About me

I am an Associate Professor of Computer Science at Northwestern University. I am interested in designing efficient algorithms for computationally hard problems. 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, theory of machine learning, and applications of high-dimension geometry in computer science.

Before joining Northwestern, I was a researcher at Microsoft and IBM Research Labs. I graduated from Princeton University in 2007. My PhD advisor was Moses Charikar. I received my undergraduate degree at the Department of Mathematics at Moscow State University. I finished Moscow Math High School #57.

See my CV for more info.


  • TTIC Workshop on Recent Trends in Clustering, September 18, 2019: Correlation Clustering
  • UPenn, October 25, 2019: Dimensionality Reduction for k-Means and k-Medians Clustering
  • FOCS Workshop on Beyond the Worst Case Analysis of Algorithms, November 9, 2019: Perturbation Stability and Certified Algorithms
  • Illinois Institute of Technology, November 19, 2019: Dimensionality Reduction for k-Means and k-Medians Clustering
  • Technion, December 2, 2019: Dimensionality Reduction for k-Means and k-Medians Clustering
  • Tel Aviv University, December 9, 2019: Dimensionality Reduction for k-Means and k-Medians Clustering

Events at Northwestern


Northwestern University

  • Design and Analysis of Algorithms: Winter 2020, Winter 2019, Spring 2018, and Winter 2018
  • Graduate Algorithms: Spring 2020
  • Approximation Algorithms: Spring 2019 and Spring 2017
  • Math Toolkit for Theoretical Computer Scientists: Spring 2019
  • Advanced Topics in Approximation Algorithms: Spring 2020

University of Washington

  • Linear and Semi-Definite Programming in Approximation Algorithms (with Mohit Singh):Fall 2014

PhD Students


  1. Approximation Algorithms for CSPs (a survey of results)
    • Konstantin Makarychev and Yury Makarychev
    • The Constraint Satisfaction Problem: Complexity and Approximability, Andrei Krokhin and Stanislav Zivny (Eds.), Dagstuhl Follow-Ups.
  2. Bilu–Linial Stability (a survey on Bilu–Linial stability and perturbation resilience)
    • Konstantin Makarychev and Yury Makarychev
    • Advanced Structured Prediction. Editors: T. Hazan, G. Papandreou, D. Tarlow (Eds.). MIT Press, 2016.


  1. Certified Algorithms: Worst-Case Analysis and Beyond
  2. Correlation Clustering with Local Objectives
    • Sanchit Kalhan, Konstantin Makarychev, Timothy Zhou
    • NeurIPS 2019, to appear
  3. Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering
  4. DNA assembly for nanopore data storage readout
  5. Scaling up DNA data storage and random access retrieval
  6. Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extensions
  7. Clustering Billions of Reads for DNA Data Storage
  8. Algorithms for Stable and Perturbation-Resilient Problems
  9. Robust algorithms with polynomial loss for near-unanimity CSPs
  10. Learning Communities in the Presence of Errors
  11. Union of Euclidean Metric Spaces is Euclidean
  12. A bi-criteria approximation algorithm for k-Means
  13. Satisfiability of Ordering CSPs Above Average
  14. Correlation Clustering with Noisy Partial Information
  15. Near Optimal LP Rounding Algorithm for Correlation Clustering on Complete Graphs
  16. Network-Aware Scheduling for Data-Parallel Jobs: Plan When You Can
  17. Solving Optimization Problems with Diseconomies of Scale
  18. Nonuniform Graph Partitioning with Unrelated Weights
  19. Precedence-constrained Scheduling of Malleable Jobs with Preemption
  20. Constant Factor Approximation for Balanced Cut in the PIE Model
  21. Bilu-Linial Stable Instances of Max Cut
  22. Approximation Algorithm for Sparsest k-Partitioning
  23. Speed Regularization and Optimality in Word Classing
  24. Local Search is Better than Random Assignment for Bounded Occurrence Ordering k-CSPs
    • Konstantin Makarychev
    • STACS 2013
  25. Sorting Noisy Data with Partial Information
  26. Approximation Algorithm for Non-Boolean MAX k-CSP
  27. Approximation Algorithms for Semi-random Graph Partitioning Problems
  28. Concentration Inequalities for Nonlinear Matroid Intersection
  29. The Grothendieck Constant is Strictly Smaller than Krivine's Bound
  30. How to Play Unique Games Against a Semi-random Adversary
  31. Min-Max Graph Partitioning and Small Set Expansion
  32. Improved Approximation for the Directed Spanner Problem
  33. Maximizing Polynomials Subject to Assignment Constraints
  34. On Parsimonious Explanations For 2-D Tree- and Linearly-Ordered Data
  35. Assembly of Circular Genomes
  36. Metric Extension Operators, Vertex Sparsifiers and Lipschitz Extendability
  37. Maximum Quadratic Assignment Problem
  38. How to Play Unique Games on Expanders
  39. On Hardness of Pricing Items for Single-Minded Bidders
  40. Integrality Gaps for Sherali-Adams Relaxations
  41. Indexing Genomic Sequences on the IBM Blue Gene
    • Amol Ghoting and Konstantin Makarychev
    • SC 2009
    • ACM Gordon Bell Prize Finalist
  42. Serial and Parallel Methods for I/O Efficient Suffix Tree Construction
    • Amol Ghoting and Konstantin Makarychev
    • SIGMOD 2009, pp. 827-840
    • ACM Transactions on Database Systems (TODS), vol. 35(4), pp. 25:1-25:37
    • IBM Pat Goldberg Best Paper Award
  43. Online Make-to-Order Joint Replenishment Model: Primal Dual Competitive Algorithms
  44. Local Global Tradeoffs in Metric Embeddings
  45. On the Advantage over Random for Maximum Acyclic Subgraph
  46. Near-Optimal Algorithms for Maximum Constraint Satisfaction Problems
  47. A Divide and Conquer Algorithm for d-Dimensional Linear Arrangement
  48. How to Play Unique Games Using Embeddings
  49. Near-Optimal Algorithms for Unique Games
  50. Directed Metrics and Directed Graph Partitioning Problems
  51. Square root log n approximation algorithms for Min UnCut, Min 2CNF Deletion, and directed cut problems
  52. Quadratic Forms on Graphs
  53. Chain Independence and Common Information
    • Konstantin Makarychev and Yury Makarychev
    • IEEE Transactions on Information Theory, 58(8), pp. 5279-5286, 2012
  54. A new class of non Shannon type inequalities for entropies
  55. The Importance of Being Formal
    • Konstantin Makarychev and Yury Makarychev
    • The Mathematical Intelligencer, vol. 23 no. 1, 2001
  56. Proof of Pak's conjecture on tilings by T-tetrominoes (in Russian)

PhD Thesis

  1. Quadratic Forms on Graphs and Their Applications
    • Konstantin Makarychev

Contact Information

  • Department of Computer Science
  • Northwestern University
  • Mudd Hall, Room 3009
  • 2233 Tech Drive, Third Floor
  • Evanston, IL 60208
  • Email: my_first_name [at]