World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
31
Citations
6133
World Ranking
9646
National Ranking
2745

Naoki Abe publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Naoki Abe sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 115 publications — 13th percentile

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

The last bar groups every scientist with 804 publications or more.

Naoki Abe D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Naoki Abe sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 31 D-Index — 2nd percentile

2% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Naoki Abe is affiliated with IBM in the United States and has contributed extensively to the field of medicine. Their main area of research focuses on inflammatory and autoimmune disorders, with a significant emphasis on inflammatory bowel disease and related gastrointestinal conditions.

Their research spans multiple subfields, including surgery, epidemiology, genetics, molecular biology, and gastroenterology. This multidisciplinary approach supports their investigation into various medical conditions and underlying biological mechanisms.

Naoki Abe's recent publications cover topics related to gastrointestinal diseases and biochemical markers. Notable works include:

  • Serum Zinc and Selenium in Children with Inflammatory Bowel Disease: A Multicenter Study in Japan, 2021, Digestive Diseases and Sciences
  • Safety and efficacy of the endoscopic delivery of capsule endoscopes in adult and pediatric patients: Multicenter Japanese study (AdvanCE-J study), 2021, Digestive Endoscopy
  • Diagnostic accuracy of serum proteinase 3 antineutrophil cytoplasmic antibodies in children with ulcerative colitis, 2020, Journal of Gastroenterology and Hepatology
  • Serum leucine-rich alpha-2 glycoprotein and calprotectin in children with inflammatory bowel disease: A multicenter study in Japan, 2023, Journal of Gastroenterology and Hepatology
  • Luteolin overcomes resistance to benzyl isothiocyanate-induced apoptosis in human colorectal cancer HCT-116 cells, 2020, Journal of Food and Drug Analysis

The frequent co-authors working with Naoki Abe include:

  • Toshihiko Kakiuchi
  • Yuri Etani
  • Tatsuki Mizuochi
  • Takahiro Kudo
  • Katsuhiro Arai

Their work has been published in various scientific venues, with multiple articles appearing in:

  • Case Reports in Women s Health
  • Journal of Gastroenterology and Hepatology
  • arXiv (Cornell University)
  • Digestive Diseases and Sciences
  • Digestive Endoscopy

Naoki Abe's research topics are varied but maintain a strong focus on gastrointestinal and inflammatory conditions. Main topics include inflammatory bowel disease, microscopic colitis, Helicobacter pylori-related gastroenterology studies, autoimmune and inflammatory disorders, point processes and geometric inequalities, diffusion and search dynamics, and trace elements in health.

Best Publications

  • Cost-sensitive learning by cost-proportionate example weighting

    B. Zadrozny;J. Langford;N. Abe

  • Query Learning Strategies Using Boosting and Bagging

    Naoki Abe;Hiroshi Mamitsuka

  • Outlier detection by active learning

    Naoki Abe;Bianca Zadrozny;John Langford

  • Temporal causal modeling with graphical granger methods

    Andrew Arnold;Yan Liu;Naoki Abe

  • Unintrusive customization techniques for Web advertising

    Marc Langheinrich;Atsuyoshi Nakamura;Naoki Abe;Tomonari Kamba

  • Generalizing case frames using a thesaurus and the MDL principle

    Hang Li;Naoki Abe

  • On the computational complexity of approximating distributions by probabilistic automata

    Naoki Abe;Manfred K. Warmuth

  • Collaborative Filtering Using Weighted Majority Prediction Algorithms

    Atsuyoshi Nakamura;Naoki Abe

  • Grouped graphical Granger modeling for gene expression regulatory networks discovery

    Aurélie C. Lozano;Naoki Abe;Yan Liu;Saharon Rosset

  • A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction

    Hisashi Kashima;Naoki Abe

  • An iterative method for multi-class cost-sensitive learning

    Naoki Abe;Bianca Zadrozny;John Langford

  • A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction

    H. Kashima;N. Abe

  • System and method for sequential decision making for customer relationship management

    Naoki Abe;Edwin P. D. Pednault

  • Spatial-temporal causal modeling for climate change attribution

    Aurelie C. Lozano;Hongfei Li;Alexandru Niculescu-Mizil;Yan Liu

  • Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction

    Grzegorz Swirszcz;Naoki Abe;Aurelie C Lozano

  • Reinforcement Learning with Immediate Rewards and Linear Hypotheses

    Naoki Abe;Alan W. Biermann;Philip M. Long

  • Optimizing debt collections using constrained reinforcement learning

    Naoki Abe;Prem Melville;Cezar Pendus;Chandan K. Reddy

  • Sequential cost-sensitive decision making with reinforcement learning

    Edwin Pednault;Naoki Abe;Bianca Zadrozny

  • Associative Reinforcement Learning using Linear Probabilistic Concepts

    Naoki Abe;Philip M. Long

  • Proximity-Based Anomaly Detection Using Sparse Structure Learning.

    Tsuyoshi Idé;Aurelie C. Lozano;Naoki Abe;Yan Liu

  • Predicting Protein Secondary Structure Using Stochastic Tree Grammars

    Naoki Abe;Hiroshi Mamitsuka

Frequent Co-Authors

Hang Li
Hang Li ByteDance
Hiroshi Mamitsuka
Hiroshi Mamitsuka Kyoto University
John Langford
John Langford Microsoft (United States)
Chandan K. Reddy
Chandan K. Reddy Virginia Tech
Saharon Rosset
Saharon Rosset Tel Aviv University
Hisashi Kashima
Hisashi Kashima Kyoto University
Philip M. Long
Philip M. Long Google (United States)
Manfred K. Warmuth
Manfred K. Warmuth Google (United States)
Marc Langheinrich
Marc Langheinrich Universita della Svizzera Italiana
Osamu Watanabe
Osamu Watanabe Tokyo Institute of Technology

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