Emily Ryu

Emily Ryu

(she/her/hers)

CS @ Cornell University

Hello!

I’m a rising third-year PhD student in Computer Science at Cornell University. I’m very fortunate to be advised by Prof. Éva Tardos and Prof. Jon Kleinberg, and be supported by the NSF GRFP. My research interests span algorithmic game theory, combinatorial optimization, and networks, particularly with more realistic models of behavioral and cognitive constraints. Recently, I’ve been thinking about matching markets and recommender systems.

Previously, I graduated from Princeton University with an A.B. in Chemistry and minors in Applied Math and Computer Science, where I worked with Prof. Matt Weinberg on Bayesian auction design for multi-item revenue maximization. I also wrote my senior thesis in physical organic chemistry under the supervision of Prof. Robert Knowles.

Non-academic interests (many starting with a C and supported by images): caffeine, cats, colouring-of-hair, crafting, dance, yoga

CV (updated Jun 2023)

Interests
  • Algorithmic game theory
  • Mechanism design
  • Combinatorial optimization
  • Networks
Education

  • PhD in Computer Science, present

    Cornell University

  • A.B. in Chemistry with minors in Applied Math & Computer Science, 2017-2021

    Princeton University

Papers

Jon Kleinberg, Emily Ryu, Eva Tardos
February 2023 arXiv preprint
Calibrated Recommendations for Users with Decaying Attention

We study calibrated recommendations for users whose attention decays over the course of a ranked list, meaning that not all recommended items receive equal consideration. For a distributional model of genres, we extend tools from submodular optimization to provide a $(1-1/e)$-approximation algorithm to calibration. For a discrete model of genres, we show that the natural greedy algorithm is a $2/3$-approximation. Our work thus addresses the problem of capturing ordering effects due to decaying attention, allowing for the extension of near-optimal calibration from recommendation sets to recommendation lists.
(This paper incorporates and supersedes our earlier paper on ordered submodularity.)

PDF Cite DOI
Emily Ryu, Harry H. Xia, Grace L. Guo, Lanjing Zhang
February 2022 Am J Transl Res
Multivariable-adjusted trends in mortality due to alcoholic liver disease among adults in the United States, from 1999-2017

We provide the first multivariable analysis of trends in mortality due to alcoholic liver disease (ALD) among U.S. adults for 1999-2017, which previously have only been analyzed using univariate models. We use multivariable piecewise log-linear models to show an upward trend in multivariable-adjusted, age-standardized ALD mortality without significant differences by sex, race, age, or urbanization, particularly in the ALD subtypes of alcoholic fatty liver, alcoholic hepatitis, and alcoholic cirrhosis.
PDF Cite

Teaching

Cornell University

Princeton University

Contact

  • eryu AT cs DOT cornell DOT edu
  • 324 Gates Hall, Ithaca, NY 14853