Natalie Collina

Natalie Collina is a fourth-year PhD student in computer science at the University of Pennsylvania, specializing in theoretical computer science.1 She is advised by professors Michael Kearns and Aaron Roth.1

Research Interests

Collina's research focuses on the intersection of algorithmic game theory and online learning.1 Specifically, she is interested in:

• Understanding algorithms for strategic settings with repeated interactions
• Studying the strategic properties of no-regret and no-swap-regret algorithms
• Exploring areas like repeated Stackelberg games, repeated contracting, and sequential online prediction

Academic Background

• Currently pursuing a PhD in Computer Science at the University of Pennsylvania (started in 2020)1
• Graduated summa cum laude from Princeton University in Fall 20191
  • Major in Computer Science
  • Minor in History and Diplomacy
  • Advised by Professor Matt Weinberg at Princeton

Professional Experience

Before starting her PhD, Collina worked for two years as a software engineer at Google.1 She has also completed internships at:

• Amazon Web Services (Software Engineering Intern, 2018)1

Achievements and Recognition

Collina has received several notable awards and recognitions:

• Recognized as one of MIT's Rising Stars in EECS (2024)1
• AWS AI ASSET Fellow (2023)1
• University of Pennsylvania Graduate Research Fellowship (2020)1
• NSF-GRFP Honorable Mention (2020)1
• Sigma Xi Book Award for Scientific Research (2019)1
• Outstanding Computer Science Senior Thesis Award, Princeton University (2019)1

Additional Activities

• Co-leads the University of Pennsylvania's weekly Theory Seminar1
• Has served as a subreviewer for various conferences including FAccT 2024, SODA 2024, and ITCS 20231

Natalie Collina's research is supported by AWS AI, and she has published papers in prestigious conferences such as EC (ACM Conference on Economics and Computation) and AAMAS (International Conference on Autonomous Agents and Multi-Agent Systems).1