Anna Karlin — LLMpedia

Anna Karlin
Name	Anna Karlin
Birth date	20th century
Fields	Computer science
Workplaces	University of Washington, Microsoft Research
Alma mater	Massachusetts Institute of Technology, Princeton University
Doctoral advisor	Richard Karp
Known for	Algorithms, randomized algorithms, online algorithms, algorithmic game theory
Awards	Fellow of the Association for Computing Machinery, Guggenheim Fellowship

Contents

Anna Karlin is an American computer scientist recognized for foundational work in randomized algorithms, online algorithms, and algorithmic game theory. She is a professor at the University of Washington and has affiliations with Microsoft Research, contributing to advances that intersect with Donald Knuth's algorithmic legacy, John Nash's game theory, and modern complexity theory associated with Leonid Levin and Stephen Cook. Her research connects to topics investigated at institutions such as MIT, Princeton University, and centers including the Simons Institute for the Theory of Computing.

Early life and education

Karlin completed undergraduate and graduate training that tied her to major centers of computer science research. She studied at Massachusetts Institute of Technology and earned a Ph.D. from Princeton University under the supervision of Richard Karp, placing her academic lineage alongside scholars from Bell Labs, IBM Research, and AT&T Bell Laboratories. During this period she engaged with the research communities around ACM, SIAM, and the International Colloquium on Automata, Languages and Programming.

Karlin's career spans appointments and collaborations at leading research organizations. She holds a faculty position at the University of Washington and has worked at Microsoft Research, participating in programs with the National Science Foundation, the Simons Foundation, and conferences like STOC and FOCS. Her work draws on methods pioneered by figures such as Michael Rabin, Leslie Valiant, Richard Karp, Ronald Rivest, and Robert Tarjan. Karlin's research agenda has addressed randomized algorithms related to Markov chain Monte Carlo techniques, adversarial analysis related to Karp–Sipser algorithm-style matching, and online problems connected to the k-server problem and the paging problem.

Karlin has produced influential results in randomized and online algorithm design, including competitive analysis frameworks connected to work by Sleator and Tarjan, and algorithmic mechanism design that builds on Vickrey and Clarke-style auction theory. Major recognitions include fellowship in the Association for Computing Machinery and awards such as a Guggenheim Fellowship. Her theoretical contributions relate to complexity topics advanced by Andrew Yao and Shimon Even, and connect to applications explored at Google Research, Amazon Web Services, and academic labs at Stanford University and UC Berkeley.

As a professor at the University of Washington, Karlin has supervised students who have gone on to positions at institutions including MIT, Princeton University, Harvard University, Columbia University, Cornell University, University of California, Berkeley, and research labs such as Microsoft Research and Google Research. Her teaching involves courses that parallel material from textbooks by Jon Kleinberg, Eva Tardos, Thomas Cormen, and Sanjoy Dasgupta, and she has contributed to curricula discussed at conferences like SIGCSE and workshops sponsored by the National Science Foundation.

Karlin's publications have appeared in proceedings of STOC, FOCS, SODA, and journals such as the Journal of the ACM and the SIAM Journal on Computing. She has collaborated with researchers including Yuval Peres, Éva Tardos, Avi Wigderson, Richard Karp, Noam Nisan, Ariel Procaccia, and Jason D. Hartline. Notable papers address themes related to randomized rounding, primal-dual methods, online matching, and algorithmic game theory, intersecting research directions pursued at Bell Labs, IBM Research, and academic groups at Carnegie Mellon University.

Karlin has served on program committees and steering committees for conferences such as STOC, FOCS, SODA, and EC (Symposium on Economics and Computation). She has reviewed for agencies including the National Science Foundation and the Simons Foundation, and held leadership roles in societies like the Association for Computing Machinery and the Society for Industrial and Applied Mathematics. Her public-facing engagement includes invited lectures at venues such as the Institute for Advanced Study, the Simons Institute for the Theory of Computing, and workshops at Microsoft Research and Google Research.