning, and real-world applications—from biological sequence engineering to the development of AI-powered tools for college admissions. She has worked across industry and academia, including roles in operations research-based consulting, machine learning-guided protein engineering for a gene therapy startup, and building educational AI platforms.

As an educator, Lauren is passionate about helping students build strong mathematical foundations and develop intuition for applying data science and machine learning methods. She focuses on adapting content and pedagogy to meet the evolving demands of the field, preparing students to thrive in both research and industry settings. She is especially interested in teaching the "art" of modeling—designing, applying, and interpreting models in complex, ambiguous scenarios.

Her teaching experience includes co-instructing data analytics courses for MBA students and working with K–12 learners through Cambridge Math Circle.

Research Interests:

• Optimization algorithms for data science and machine learning
• Machine learning for biological sequence engineering
• Language models: theory and applications
• Educational technology and AI

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