Konstantin Makarychev

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

Employment

01/01/2023 – present
  • Northwestern University, Evanston, IL
  • Associate Chair for Graduate Studies (DGS) at the Computer Science Department
09/2021 – present
  • Northwestern University, Evanston, IL
  • Professor of Computer Science
02/2017 – 08/2023
  • Microsoft Research, Redmond, WA
  • Consultant
02/2017 – 09/2021
  • Northwestern University, Evanston, IL
  • Associate Professor of Computer Science (with tenure)
04/2012 – 01/2017
  • Microsoft Research, Redmond, WA
  • Researcher, Theory Group
07/2007 – 04/2012
  • IBM Research, Yorktown Heights, NY
  • Research Staff Member, Algorithms Group
06/2006 – 09/2006
  • IBM Research, Yorktown Heights, NY
  • Intern, Algorithms Group
  • Mentor: Maxim Sviridenko
06/2005 – 09/2005
  • Microsoft Research, Redmond, WA
  • Intern, Theory Group
  • Mentor: Assaf Naor
01/2002 – 08/2003
  • Siebel Systems, San Mateo, CA
  • Software Engineer, Core Engineering

Education

2003 – 2007
  • Department of Computer Science, Princeton University
  • Ph.D. in Computer Science
  • Advisor: Moses Charikar
1996 – 2001
  • Department of Mathematics, Moscow University
  • M.S. in Pure and Applied Mathematics
  • Diploma with Honors; GPA 5.0/5.0
  • Advisors: Alexander Shen and Nikolai Vereshchagin
1992 – 1996
  • Moscow Math High School #57

Current and Former PhD Students

Postdocs

Summer Interns

Microsoft Research

IBM Research

Undergraduate Research Advisees

Professional Service

  • Program Committee Member: STOC 2022, ICALP 2021, SODA 2020, ESA 2018, STOC 2016, APPROX 2014, CSR 2014, ICALP 2013, CSR 2013, SODA 2013, APPROX 2012, STOC 2008
  • General co-chair for STOC 2020
  • PhD Dissertation Committees: Abhratanu Dutta (Northwestern University), Emirhan Gürpinar (Montpellier University), Jafar Jafarov (Toyota Technological Institute at Chicago), Tarik Kaced (Montpellier University), Aravindan Vijayaraghavan (Princeton University)
  • Grant reviewing for the National Science Foundation (NSF) and Israel Science Foundation (ISF)
  • Refereeing for APPROX, COLT, CSR, ESA, FOCS, ICALP, ICML, PODC, SODA, STACS, STOC, WINE (conferences); and Algorithmica, Combinatorica, Discrete Optimization, Information Processing Letters, Journal of ACM, Journal of Global Optimization, Mathematics of Operations Research, SIAM Journal on Computing, SIAM Journal on Discrete Mathematics, Theoretical Computer Science (journals)

Research Funding

2020 – 2024
NSF Award CCF-1955351 for Collaborative Medium Research Project “Design and Analysis of Models and Algorithms for Real-life Problems.” This is a joint project with Yury Makarychev.
2019 – 2022
Team member of the Institute for Data, Econometrics, Algorithms, and Learning (IDEAL). The institute is supported by NSF Award CCF-1934931.

Awards and Honors

2011
IBM A-Level Accomplishment for work on Semidefinite Programming
2010
IBM Research 2009 Pat Goldberg Memorial Best Paper Award
2006 – 2007
IBM Ph.D. Fellowship
2003 – 2007
Gordon Wu Fellowship
2003
Siebel Engineering Outstanding Contributor Award
1996 – 1997
George Soros Fellowship
1996
Russian Mathematical Olympiad – Silver Medal

Teaching

Northwestern University

  • Design and Analysis of Algorithms: Winter 2024, Fall 2022, Fall 2021, Winter 2021, Winter 2020, Winter 2019, Spring 2018, Winter 2018
  • Graduate Algorithms (syllabus): Fall 2024, Spring 2024, Fall 2020, Spring 2020
  • Approximation Algorithms (syllabus): Fall 2024, Winter 2023, Winter 2021, Spring 2019, Spring 2017
  • Special Topics in Approximation Algorithms: Winter 2025, Spring 2020
  • Advanced Algorithm Design Through the Lens of Competitive Programming: Winter 2022
  • Algorithms for Big Data: Spring 2022
  • Math Toolkit for Theoretical Computer Scientists: Spring 2019

University of Washington

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

Summer Schools

  • Metric Geometry and Its Applications in Computer Science (CS Club, Saint Petersburg, Russia): Fall 2017
  • Approximation Algorithms (CSR Conference): Summer 2013

Teaching Assistant at Princeton University

Math Instructor

  • Math circle classes for high school students at Moscow High School #57, Moscow University, and Moscow Center for Continuous Mathematical Education: 1996 – 1998, 2000 – 2001

Surveys and Book Chapters

  1. Perturbation Resilience
    • Konstantin Makarychev and Yury Makarychev
    • Beyond the Worst-Case Analysis of Algorithms. Editor: Tim Roughgarden. Cambridge University Press. 2020.
    •  
  2. Approximation Algorithms for CSPs (a survey of results)
    • Konstantin Makarychev and Yury Makarychev
    • The Constraint Satisfaction Problem: Complexity and Approximability. Editors: Andrei Krokhin and Stanislav Zivny. Dagstuhl Follow-Ups. 2017.
    •  
  3. 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. MIT Press. 2016.

Publications

  1. Constraint Satisfaction Problems with Advice
  2. Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
  3. Approximation Scheme for Weighted Metric Clustering via Sherali-Adams
  4. Higher-Order Cheeger Inequality for Partitioning with Buffers
  5. Random Cuts are Optimal for Explainable k-Medians
    • Konstantin Makarychev and Liren Shan
    • NeurIPS 2023 (oral presentation)
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  6. Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple!
    • Sayak Chakrabarty and Konstantin Makarychev
    • NeurIPS 2023
    •  
  7. Phylogenetic CSPs are Approximation Resistant
  8. Approximation Algorithm for Norm Multiway Cut
  9. Explainable k-means. Don’t be greedy, plant bigger trees!
    • Konstantin Makarychev and Liren Shan
    • STOC 2022
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  10. Near-optimal algorithms for explainable k-medians and k-means
    • Konstantin Makarychev and Liren Shan
    • ICML 2021
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  11. Local Correlation Clustering with Asymmetric Classification Errors
  12. Batch Optimization for DNA Synthesis
  13. Two-sided Kirszbraun Theorem
  14. Improved Guarantees for k-means++ and k-means++ Parallel
  15. Correlation Clustering with Asymmetric Classification Errors
  16. Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
  17. Certified Algorithms: Worst-Case Analysis and Beyond
  18. Correlation Clustering with Local Objectives
  19. Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering
  20. DNA assembly for nanopore data storage readout
  21. Scaling up DNA data storage and random access retrieval
  22. Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extensions
  23. Clustering Billions of Reads for DNA Data Storage
  24. Algorithms for Stable and Perturbation-Resilient Problems
  25. Robust algorithms with polynomial loss for near-unanimity CSPs
  26. Learning Communities in the Presence of Errors
  27. Union of Euclidean Metric Spaces is Euclidean
  28. A bi-criteria approximation algorithm for k-Means
  29. Satisfiability of Ordering CSPs Above Average
  30. Correlation Clustering with Noisy Partial Information
  31. Near Optimal LP Rounding Algorithm for Correlation Clustering on Complete Graphs
  32. Network-Aware Scheduling for Data-Parallel Jobs: Plan When You Can
  33. Solving Optimization Problems with Diseconomies of Scale
  34. Nonuniform Graph Partitioning with Unrelated Weights
    • Konstantin Makarychev and Yury Makarychev
    • ICALP 2014
    • Sbornik: Mathematics (Russian Academy of Sciences), vol. 208
    •  
  35. Precedence-constrained Scheduling of Malleable Jobs with Preemption
  36. Constant Factor Approximation for Balanced Cut in the PIE Model
  37. Bilu-Linial Stable Instances of Max Cut
  38. Approximation Algorithm for Sparsest k-Partitioning
  39. Speed Regularization and Optimality in Word Classing
  40. Local Search is Better than Random Assignment for Bounded Occurrence Ordering k-CSPs
    • Konstantin Makarychev
    • STACS 2013
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  41. Sorting Noisy Data with Partial Information
  42. Approximation Algorithm for Non-Boolean MAX k-CSP
  43. Approximation Algorithms for Semi-random Graph Partitioning Problems
  44. Concentration Inequalities for Nonlinear Matroid Intersection
  45. The Grothendieck Constant is Strictly Smaller than Krivine's Bound
  46. How to Play Unique Games Against a Semi-random Adversary
  47. Min-Max Graph Partitioning and Small Set Expansion
  48. Improved Approximation for the Directed Spanner Problem
  49. Maximizing Polynomials Subject to Assignment Constraints
  50. On Parsimonious Explanations For 2-D Tree- and Linearly-Ordered Data
  51. Assembly of Circular Genomes
  52. Metric Extension Operators, Vertex Sparsifiers and Lipschitz Extendability
  53. Maximum Quadratic Assignment Problem
  54. How to Play Unique Games on Expanders
  55. On Hardness of Pricing Items for Single-Minded Bidders
  56. Integrality Gaps for Sherali-Adams Relaxations
  57. Indexing Genomic Sequences on the IBM Blue Gene
    • Amol Ghoting and Konstantin Makarychev
    • SC 2009
    • ACM Gordon Bell Prize Finalist
    •  
  58. Serial and Parallel Methods for I/O Efficient Suffix Tree Construction
    • Amol Ghoting and Konstantin Makarychev
    • SIGMOD 2009
    • ACM Transactions on Database Systems (TODS), vol. 35(4), pp. 25:1-25:37
    • IBM Pat Goldberg Best Paper Award
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  59. Online Make-to-Order Joint Replenishment Model: Primal Dual Competitive Algorithms
  60. Local Global Tradeoffs in Metric Embeddings
  61. On the Advantage over Random for Maximum Acyclic Subgraph
  62. Near-Optimal Algorithms for Maximum Constraint Satisfaction Problems
  63. A Divide and Conquer Algorithm for d-Dimensional Linear Arrangement
  64. How to Play Unique Games Using Embeddings
  65. Near-Optimal Algorithms for Unique Games
  66. Directed Metrics and Directed Graph Partitioning Problems
  67. Square root log n approximation algorithms for Min UnCut, Min 2CNF Deletion, and directed cut problems
  68. Quadratic Forms on Graphs
  69. Chain Independence and Common Information
    • Konstantin Makarychev and Yury Makarychev
    • IEEE Transactions on Information Theory, 58(8), pp. 5279-5286, 2012
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  70. A new class of non Shannon type inequalities for entropies
  71. The Importance of Being Formal
    • Konstantin Makarychev and Yury Makarychev
    • The Mathematical Intelligencer, vol. 23 no. 1, 2001
    •  
  72. Proof of Pak's conjecture on tilings by T-tetrominoes (in Russian)

PhD Thesis

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

Patents

  1. Serial and parallel methods for I/O efficient suffix tree construction.
  2. Efficient clustering of noisy polynucleotide sequence reads.
  3. Efficient payload extraction from polynucleotide sequence reads.
  4. Efficient polymer synthesis.