| CARVIEW |
Select Language
HTTP/1.1 200 OK
Date: Sun, 28 Dec 2025 17:09:45 GMT
Server: Apache/2.4.37 (Red Hat Enterprise Linux) OpenSSL/1.1.1k mod_wsgi/4.6.4 Python/3.6
Last-Modified: Tue, 10 Dec 2024 18:26:14 GMT
ETag: "1211b-628ee9dc7da88-gzip"
Accept-Ranges: bytes
Vary: Accept-Encoding
Content-Encoding: gzip
Content-Length: 8255
Content-Type: text/html
FODSI
-
8 RESEARCH THEMESFOUNDATIONS OF DATA SCIENCE
INSTITUTEWe bring together a large and diverse team of researchers and educators from UC Berkeley, MIT, Boston University, Bryn Mawr College, Harvard University, Howard University, and Northeastern University, with the aim of advancing the theoretical foundations for the field of data science.
FODSI
Computational Complexity of Statistical Inference
Explore computational vs. statistical tradeoffs in estimation problems.
Networks and Graphical Models
Model and predict complex interactions.
Geometric Aspects of Sampling and Optimization
Develop a combined perspective that leads to simultaneous progress on both optimization and sampling.
Machine Learning for Algoritms
Leverage machine learning to improve the performance of classical algorithms.
Sketching, Sampling, and Sublinear-Time Algorithms
Develop techniques that provide tradeoffs between algorithmic efficiency quality of approximation or statistical guarantees for the downstream applications.
Economics and Learning
Develop the theoretical and algorithmic foundations of systems with strategic agents.
Reinforcement Learning
Develop RL methods with rigorous guarantees.
Causal Inference
Extract causal information from observational data.