World's Best Scientists 2026 revealed!
Connor W. Coley

Connor W. Coley

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Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
51
Citations
11836
World Ranking
290
National Ranking
50

Chemistry

D-Index
51
Citations
13913
World Ranking
13782
National Ranking
3577

Engineering and Technology

D-Index
54
Citations
16308
World Ranking
3118
National Ranking
922

Connor W. Coley 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 Connor W. Coley sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 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: 117 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: 59 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: 146 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Connor W. Coley 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 Connor W. Coley sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 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: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 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: 94 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: 24 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: 54 D-Index — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Connor W. Coley is affiliated with MIT in the United States. Their research focus spans multiple scientific fields, including computer science, materials science, and biochemistry, genetics, and molecular biology. Within these domains, they have contributed extensively to subfields such as materials chemistry, computational theory and mathematics, molecular biology, biomedical engineering, and artificial intelligence.

Their work covers a range of main topics, notably computational drug discovery methods and machine learning applications in materials science. Other topics addressed in their research include innovative microfluidic and catalytic techniques innovation, chemical synthesis and analysis, protein structure and dynamics, chemistry and chemical engineering, and click chemistry and applications.

Recent papers authored or coauthored by Coley demonstrate a focus on the intersection of artificial intelligence, chemistry, and materials science. Key recent publications include:

  • Scientific discovery in the age of artificial intelligence, 2023, Nature
  • The Synthesizability of Molecules Proposed by Generative Models, 2020, Journal of Chemical Information and Modeling
  • The Open Reaction Database, 2021, Journal of the American Chemical Society
  • Accelerating high-throughput virtual screening through molecular pool-based active learning, 2021, Chemical Science
  • Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis, 2020, Journal of Medicinal Chemistry

Frequent coauthors collaborating with Coley include:

  • Klavs F. Jensen
  • Wenhao Gao
  • Regina Barzilay
  • David Graff
  • Zhengkai Tu

Publication venues in which Coley has appeared most frequently reflect the interdisciplinary nature of their research. These include:

  • arXiv (Cornell University)
  • Journal of Chemical Information and Modeling
  • Chemical Science
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Digital Discovery

Best Publications

  • Analyzing Learned Molecular Representations for Property Prediction.

    Kevin Yang;Kyle Swanson;Wengong Jin;Connor W. Coley

  • A robotic platform for flow synthesis of organic compounds informed by AI planning

    Connor W. Coley;Dale A. Thomas;Justin A. M. Lummiss;Jonathan N. Jaworski

  • Prediction of Organic Reaction Outcomes Using Machine Learning

    Connor W. Coley;Regina Barzilay;Tommi S. Jaakkola;William H. Green

  • Machine Learning in Computer-Aided Synthesis Planning

    Connor W Coley;William H Green;Klavs F Jensen

  • A graph-convolutional neural network model for the prediction of chemical reactivity

    Connor W. Coley;Wengong Jin;Luke Rogers;Timothy F. Jamison

  • Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction

    Connor W. Coley;Regina Barzilay;William H. Green;Tommi S. Jaakkola

  • Using Machine Learning To Predict Suitable Conditions for Organic Reactions.

    Hanyu Gao;Thomas J. Struble;Connor W. Coley;Yuran Wang

  • Autonomous Discovery in the Chemical Sciences Part I: Progress.

    Connor W. Coley;Natalie S. Eyke;Klavs F. Jensen

  • Computer-Assisted Retrosynthesis Based on Molecular Similarity

    Connor W. Coley;Luke Rogers;William H. Green;Klavs F. Jensen

  • SCScore: Synthetic Complexity Learned from a Reaction Corpus.

    Connor W. Coley;Luke Rogers;William H. Green;Klavs F. Jensen

  • The Synthesizability of Molecules Proposed by Generative Models

    Wenhao Gao;Wenhao Gao;Connor W. Coley;Connor W. Coley

  • The Open Reaction Database.

    Steven M. Kearnes;Michael R. Maser;Michael Wleklinski;Anton Kast

  • BigSMILES: A Structurally-Based Line Notation for Describing Macromolecules

    Tzyy-Shyang Lin;Connor Wilson Coley;Hidenobu Mochigase;Haley K. Beech

  • Accelerating high-throughput virtual screening through molecular pool-based active learning

    David E. Graff;Eugene I. Shakhnovich;Connor W. Coley

  • Autonomous Discovery in the Chemical Sciences Part II: Outlook.

    Connor W. Coley;Natalie S. Eyke;Klavs F. Jensen

  • Uncertainty Quantification Using Neural Networks for Molecular Property Prediction

    Lior Hirschfeld;Kyle Swanson;Kevin Yang;Regina Barzilay

  • Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis.

    Thomas J. Struble;Juan C. Alvarez;Scott P. Brown;Milan Chytil

  • RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application.

    Connor W Coley;William H Green;Klavs F Jensen

  • Evidential Deep Learning for Guided Molecular Property Prediction and Discovery.

    Ava P Soleimany;Ava P Soleimany;Ava P Soleimany;Alexander Amini;Samuel Goldman;Daniela Rus

  • Learning Retrosynthetic Planning through Simulated Experience.

    John S. Schreck;Connor W. Coley;Kyle J. M. Bishop

  • Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network

    Wengong Jin;Connor Wilson Coley;Regina Barzilay;Tommi S Jaakkola

  • Automated microfluidic platform for systematic studies of colloidal perovskite nanocrystals: towards continuous nano-manufacturing

    Robert W. Epps;Kobi C. Felton;Connor W. Coley;Milad Abolhasani

  • Photoredox Iridium–Nickel Dual-Catalyzed Decarboxylative Arylation Cross-Coupling: From Batch to Continuous Flow via Self-Optimizing Segmented Flow Reactor

    Hsiao-Wu Hsieh;Connor W. Coley;Lorenz M. Baumgartner;Klavs F. Jensen

  • Retrosynthesis Prediction with Conditional Graph Logic Network

    Hanjun Dai;Chengtao Li;Connor W. Coley;Bo Dai

Frequent Co-Authors

Cao Xiao
Cao Xiao General Electric (United Kingdom)
Jimeng Sun
Jimeng Sun University of Illinois at Urbana-Champaign
Kevin Van Geem
Kevin Van Geem Ghent University
Kyle J. M. Bishop
Kyle J. M. Bishop Columbia University

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