Before coming to Berkeley, I received an A.B. and S.M. in computer science, math, and statistics at Harvard, where I was advised by Jelani Nelson. In the summer of 2020, I interned at Microsoft Research in the Machine Learning and Optimization Group.
Here's my CV and my contact info. * denotes equal contribution, α-β denotes alphabetical ordering)
- Performative Power
(α-β) Moritz Hardt, Meena Jagadeesan, and Celestine Mendler-Dünner.
- Regret Minimization with Performative Feedback
Meena Jagadeesan, Tijana Zrnic, and Celestine Mendler-Dünner.
ICML 2022. (Preliminary version at FORC 2022.)
- Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Meena Jagadeesan, Ilya Razenshteyn, and Suriya Gunasekar.
[arXiv] [talk at MIT]
- Individual Fairness in Advertising Auctions through Inverse Proportionality
(α-β) Shuchi Chawla and Meena Jagadeesan.
ITCS 2022. (Preliminary version at FORC 2021.)
[paper] [talk] [slides]
- Learning Equilibria in Matching Markets from Bandit Feedback
Meena Jagadeesan*, Alexander Wei*, Yixin Wang, Michael I. Jordan, and Jacob Steinhardt.
NeurIPS 2021. Spotlight Presentation (given to ~10% of accepted papers).
- Alternative Microfoundations for Strategic Classification
Meena Jagadeesan, Celestine Mendler-Dünner, and Moritz Hardt.
[paper] [slides] [poster]
- Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine
Subarna Chatterjee, Meena Jagadeesan, Wilson Qin, and Stratos Idreos.
- Multi-Category Fairness in Sponsored Search Auctions
Christina Ilvento*, Meena Jagadeesan*, and Shuchi Chawla.
ACM FAT* 2020. (Preliminary version at EC 2019 Workshop on Mechanism Design for Social Good.)
[paper] [slides] [talk]
- Individual Fairness in Pipelines
(α-β) Cynthia Dwork, Christina Ilvento, and Meena Jagadeesan.
[paper] [full version] [slides from reading group]
- Understanding Sparse JL for Feature Hashing
NeurIPS 2019. Oral Presentation (given to ~3% of accepted papers).
[paper] [full version] [talk] [slides] [coverage]
- Simple Analysis of Sparse, Sign-Consistent JL
[paper] [full version] [slides]
- Varying the Number of Signals in Matching Markets
Meena Jagadeesan* and Alexander Wei*.
WINE 2018. (Preliminary version at EC 2018 Workshop on Frontiers of Market Design.)
[paper] [full version]
- Dyson's partition ranks and their multiplicative extensions
(α-β) Elaine Hou and Meena Jagadeesan.
The Ramanujan Journal, 2018.
- Mobius Polynomials of Face Posets of Convex Polytopes
Meena Jagadeesan and Susan Durst.
Communications in Algebra, 2016.
- From Worst-Case to Average-Case Analysis: Accurate Latency Predictions for Key-Value Storage Engines
Meena Jagadeesan* and Garrett Tanzer*.
SIGMOD 2020 (2-Page Extended Abstract). Winner of SIGMOD SRC.
- The Performance of Johnson-Lindenstrauss Transforms: Beyond the Classical Framework
Undergraduate thesis, 2020. Awarded Hoopes Prize.
- Open Philanthropy AI Fellowship (2021-2025)
- PD Soros Fellowship for New Americans (2020-2022)
- Berkeley Fellowship (2020-2023)
- CRA Outstanding Undergraduate Researcher Award (2020)
- Siebel Scholar (2019-2020)
- Barry Goldwater Scholar (2018-2020)
- Intel STS 2nd Place Prize in Basic Research (2016)
[Twitter] [Google Scholar] [LinkedIn]