World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9848
World Ranking
7480
National Ranking
371

Milica Gasic 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 Milica Gasic 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: 111 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Milica Gasic 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 Milica Gasic 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Milica Gasic is affiliated with Heinrich Heine University Düsseldorf in Germany. Their research is primarily situated within the broad field of Computer Science, with a particular concentration on Artificial Intelligence. Other subfields of study include Experimental and Cognitive Psychology, Computational Theory and Mathematics, Social Psychology, and Computer Vision and Pattern Recognition.

The scientist's work extensively explores several main topics, such as:

  • Topic Modeling
  • Speech and dialogue systems
  • Natural Language Processing Techniques
  • AI in Service Interactions
  • Emotion and Mood Recognition
  • Intelligent Tutoring Systems and Adaptive Learning
  • Sentiment Analysis and Opinion Mining

Milica Gasic has contributed to numerous research papers published in various venues. Recent publications include:

  • "Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges," 2022, arXiv (Cornell University)
  • "TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking," 2020, arXiv (Cornell University)
  • "Robust Dialogue State Tracking with Weak Supervision and Sparse Data," 2022, Transactions of the Association for Computational Linguistics
  • "EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems," 2022, arXiv (Cornell University)
  • "Dynamic Dialogue Policy for Continual Reinforcement Learning," 2022, arXiv (Cornell University)

The frequent co-authors collaborating with Milica Gasic include:

  • Michael Heck
  • Carel van Niekerk
  • Nurul Lubis
  • Hsien-chin Lin
  • Christian Geishauser

Publications appear most often in the following venues:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • AI Magazine

Best Publications

  • Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems

    Tsung-Hsien Wen;Milica Gasic;Nikola Mrkšić;Pei-Hao Su

  • MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling

    Paweł Budzianowski;Tsung-Hsien Wen;Bo-Hsiang Tseng;Iñigo Casanueva

  • POMDP-Based Statistical Spoken Dialog Systems: A Review

    S. Young;M. Gasic;B. Thomson;J. D. Williams

  • A Network-based End-to-End Trainable Task-oriented Dialogue System

    Tsung-Hsien Wen;David Vandyke;Nikola Mrksic;Milica Gasic

  • The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management

    Steve Young;Milica Gašić;Simon Keizer;François Mairesse

  • Counter-fitting word vectors to linguistic constraints

    Nikola Mrksic;Diarmuid Ó Séaghdha;Blaise Thomson;Milica Gasic

  • Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

    Nikola Mrksic;Nikola Mrksic;Ivan Vulic;Diarmuid Ó Séaghdha;Ira Leviant

  • Multi-domain Neural Network Language Generation for Spoken Dialogue Systems

    Tsung-Hsien Wen;Milica Gasic;Nikola Mrksic;Lina Maria Rojas-Barahona

  • Multi-domain Dialog State Tracking using Recurrent Neural Networks

    Nikola Mrkšić;Diarmuid Ó Séaghdha;Blaise Thomson;Milica Gasic

  • TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking

    Michael Heck;Carel van Niekerk;Nurul Lubis;Christian Geishauser

  • Gaussian Processes for POMDP-Based Dialogue Manager Optimization

    Milica Gasic;Steve Young

  • PyDial: A Multi-domain Statistical Dialogue System Toolkit

    Stefan Ultes;Lina Maria Rojas-Barahona;Pei-Hao Su;David Vandyke

  • Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking

    Tsung-Hsien Wen;Milica Gasic;Dongho Kim;Nikola Mrksic

  • Phrase-Based Statistical Language Generation Using Graphical Models and Active Learning

    Francois Mairesse;Milica Gasic;Filip Jurcicek;Simon Keizer

  • Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing

    Osman Ramadan;Paweł Budzianowski;Milica Gašić

  • A Network-based End-to-End Trainable Task-oriented Dialogue System

    Tsung-Hsien Wen;David Vandyke;Nikola Mrksic;Milica Gasic

  • On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems

    Pei-Hao Su;Milica Gasic;Nikola Mrksic;Lina Maria Rojas-Barahona

  • Continuously Learning Neural Dialogue Management.

    Pei-Hao Su;Milica Gasic;Nikola Mrksic;Lina Maria Rojas-Barahona

  • Sample-efficient Actor-Critic Reinforcement Learning with Supervised Data for Dialogue Management

    Pei-Hao Su;Pawel Budzianowski;Stefan Ultes;Milica Gasic

  • Discriminative spoken language understanding using word confusion networks

    Matthew Henderson;Milica Gasic;Blaise Thomson;Pirros Tsiakoulis

  • Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

    Nikola Mrkšić;Ivan Vulić;Diarmuid Ó Séaghdha;Ira Leviant

  • POMDP-Based Statistical Spoken Dialog Systems: A Review This paper presents the theory and practice of belief tracking, policy optimization, parameter estimation, and fast learning.

    Steve Young;Milica Gasic;Blaise Thomson;Jason D. Williams

Frequent Co-Authors

Steve Young
Steve Young University of Cambridge
Nikola Mrksic
Nikola Mrksic PolyAI Limited
Kai Yu
Kai Yu Shanghai Jiao Tong University
Peter Mika
Peter Mika Yahoo (United Kingdom)
Verena Rieser
Verena Rieser Heriot-Watt University
Oliver Lemon
Oliver Lemon Heriot-Watt University
Roi Reichart
Roi Reichart Technion – Israel Institute of Technology
Jason D. Williams
Jason D. Williams Apple (United States)
Anna Korhonen
Anna Korhonen University of Cambridge
Ivan Vulić
Ivan Vulić University of Cambridge

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