World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
7111
World Ranking
12434
National Ranking
609

Stefan Lessmann 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 Stefan Lessmann 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: 119 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Stefan Lessmann 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 Stefan Lessmann 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

Stefan Lessmann is affiliated with Humboldt-Universität zu Berlin in Germany. Their research spans multiple fields with a strong focus on computer science and business, management, and accounting. The scientist's work extensively covers artificial intelligence, marketing, economics and econometrics, management science and operations research, and accounting.

Their research topics highlight various specialized areas including financial distress and bankruptcy prediction, stock market forecasting methods, consumer market behavior and pricing, imbalanced data classification techniques, market dynamics and volatility, customer churn and segmentation, and advanced causal inference techniques.

Stefan Lessmann has contributed to a range of academic venues with recurring publications in:

  • arXiv (Cornell University)
  • European Journal of Operational Research
  • SSRN Electronic Journal
  • Expert Systems with Applications
  • RePEc: Research Papers in Economics

Some of the recent papers authored or coauthored by Stefan Lessmann include:

  • Deep learning for detecting financial statement fraud, 2020, Decision Support Systems
  • Predicting online shopping behaviour from clickstream data using deep learning, 2020, Expert Systems with Applications
  • Fairness in credit scoring: Assessment, implementation and profit implications, 2021, European Journal of Operational Research
  • A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters, 2021, Information Systems Frontiers
  • Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda, 2023, European Journal of Operational Research

The scientist frequently collaborates with several coauthors, including:

  • Wolfgang Karl Härdle
  • Daniel Traian Pele
  • Björn Bokelmann
  • Nikita Kozodoi
  • Wouter Verbeke

Stefan Lessmann's research integrates elements of machine learning, data analysis, and operational research to address challenges in financial and consumer markets. Their work encompasses studies on fraud detection, online consumer behavior, fairness in credit scoring, sentiment analysis in social media, and explainable AI applications in operational research.

Best Publications

  • Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings

    S. Lessmann;B. Baesens;C. Mues;S. Pietsch

  • Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research

    Stefan Lessmann;Bart Baesens;Bart Baesens;Hsin-Vonn Seow;Lyn C. Thomas

  • A comparative study of LSTM neural networks in forecasting day-ahead global horizontal irradiance with satellite data

    Shikhar Srivastava;Stefan Lessmann

  • The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing

    Sven F. Crone;Stefan Lessmann;Robert Stahlbock

  • Deep learning for detecting financial statement fraud

    Patricia Craja;Alisa Kim;Stefan Lessmann

  • Conditional Wasserstein GAN-based oversampling of tabular data for imbalanced learning

    Justin Engelmann;Stefan Lessmann

  • A comparative analysis of data preparation algorithms for customer churn prediction

    Kristof Coussement;Stefan Lessmann;Geert Verstraeten

  • Genetic Algorithms for Support Vector Machine Model Selection

    S. Lessmann;R. Stahlbock;S.F. Crone

  • Extreme learning machines for credit scoring: An empirical evaluation

    Artem Bequé;Stefan Lessmann

  • Predicting online shopping behaviour from clickstream data using deep learning

    Dennis Koehn;Stefan Lessmann;Markus Schaal

  • Incorporating textual information in customer churn prediction models based on a convolutional neural network

    Arno De Caigny;Arno De Caigny;Kristof Coussement;Kristof Coussement;Koen W. De Bock;Stefan Lessmann

  • Fairness in credit scoring: Assessment, implementation and profit implications

    Nikita Kozodoi;Johannes Jacob;Stefan Lessmann

  • A multi-objective approach for profit-driven feature selection in credit scoring

    Nikita Kozodoi;Stefan Lessmann;Konstantinos Papakonstantinou;Yiannis Gatsoulis

  • A reference model for customer-centric data mining with support vector machines

    Stefan Lessmann;Stefan Voß

  • Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting

    Alisa Kim;Y. Yang;Stefan Lessmann;Tiejun Ma

  • A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters

    Shalak Mendon;Shalak Mendon;Pankaj Dutta;Abhishek Behl;Stefan Lessmann

  • Forex exchange rate forecasting using deep recurrent neural networks

    Alexander Jakob Dautel;Wolfgang Karl Härdle;Stefan Lessmann;Hsin-Vonn Seow

  • A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

    Abhishek Behl;Pankaj Dutta;Stefan Lessmann;Yogesh K. Dwivedi

  • Targeting customers for profit: An ensemble learning framework to support marketing decision-making

    Stefan Lessmann;Johannes Haupt;Kristof Coussement;Koen W. De Bock

  • Car resale price forecasting: The impact of regression method, private information, and heterogeneity on forecast accuracy

    Stefan Lessmann;Stefan Voß

  • Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting

    Yaodong Yang;Alisa Kolesnikova;Stefan Lessmann;Tiejun Ma

Frequent Co-Authors

Wolfgang Karl Härdle
Wolfgang Karl Härdle Humboldt-Universität zu Berlin
Kristof Coussement
Kristof Coussement IESEG School of Management
Stefan Voß
Stefan Voß Universität Hamburg
Bart Baesens
Bart Baesens KU Leuven
Lyn C. Thomas
Lyn C. Thomas University of Southampton
Marco C. Campi
Marco C. Campi University of Brescia
Gary M. Weiss
Gary M. Weiss Fordham University
Samarjit Kar
Samarjit Kar National Institute of Technology Durgapur
Yogesh K. Dwivedi
Yogesh K. Dwivedi King Fahd University of Petroleum and Minerals

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens doors to diverse online degree options. Many students consider easy associate degrees as a flexible starting point, offering quick entry into the tech workforce or a foundation for further studies.

For those aiming for leadership roles in education or higher-level academic positions, an ed d degree can help them develop research and management skills needed in modern learning environments.

The rise of remote education has also made it easier to access online schools that are nationally accredited. These institutions offer recognized programs in computer science and related fields, maintaining quality and affordability.

Additionally, interest is growing in creative tech fields. If you’re passionate about gaming or interactive media, pursuing the video game design degree can lead to exciting careers in game development, animation, and digital art.

Best Scientists Citing Stefan Lessmann

Trending Scientists

Recently Published Articles