Projects
Ongoing
Large Language Models and Data Discovery
(2022-present)
Quasi-stable Coloring for Graph Compression
(2020-present)
Discovering graph-theoretic techniques to accelerate data science tasks.
Completed
Mining Robust Default Configurations for Resource-constrained AutoML
(2021-2022, at Microsoft Research)
Accelerating automatic selection of models and parameters using data dependent defaults.
Causal Relational Learning
(2019–2020)
Finding cause-and-effect in complex relational domains.
ReviewData
Dataset of academic peer-review, including rejected submissions.