Grants per year
Personal profile
Research Interests
The aim of my research is to introduce new core techniques and design general principles for developing and analyzing algorithms that work in theory and practice. My research interests include approximation algorithms, beyond worst-case analysis, and applications of high-dimension geometry in computer science.
Education/Academic qualification
Mechanics and Mathematics, Lomonosov Moscow State University
Computer Science, PhD, Princeton University
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Grants
- 2 Active
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Collaborative Research: AF: Medium: Design and Analysis of Models and Algorithms for Real-life Problems
7/1/20 → 6/30/24
Project: Research project
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HDR TRIPODS: Collaborative Research: Institute for Data, Econometrics, Algorithms and Learning .
Auerbach, E. J., Berry, R. A., Canay, I. A., Guo, D., Hartline, J. D., Makarychev, K., Vijayaraghavan, A., Wang, Z., Khuller, S. & Horowitz, J. L.
9/15/19 → 8/31/22
Project: Research project
Research Output
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Certified algorithms: Worst-case analysis and beyond
Makarychev, K. & Makarychev, Y., Jan 2020, 11th Innovations in Theoretical Computer Science Conference, ITCS 2020. Vidick, T. (ed.). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 49. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 151).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Correlation clustering with local objectives
Kalhan, S., Makarychev, K. & Zhou, T., 2019, In: Advances in Neural Information Processing Systems. 32Research output: Contribution to journal › Conference article › peer-review
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DNA assembly for nanopore data storage readout
Lopez, R., Chen, Y. J., Dumas Ang, S., Yekhanin, S., Makarychev, K., Racz, M. Z., Seelig, G., Strauss, K. & Ceze, L., Dec 1 2019, In: Nature communications. 10, 1, 2933.Research output: Contribution to journal › Article › peer-review
Open Access11 Scopus citations -
Performance of Johnson–Lindenstrauss transform for k-means and k-medians clustering
Makarychev, K., Makarychev, Y. & Razenshteyn, I., Jun 23 2019, STOC 2019 - Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing. Charikar, M. & Cohen, E. (eds.). Association for Computing Machinery, p. 1027-1038 12 p. (Proceedings of the Annual ACM Symposium on Theory of Computing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
5 Scopus citations -
Robust algorithms with polynomial loss for near-unanimity CSPs
Dalmau, V., Kozik, M., Krokhin, A., Makarychev, K., Makarychev, Y. & Opršal, J., 2019, In: SIAM Journal on Computing. 48, 6, p. 1763-1795 33 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations