About Me

I'm an Assistant Professor of Information Science at Cornell University (and a field faculty member of the Computer Science department). My research interests lie broadly at the intersection of economics and computer science, focusing on algorithmic fairness. My projects apply computational methods, such as machine learning and causal inference, to study societal inequities in domains including public services, online platforms, and public health. I am regularly quoted as an expert on disparities in automated speech-to-text systems.

Previously, I was a postdoc at Microsoft Research New England in the Machine Learning and Statistics group. Before that, I received my PhD from Stanford's Institute for Computational & Mathematical Engineering under the guidance of my reading committee: Susan Athey, Sharad Goel, and Hal Varian. I am the recipient of several NSF awards, and was recognized for the Forbes 30 Under 30 in Science.

My formal bio for talks is available here, and headshot here. You can reach me at: koenecke at cornell.edu

Teaching & CV

At Cornell, I have co-developed and taught a range of Information Science / Computer Science classes, including large undergraduate classes like Introduction to Data Science (Fall '22, Fall '23, Fall '24), and smaller upper-level courses including: Designing Fair Algorithms (Spring '24), and Data Science for Global Development (Spring '23).

These courses are a reflection of the academic research communities in which I am active (such as Fairness, Accountability, and Transparency [FAccT] and Computational Social Science [IC2S2]), as well as the interdisciplinary nature of Information Science (including my own research, involving collaborations across academia, big tech, non-profits, and government offices). I am honored to be the recipient of a Cornell CIS Teaching and Advising Excellence award in 2024, and a Cornell DEIB Faculty of the Year award in 2024.

Curriculum Vitae available here.

Media

My media tip sheet commentary is searchable here; I can be contacted for comment via the Cornell Media Relations Office, or via email.

Selected News Coverage 🗞️

Podcast Appearances 🎧

Selected Publications

More papers can be found on Google Scholar.

Fairness in Automated Speech Recognition 🎤

Fairness in Algorithm-Assisted Decision-Making and Policy ⚖️

Causal Inference Methods & Public Health 🧪

Written Guides for General Audiences 👥