World's Best Scientists 2026 revealed!
Prakash M. Nadkarni

Prakash M. Nadkarni

Prakash M. Nadkarni 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 Prakash M. Nadkarni 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+

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

Prakash M. Nadkarni 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 Prakash M. Nadkarni 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+

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

Overview

Prakash M. Nadkarni is affiliated with Yale University in the United States. Their research spans multiple fields of study, prominently including Medicine and Computer Science. Within these fields, their work covers several subfields such as Pulmonary and Respiratory Medicine, Epidemiology, Computer Networks and Communications, and Signal Processing.

The main topics of Nadkarni's research focus on congenital heart disease studies, aortic disease and treatment approaches, cardiovascular and diving-related complications, as well as network security and intrusion detection and advanced malware detection techniques.

The recent publications by Nadkarni include:

  • Percutaneous Transcatheter Therapy in a Case of Lutembacher's Syndrome, 2024, Indian Journal of Clinical Cardiology
  • A Survey On Secure Machine Learning, 2025, arXiv (Cornell University)

The venues where Nadkarni frequently publishes include the Indian Journal of Clinical Cardiology and arXiv (Cornell University).

Research collaboration is a part of Nadkarni's work. Frequent co-authors include Michelle Viegas Parab, Guruprasad Naik, Taobo Liao, and Taoran Li.

Best Publications

  • Natural language processing: an introduction.

    Prakash M. Nadkarni;Lucila Ohno-Machado;Wendy Webber Chapman

  • Organization of Heterogeneous Scientific Data Using the EAV/CR Representation

    Prakash M. Nadkarni;Luis N. Marenco;Roland Chen;Emmanouil Skoufos

  • Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions

    Wendy Webber Chapman;Prakash M. Nadkarni;Lynette Hirschman;Leonard W. D'Avolio;Leonard W. D'Avolio

  • Use of General-purpose Negation Detection to Augment Concept Indexing of Medical Documents: A Quantitative Study Using the UMLS

    Pradeep G. Mutalik;Aniruddha Deshpande;Prakash M. Nadkarni

  • Data Extraction and Ad Hoc Query of an Entity- Attribute-Value Database

    Prakash M. Nadkarni;Cynthia Brandt

  • The Human Brain Project : neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data

    Gordon M. Shepherd;Jason S. Mirsky;Matthew D. Healy;Michael S. Singer

  • UMLS concept indexing for production databases: a feasibility study.

    Prakash M. Nadkarni;Roland Chen;Cynthia Brandt

  • Guidelines for the effective use of entity-attribute-value modeling for biomedical databases.

    Valentin Dinu;Prakash M. Nadkarni

  • Managing Attribute–Value Clinical Trials Data Using the ACT/DB Client–Server Database System

    Prakash M. Nadkarni;Cynthia Brandt;Sandra J. Frawley;Frederick G. Sayward

  • Exploring performance issues for a clinical database organized using an entity-attribute-value representation.

    Roland Chen;Prakash M. Nadkarni;Luis N. Marenco;Forrest W. Levin

  • WebEAV: automatic metadata-driven generation of web interfaces to entity-attribute-value databases.

    Prakash M. Nadkarni;Cynthia M. Brandt;Luis Marenco

  • Exploring the Degree of Concordance of Coded and Textual Data in Answering Clinical Queries from a Clinical Data Repository

    H. David Stein;Prakash M. Nadkarni;Joseph Erdos;Perry L. Miller

  • Achieving evolvable Web-database bioscience applications using the EAV/CR framework: recent advances.

    Luis N. Marenco;Nicholas P. Tosches;Chiquito J. Crasto;Gordon M. Shepherd

  • Data standards for clinical research data collection forms: current status and challenges

    Rachel L. Richesson;Prakash M. Nadkarni

  • The Common Data Elements for Cancer Research: Remarks on Functions and Structure

    Prakash M. Nadkarni;Cynthia A. Brandt

  • Metadata-driven creation of data marts from an EAV-modeled clinical research database.

    Cynthia A Brandt;Richard Morse;Keri Matthews;Kexin Sun

  • Migrating existing clinical content from ICD-9 to SNOMED

    Prakash M Nadkarni;Jonathan A Darer

  • Drug safety surveillance using de-identified EMR and claims data: issues and challenges.

    Prakash M Nadkarni

  • Database tools for integrating and searching membrane property data correlated with neuronal morphology

    Jason S. Mirsky;Prakash M. Nadkarni;Matthew D. Healy;Perry L. Miller

  • Using a Computer Database to Monitor Compliance With Pharmacotherapeutic Guidelines for Schizophrenia

    Roland S. Chen;Prakash M. Nadkarni;Forrest L. Levin;Perry L. Miller

Frequent Co-Authors

Perry L. Miller
Perry L. Miller Yale University
Gordon M. Shepherd
Gordon M. Shepherd Yale School of Medicine
Kei-Hoi Cheung
Kei-Hoi Cheung Yale University
Kenneth K. Kidd
Kenneth K. Kidd Yale University
Michele Migliore
Michele Migliore National Academies of Sciences, Engineering, and Medicine
Andrew J. Pakstis
Andrew J. Pakstis Yale University
Stephen T. Reeders
Stephen T. Reeders Brigham and Women's Hospital
Michael L. Hines
Michael L. Hines Yale University
David C. Ward
David C. Ward Nevada Cancer Research Foundation
Raju Kucherlapati
Raju Kucherlapati Harvard University

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 can open up various online education and career pathways. For example, some students start their journey with an associates degree online, which offers flexibility and a quick entry into the tech field. This can be a great option for those seeking foundational skills or a stepping stone to a bachelor’s program.

If you’re considering graduate study, you may want to look into masters degrees that are worth it. Specialized master’s programs in computer science or related fields are in high demand and can significantly boost your job prospects and earning potential.

Affordability is a key concern for many students. Luckily, there are many cheap online college classes available that can help you balance costs while gaining quality education. These programs allow you to learn at your own pace and save money.

Worried about your academic history? Some will grad schools accept low gpa and still provide pathways to a successful tech career. Research your options and keep striving for your goals in computer science!

Best Scientists Citing Prakash M. Nadkarni

Trending Scientists

Recently Published Articles