World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
74
Citations
20344
World Ranking
1506
National Ranking
784

Electronics and Electrical Engineering

D-Index
68
Citations
17884
World Ranking
1019
National Ranking
431

Research.com Recognitions

  • 2013 - IEEE Fellow For contributions to optimization methods in electronic design automation
  • 2011 - ACM Distinguished Member
  • 2007 - ACM Senior Member

Overview

Igor L. Markov is affiliated with Synopsys in the United States. Their research primarily spans the field of Computer Science, with a notable focus on Artificial Intelligence, Electrical and Electronic Engineering, and Information Systems. Additional subfields include Hardware and Architecture as well as Computer Vision and Pattern Recognition.

The scientist's work covers several main research topics including:

  • Quantum Computing Algorithms and Architecture
  • Parallel Computing and Optimization Techniques
  • Privacy-Preserving Technologies in Data
  • Machine Learning and Data Classification
  • Cryptography and Data Security
  • Software Engineering Research
  • Quantum Information and Cryptography

Igor L. Markov has published extensively, with contributions to venues such as:

  • arXiv (Cornell University)
  • Известия высших учебных заведений Электромеханика
  • ACM Transactions on Quantum Computing
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Machine Learning

Notable recent papers include:

  • "Approximating Decision Diagrams for Quantum Circuit Simulation," 2022, ACM Transactions on Quantum Computing
  • "Looper: An End-to-End ML Platform for Product Decisions," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Workshops on Extreme Scale Design Automation (ESDA) Challenges and Opportunities for 2025 and Beyond," 2020, arXiv (Cornell University)
  • "Enhancing quantum computer performance via symmetrization," 2023, arXiv (Cornell University)
  • "The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement," 2023, arXiv (Cornell University)

Frequent collaborators in Igor L. Markov's research include Norm Zhou, Hanson Wang, Graham Cormode, Nitya Kasturi, and Mia R. Garrard. These coauthors have contributed to multiple publications alongside Igor L. Markov.

The scientist has received several professional recognitions including:

  • IEEE Fellow, awarded in 2013, for contributions to optimization methods in electronic design automation
  • ACM Distinguished Member, awarded in 2011
  • ACM Senior Member, awarded in 2007

Best Publications

  • Ending Piracy of Integrated Circuits

    J A Roy;F Koushanfar;I L Markov

  • Synthesis of quantum-logic circuits

    V.V. Shende;S.S. Bullock;I.L. Markov

  • EPIC: ending piracy of integrated circuits

    Jarrod A. Roy;Farinaz Koushanfar;Igor L. Markov

  • Synthesis of reversible logic circuits

    V.V. Shende;A.K. Prasad;I.L. Markov;J.P. Hayes

  • Limits on fundamental limits to computation

    Igor L. Markov

  • Can recursive bisection alone produce routable placements

    Andrew E. Caldwell;Andrew B. Kahng;Igor L. Markov

  • Simulating Quantum Computation by Contracting Tensor Networks

    Igor L. Markov;Yaoyun Shi

  • Fixed-outline floorplanning: enabling hierarchical design

    S.N. Adya;I.L. Markov

  • VLSI Physical Design: From Graph Partitioning to Timing Closure

    Andrew B. Kahng;Jens Lienig;Igor L. Markov;Jin Hu

  • Minimal universal two-qubit controlled- NOT -based circuits

    Vivek V. Shende;Igor L. Markov;Stephen S. Bullock

  • Accurate Reliability Evaluation and Enhancement via Probabilistic Transfer Matrices

    Smita Krishnaswamy;George F. Viamontes;Igor L. Markov;John P. Hayes

  • Synthesis and optimization of reversible circuits—a survey

    Mehdi Saeedi;Igor L. Markov

  • High-Performance Routing at the Nanometer Scale

    J.A. Roy;I.L. Markov

  • Watermarking techniques for intellectual property protection

    A. B. Kahng;J. Lach;W. H. Mangione-Smith;S. Mantik

  • SimPL: An Effective Placement Algorithm

    Myung-Chul Kim;Dong-Jin Lee;I. L. Markov

  • Fault testing for reversible circuits

    K.N. Patel;J.P. Hayes;I.L. Markov

  • Progress and challenges in VLSI placement research

    Igor L. Markov;Jin Hu;Myung-Chul Kim

  • Efficient symmetry breaking for Boolean satisfiability

    F.A. Aloul;K.A. Sakallah;I.L. Markov

  • Constraint-based watermarking techniques for design IP protection

    A.B. Kahng;J. Lach;W.H. Mangione-Smith;S. Mantik

  • Generic ILP versus specialized 0-1 ILP: an update

    Fadi A. Aloul;Arathi Ramani;Igor L. Markov;Karem A. Sakallah

Frequent Co-Authors

John P. Hayes
John P. Hayes University of Michigan–Ann Arbor
Andrew B. Kahng
Andrew B. Kahng University of California, San Diego
Karem A. Sakallah
Karem A. Sakallah University of Michigan–Ann Arbor
Valeria Bertacco
Valeria Bertacco University of Michigan–Ann Arbor
Charles J. Alpert
Charles J. Alpert Cadence Design Systems
Farinaz Koushanfar
Farinaz Koushanfar University of California, San Diego
Luciano Lavagno
Luciano Lavagno Polytechnic University of Turin
Tony F. Chan
Tony F. Chan University of California, Los Angeles
Dennis Sylvester
Dennis Sylvester University of Michigan–Ann Arbor
Miodrag Potkonjak
Miodrag Potkonjak University of California, Los Angeles

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