I have 5+ years of experience using data science, machine learning, and AI to solve complex problems. Using my background in software engineering and data analytics, I’ve lead multiple research projects end-to-end: from building data and ML pipelines to rigorously analyzing and communicating results. I’ve applied these skillsets to problems in cancer care and infectious disease, and I’ve presented the results of my research to public health departments, epidemiologists, and international machine learning conferences.

I recently completed my PhD in computer science at Cornell University, where I was advised by Jon Kleinberg. Prior to the PhD I was a software engineer at Google and earned bachelor’s and master’s degrees in computer science at Stanford. I love teaching, and during my graduate studies I served as a teaching assistant for 9 computer science courses, clarifying complex concepts from probability, AI, and algorithms for >200 students.

In the past, I played competitive ultimate frisbee at the collegiate, national, and international level, where I learned that I thrive on teams that support each other in achieving excellence.

Papers

Predicting drug response via transfer learning
Michela Meister, Christopher Tosh and Wesley Tansey
Machine Learning for Healthcare (ML4H) 2023, Findings Track [Paper] [Code]

Containing the spread of a contagion on a tree
Michela Meister and Jon Kleinberg
Autonomous Agents and Multi-Agent Systems (AAMAS) 2024 [Paper] [Talk]

Optimizing the order of actions in a model of contact tracing
Michela Meister and Jon Kleinberg
PNAS Nexus [Paper]

Learning with Comparison Feedback: Online Estimation of Sample Statistics
Michela Meister and Sloan Nietert
Algorithmic Learning Theory (ALT) 2021 [Paper]

Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels
Michela Meister, Tamás Sarlós, and David P. Woodruff
Advances in Neural Information Processing Systems (NeurIPS) 2019 [Paper]

A Data Prism: Semi-verified learning in the small-alpha regime
Michela Meister and Gregory Valiant
Conference on Learning Theory (COLT) 2018 [Paper]

Other Writing

Digital Security and Reproductive Rights: Lessons for Feminist Cyberlaw
Michela Meister and Karen Levy
Book chapter in Feminist Cyberlaw (UC Press, 2024)

Teaching

I served as a graduate teaching assistant for the following courses.

• Cornell: Networks, Choices and Consequences in Computing
• Stanford: Optimization and Algorithmic Paradigms; Probability for Computer Scientists; Mathematical Foundations of Computing; Mathematical Methods for Robotics, Vision, and Graphics