World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
9837
World Ranking
5877
National Ranking
134

Fabrizio Maria Maggi 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 Fabrizio Maria Maggi 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: 226 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Fabrizio Maria Maggi 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 Fabrizio Maria Maggi 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: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Overview

Fabrizio Maria Maggi is affiliated with the Free University of Bozen-Bolzano in Italy. Their research spans several areas within computer science and business management, focusing extensively on process modeling, information systems, and related computational methods.

The main fields of study for Fabrizio Maria Maggi include:

  • Computer Science
  • Business, Management and Accounting

The scientist's work is further specialized in subfields such as:

  • Management Information Systems
  • Artificial Intelligence
  • Information Systems
  • Computational Theory and Mathematics
  • Industrial and Manufacturing Engineering

Maggi's research mainly covers these topics:

  • Business Process Modeling and Analysis
  • Service-Oriented Architecture and Web Services
  • Semantic Web and Ontologies
  • Data Quality and Management
  • Petri Nets in System Modeling
  • Formal Methods in Verification
  • Software System Performance and Reliability

The scientist has frequently published in venues such as:

  • arXiv (Cornell University)
  • Information Systems
  • SSRN Electronic Journal
  • Process Science
  • Business & Information Systems Engineering

Some notable recent papers include:

  • "Robotic Process Mining: Vision and Challenges" (2020) published in Business & Information Systems Engineering
  • "Fire now, fire later: alarm-based systems for prescriptive process monitoring" (2021) in Knowledge and Information Systems
  • "Encoding resource experience for predictive process monitoring" (2021) in Decision Support Systems
  • "How do I update my model? On the resilience of Predictive Process Monitoring models to change" (2022) in Knowledge and Information Systems
  • "Probabilistic Trace Alignment" (2021) in BOA (University of Milano-Bicocca)

Fabrizio Maria Maggi often collaborates with other researchers, including:

  • Marco Montali
  • Chiara Di Francescomarino
  • Chiara Ghidini
  • Ivan Donadello
  • Fabio Patrizi

Books published with Springer Science+Business Media featuring Fabrizio Maria Maggi are:

  • "Enterprise Design, Operations, and Computing" (2022)
  • "Enterprise Design, Operations, and Computing. EDOC 2022 Workshops" (2023)

Best Publications

  • Process Mining Manifesto

    Wil van der Aalst;Wil van der Aalst;Arya Adriansyah;Ana Karla Alves de Medeiros;Franco Arcieri

  • Automated Discovery of Process Models from Event Logs: Review and Benchmark

    Adriano Augusto;Raffaele Conforti;Marlon Dumas;Marcello La Rosa

  • Outcome-Oriented Predictive Process Monitoring: Review and Benchmark

    Irene Teinemaa;Marlon Dumas;Marcello La Rosa;Fabrizio Maria Maggi

  • Predictive Monitoring of Business Processes

    Fabrizio Maria Maggi;Chiara Di Francescomarino;Marlon Dumas;Chiara Ghidini

  • Monitoring business constraints with linear temporal logic: an approach based on colored automata

    Fabrizio Maria Maggi;Marco Montali;Michael Westergaard;Wil M. P. Van Der Aalst

  • Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

    Anna Leontjeva;Raffaele Conforti;Chiara Francescomarino;Marlon Dumas

  • User-guided discovery of declarative process models

    Fabrizio M. Maggi;Arjan J. Mooij;Wil M.P. van der Aalst

  • Compliance monitoring in business processes

    Linh Thao Ly;Fabrizio Maria Maggi;Marco Montali;Stefanie Rinderle-Ma

  • Conformance checking based on multi-perspective declarative process models

    Andrea Burattin;Fabrizio M. Maggi;Alessandro Sperduti

  • Declarative process mining in healthcare

    Marcella Rovani;Fabrizio M. Maggi;Massimiliano de Leoni;Wil M.P. van der Aalst

  • Clustering-Based Predictive Process Monitoring

    Chiara Di Francescomarino;Marlon Dumas;Fabrizio Maria Maggi;Irene Teinemaa

  • Predictive Process Monitoring Methods: Which One Suits Me Best?

    Chiara Di Francescomarino;Chiara Ghidini;Fabrizio Maria Maggi;Fredrik Milani

  • Efficient discovery of understandable declarative process models from event logs

    Fabrizio M. Maggi;R. P. Jagadeesh Chandra Bose;Wil M. P. van der Aalst

  • Smart technologies for long-term stress monitoring at work

    Rafal Kocielnik;Natalia Sidorova;Fabrizio Maria Maggi;Martin Ouwerkerk

  • Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

    Ilya Verenich;Marlon Dumas;Marcello La Rosa;Fabrizio Maria Maggi

  • Monitoring business constraints with the event calculus

    Marco Montali;Fabrizio M. Maggi;Federico Chesani;Paola Mello

  • Genetic algorithms for hyperparameter optimization in predictive business process monitoring

    Chiara Di Francescomarino;Marlon Dumas;Marco Federici;Chiara Ghidini

  • Aligning event logs and declarative process models for conformance checking

    Massimiliano de Leoni;Fabrizio Maria Maggi;Wil M. P. van der Aalst

  • An alignment-based framework to check the conformance of declarative process models and to preprocess event-log data

    Massimiliano de Leoni;Fabrizio M. Maggi;Wil M.P. van der Aalst

  • Robotic Process Mining: Vision and Challenges

    Volodymyr Leno;Artem Polyvyanyy;Marlon Dumas;Marcello La Rosa

  • Declarative process mining in healthcare

    M. Rovani;F.M. Maggi;M. de Leoni;W.M.P. van der Aalst

Frequent Co-Authors

Marlon Dumas
Marlon Dumas University of Tartu
Marco Montali
Marco Montali Free University of Bozen-Bolzano
Marcello La Rosa
Marcello La Rosa University of Melbourne
Wil M. P. van der Aalst
Wil M. P. van der Aalst RWTH Aachen University
Claudio Di Ciccio
Claudio Di Ciccio Utrecht University
Jan Mendling
Jan Mendling Humboldt-Universität zu Berlin
Artem Polyvyanyy
Artem Polyvyanyy University of Melbourne
Massimiliano de Leoni
Massimiliano de Leoni University of Padua
Giuseppe De Giacomo
Giuseppe De Giacomo Sapienza University of Rome
Diego Calvanese
Diego Calvanese Free University of Bozen-Bolzano

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

As interest in studying Computer Science in the USA grows, many students are now exploring flexible online degrees that open doors to diverse career opportunities. Online programs offer the convenience and accessibility needed by both working professionals and recent graduates.

Beyond computer science, related high-demand fields include data science, business management, and construction. For example, those looking to deepen their data analytics expertise can benefit from an online data science masters, which equips graduates for roles in AI, analytics, and research.

Similarly, expanding industries like construction are embracing digital innovation. An online degree for construction management prepares students for leadership positions in construction planning and project oversight.

For those interested in business or entrepreneurship, pursuing the most affordable online mba can offer essential management and leadership skills at a fraction of traditional costs.

Finally, if you are looking for a fast track to graduation, consider exploring one year online masters programs that allow you to quickly gain advanced qualifications and accelerate your career.

Best Scientists Citing Fabrizio Maria Maggi

Trending Scientists

Recently Published Articles