Bio

Kiran Shiragur is a final year PhD student at Stanford, co-advised by Prof. Moses Charikar and Prof. Aaron Sidford. His research interests lie in the intersection of theoretical computer science, statistics, information theory and optimization. A major theme of his work involves building efficient algorithms for extracting information from limited data. Complementary to this theme, he also enjoy formulating new mathematical models and practical solutions for problems in the natural and social sciences, that lie beyond the range of traditional machinery.

RESEARCH AREA: Operations Research, Theoretical Computer Science

Contact

  • Academic
    shiragur@stanford.edu
    University - Student Department: Management Science and Engineering Position: Graduate

Additional Info

  • Mail Code: 4026

Links

All Publications

  • Reward Identification in Inverse Reinforcement Learning Kim, K., Garg, S., Shiragur, K., Ermon, S., Meila, M., Zhang, T. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2021

    View details for Web of Science ID 000683104605049

  • Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation Charikar, M., Shiragur, K., Sidford, A., Charikar, M., Cohen, E. ASSOC COMPUTING MACHINERY. 2019: 780–91

    View details for DOI 10.1145/3313276.3316398

    View details for Web of Science ID 000523199100070

  • A General Framework for Symmetric Property Estimation Charikar, M., Shiragur, K., Sidford, A., Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019

    View details for Web of Science ID 000535866904013