Scholar
Mohit Gurumukhani
Google Scholar ID: Wy3qqusAAAAJ
Cornell University
Citations & Impact
Citations
30
H-index
3
i10-index
1
Publications
10
Co-authors
8
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Papers: 'Lower Bounds for Leader Election and Collective Coin Flipping, Revisited', 'Condensing and Extracting Against Online Adversaries', 'Two-Sided Lossless Expanders in the Unbalanced Setting', 'On Extremal Properties of k-CNF: Capturing Threshold Functions', 'Local Enumeration: The Not-All-Equal Case' (STACS 2025), 'On the Existence of Seedless Condensers: Exploring the Terrain' (FOCS 2024), 'Local Enumeration and Majority Lower Bounds' (CCC 2024), 'Extractors for Polynomial Sources over F_2' (ITCS 2024), 'The Fine-Grained Complexity of Multi-Dimensional Ordering Properties' (Algorithmica, 2022).
Research Experience
- Teaching Assistant: Theory of Computing (Fall 2023, Cornell), Introduction to Analysis of Algorithms (Fall 2022, Spring 2023, and Spring 2024, Cornell), Foundations of Responsible Machine Learning (Fall 2024, Cornell); Discrete Math for CS (Winter 2021, UC San Diego), Design and Analysis of Algorithms (Spring 2020, UC San Diego), Mathematics for Algorithms and Systems Analysis (Fall 2019, UC San Diego), Theory of Computation (Winter 2019, UC San Diego), Computer Organization and Assembly (Spring 2018, UC San Diego).
Education
- PhD: Department of Computer Science, Cornell University, Advisor: Eshan Chattopadhyay; Undergraduate: UC San Diego, Collaborators: Russell Impagliazzo and Ramamohan Paturi.
Background
- Research Interests: Theoretical Computer Science, specifically computational complexity and pseudorandomness.
