World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
8641
World Ranking
12885
National Ranking
5198

Alex Olshevsky publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Alex Olshevsky sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 141 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Alex Olshevsky D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Alex Olshevsky sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 32 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Alex Olshevsky is affiliated with Boston University in the United States and specializes in the field of Computer Science. Their research primarily focuses on subfields such as Artificial Intelligence, Computer Networks and Communications, Computational Mechanics, Statistical and Nonlinear Physics, and Public Health, Environmental and Occupational Health.

The scientist's work encompasses several main topics including Stochastic Gradient Optimization Techniques, Distributed Control Multi-Agent Systems, Sparse and Compressive Sensing Techniques, Reinforcement Learning in Robotics, Model Reduction and Neural Networks, Mathematical and Theoretical Epidemiology and Ecology Models, as well as COVID-19 epidemiological studies.

Alex Olshevsky has contributed numerous publications to a range of venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Control Systems Letters
  • IEEE Transactions on Automatic Control
  • IEEE Signal Processing Magazine
  • SIAM Journal on Control and Optimization

The scientist's recent papers demonstrate a focus on distributed and stochastic optimization as well as control and matrix completion techniques. Selected recent publications include:

  • "Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning: Examining Distributed and Centralized Stochastic Gradient Descent," 2020, IEEE Signal Processing Magazine
  • "A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent," 2021, IEEE Transactions on Automatic Control
  • "Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion," 2020, arXiv (Cornell University)
  • "Deterministic and Randomized Actuator Scheduling With Guaranteed Performance Bounds," 2020, IEEE Transactions on Automatic Control
  • "Local SGD With a Communication Overhead Depending Only on the Number of Workers," 2020, arXiv (Cornell University)

Collaborations have been a notable aspect of their scientific activity. Frequent co-authors include:

  • Ioannis Ch. Paschalidis
  • Arsenii Mustafin
  • Bahman Gharesifard
  • Haoxing Tian
  • Shi Pu

Best Publications

  • Distributed optimization over time-varying directed graphs

    Angelia Nedic;Alex Olshevsky

  • Convergence in Multiagent Coordination, Consensus, and Flocking

    V.D. Blondel;J.M. Hendrickx;A. Olshevsky;J.N. Tsitsiklis

  • Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs

    Angelia Nedić;Alex Olshevsky;Wei Shi

  • Convergence Speed in Distributed Consensus and Averaging

    Alex Olshevsky;John N. Tsitsiklis

  • Federated learning of predictive models from federated Electronic Health Records.

    Theodora S. Brisimi;Ruidi Chen;Theofanie Mela;Alex Olshevsky

  • On distributed averaging algorithms and quantization effects

    A. Nedic;A. Olshevsky;A. Ozdaglar;J.N. Tsitsiklis

  • Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization

    Angelia Nedic;Alex Olshevsky;Michael G. Rabbat

  • Minimal Controllability Problems

    Alexander Olshevsky

  • Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs

    Angelia Nedic;Alex Olshevsky

  • Convergence Rates in Distributed Consensus and Averaging

    A. Olshevsky;J.N. Tsitsiklis

  • Distributed subgradient methods and quantization effects

    A. Nedic;A. Olshevsky;A. Ozdaglar;J.N. Tsitsiklis

  • Fast Convergence Rates for Distributed Non-Bayesian Learning

    Angelia Nedic;Alex Olshevsky;Cesar A. Uribe

  • Network Lifetime and Power Assignment in ad hoc Wireless Networks

    Gruia Calinescu;Sanjiv Kapoor;Alexander Olshevsky;Alexander Zelikovsky

  • NP-hardness of deciding convexity of quartic polynomials and related problems

    Amir Ali Ahmadi;Alexander Olshevsky;Pablo A. Parrilo;John N. Tsitsiklis

  • Geometrically convergent distributed optimization with uncoordinated step-sizes

    Angelia Nedic;Alex Olshevsky;Wei Shi;Cesar A. Uribe

  • Matrix $p$-Norms Are NP-Hard to Approximate If $p eq1,2,\infty$

    Julien M. Hendrickx;Alex Olshevsky

  • Nonasymptotic convergence rates for cooperative learning over time-varying directed graphs

    Angelia Nedic;Alex Olshevsky;Cesar A. Uribe

  • Linear Time Average Consensus on Fixed Graphs and Implications for Decentralized Optimization and Multi-Agent Control

    Alex Olshevsky

  • On the Nonexistence of Quadratic Lyapunov Functions for Consensus Algorithms

    A. Olshevsky;J.N. Tsitsiklis

  • Improved Convergence Rates for Distributed Resource Allocation

    Angelia Nedic;Alex Olshevsky;Wei Shi

  • Minimum input selection for structural controllability

    Alex Olshevsky

  • A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent

    Shi Pu;Alexander Olshevsky;Ioannis Ch. Paschalidis

  • Linear Time Average Consensus and Distributed Optimization on Fixed Graphs

    Alex Olshevsky

  • Distributed Anonymous Discrete Function Computation

    J. M. Hendrickx;A. Olshevsky;J. N. Tsitsiklis

  • Achieving Geometric Convergence for Distributed Optimization over Time-Varying Graphs

    Angelia Nedich;Alex Olshevsky;Wei Shi

  • Distributed optimization over time-varying directed graphs

    Angelia Nedic;Alex Olshevsky

Frequent Co-Authors

Angelia Nedic
Angelia Nedic Arizona State University
Julien M. Hendrickx
Julien M. Hendrickx Université Catholique de Louvain
Ioannis Ch. Paschalidis
Ioannis Ch. Paschalidis Boston University
Naomi Ehrich Leonard
Naomi Ehrich Leonard Princeton University
Venkatesh Saligrama
Venkatesh Saligrama Boston University
Vincent D. Blondel
Vincent D. Blondel Université Catholique de Louvain
Alexander Zelikovsky
Alexander Zelikovsky Georgia State University
Csaba Szepesvári
Csaba Szepesvári University of Alberta

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