World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
4258
World Ranking
12265
National Ranking
27

Jiří Sgall 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 Jiří Sgall 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: 120 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Jiří Sgall 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 Jiří Sgall 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Jiří Sgall is affiliated with Charles University in the Czech Republic, focusing primarily on research in computer science and engineering. Their work addresses complex problems in optimization, scheduling, and computational theory.

The primary fields of study include:

  • Computer Science
  • Engineering

Within these fields, their research spans several subfields such as:

  • Computer Networks and Communications
  • Industrial and Manufacturing Engineering
  • Computational Theory and Mathematics
  • Management Information Systems
  • Electrical and Electronic Engineering

The main topics covered in Jiří Sgall's research include:

  • Optimization and Search Problems
  • Scheduling and Optimization Algorithms
  • Complexity and Algorithms in Graphs
  • Advanced Graph Theory Research
  • Interconnection Networks and Systems
  • Optimization and Packing Problems
  • Supply Chain and Inventory Management

Jiří Sgall has contributed to a number of papers published in respected venues, with recent works including:

  • "Multiprocessor jobs, preemptive schedules, and one-competitive online algorithms," 2023, Operations Research Letters
  • "Online Algorithms for Multilevel Aggregation," 2020, Operations Research
  • "A φ-Competitive Algorithm for Scheduling Packets with Deadlines," 2022, SIAM Journal on Computing
  • "New results on multi-level aggregation," 2021, Theoretical Computer Science
  • "Improved online load balancing with known makespan," 2024, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Frequent publication venues for Jiří Sgall include:

  • Theoretical Computer Science
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Operations Research Letters
  • Operations Research
  • SIAM Journal on Computing

Their collaborative work prominently features coauthors such as:

  • Pavel Veselý
  • Martin Böhm
  • Marek Chrobák
  • Marcin Bieńkowski
  • Łukasz Jeż

Best Publications

  • Multiprocessor Scheduling with Rejection

    Yair Bartal;Stefano Leonardi;Alberto Marchetti-Spaccamela;Jirí Sgall

  • On the computational power of DNA

    Dan Boneh;Christopher Dunworth;Richard J. Lipton;Jiří Sgall

  • On-line Scheduling

    Unknown

  • Dynamic scheduling on parallel machines

    Anja Feldmann;Jiří Sgall;Shang-Hua Teng

  • Lower bounds for the polynomial calculus and the Gröbner basis algorithm

    Russell Impagliazzo;Pavel Pudlák;Jiří Sgall

  • Semi-online scheduling with decreasing job sizes

    Steve Seiden;Jiřı Sgall;Gerhard Woeginger

  • Proof complexity in algebraic systems and bounded depth Frege systems with modular counting

    S. Buss;R. Impagliazzo;J. Krajíček;P. Pudlák

  • Online competitive algorithms for maximizing weighted throughput of unit jobs

    Francis Y. L. Chin;Marek Chrobak;Stanley P. Y. Fung;Wojciech Jawor

  • Graph balancing: a special case of scheduling unrelated parallel machines

    Tomáš Ebenlendr;Marek Krčál;Jiří Sgall

  • Energy-Aware Scheduling for Streaming Applications on Chip Multiprocessors

    Ruibin Xu;R. Melhem;D. Mosse

  • On the complexity of cake cutting

    Gerhard J. Woeginger;Jiří Sgall

  • Boolean Circuits, Tensor Ranks, and Communication Complexity

    Pavel Pudlák;Vojtech Rödl;Jirí Sgall

  • Optimal online scheduling of parallel jobs with dependencies

    Anja Feldmann;Ming-Yang Kao;Jiří Sgall;Shang-Hua Teng

  • A lower bound for randomized on-line multiprocessor scheduling

    Jiří Sgall

  • Computer-Aided Complexity Classification of Dial-a-Ride Problems

    Willem E. de Paepe;Jan Karel Lenstra;Jiri Sgall;René A. Sitters

  • Online Scheduling of Equal-Length Jobs: Randomization and Restarts Help

    Marek Chrobak;Wojciech Jawor;Jir caron;i´ Sgall

  • Online Competitive Algorithms for Maximizing Weighted Throughput of Unit Jobs

    Yair Bartal;Francis Y. L. Chin;Marek Chrobak;Stanley P. Y. Fung

  • The greedy algorithm for the minimum common string partition problem

    Marek Chrobak;Petr Kolman;Jiří Sgall

  • Approximation Schemes for Scheduling on Uniformly Related and Identical Parallel Machines

    Leah Epstein;Jiri Sgall

  • A lower bound for on-line scheduling on uniformly related machines

    Leah Epstein;Jiřı Sgall

  • Improved online algorithms for buffer management in QoS switches

    Marek Chrobak;Wojciech Jawor;Jiří Sgall;Tomáš Tichý

  • Ancient and new algorithms for load balancing in the Lp norm

    Adi Avidor;Yossi Azar;Jiří Sgall

  • Dynamic scheduling on parallel machines

    S. Feldmann;J. Sgall;S.-H. Teng

  • Randomized online scheduling on two uniform machines

    Leah Epstein;John Noga;Steve Seiden;Jiří Sgall

Frequent Co-Authors

Marek Chrobak
Marek Chrobak University of California, Riverside
Gerhard J. Woeginger
Gerhard J. Woeginger RWTH Aachen University
Daniel Král
Daniel Král Masaryk University
Leah Epstein
Leah Epstein University of Haifa
Shang-Hua Teng
Shang-Hua Teng University of Southern California
Anja Feldmann
Anja Feldmann Max Planck Society
Leen Stougie
Leen Stougie Centrum Wiskunde & Informatica
Monika Henzinger
Monika Henzinger Institute of Science and Technology Austria
Yair Bartal
Yair Bartal Hebrew University of Jerusalem
Luca Aceto
Luca Aceto Reykjavík University

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