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Regina Barzilay

Active 1997–2026

270
Papers
39,853
Citations
96
h-index
228
i10-index

Citations

Citations per year for Regina Barzilay1967: 5 citations1969: 3 citations1980: 1 citations1985: 1 citations1987: 1 citations1988: 1 citations1989: 2 citations1993: 3 citations1994: 1 citations1995: 2 citations1996: 1 citations1997: 7 citations1998: 13 citations1999: 19 citations2000: 42 citations2001: 59 citations2002: 86 citations2003: 99 citations2004: 145 citations2005: 152 citations2006: 193 citations2007: 216 citations2008: 290 citations2009: 307 citations2010: 433 citations2011: 498 citations2012: 483 citations2013: 479 citations2014: 496 citations2015: 505 citations2016: 544 citations2017: 528 citations2018: 695 citations2019: 1,060 citations2020: 1,557 citations2021: 1,847 citations2022: 1,460 citations2023: 1,886 citations2024: 2,506 citations2025: 2,345 citations2026: 543 citations1968: no citations, so this year is not shown1970–1979: no citations, so these years are not shown1981–1984: no citations, so these years are not shown1986: no citations, so this year is not shown1990–1992: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 5,144 citing papers, 26.6% of this breakdownChina: 3,054 citing papers, 15.8% of this breakdownUnited Kingdom: 1,465 citing papers, 7.6% of this breakdownGermany: 878 citing papers, 4.5% of this breakdownCanada: 670 citing papers, 3.5% of this breakdownIndia: 658 citing papers, 3.4% of this breakdownJapan: 529 citing papers, 2.7% of this breakdownFrance: 513 citing papers, 2.7% of this breakdownSouth Korea: 420 citing papers, 2.2% of this breakdownSwitzerland: 413 citing papers, 2.1% of this breakdownAustralia: 357 citing papers, 1.9% of this breakdownItaly: 349 citing papers, 1.8% of this breakdown
0%26.6%Other 25.2%

Institutions

Fields

  • Computer Science68.6%
  • Biochemistry, Genetics and Molecular Biology9.2%
  • Medicine7%
  • Materials Science5.8%
  • Engineering2.4%
  • Social Sciences1.1%
  • Other5.9%

Topics

  • Topic Modeling13.3%
  • Natural Language Processing Techniques11%
  • Computational Drug Discovery Methods5.6%
  • Machine Learning in Materials Science4.5%
  • Advanced Text Analysis Techniques4.1%
  • Protein Structure and Dynamics2.4%
  • Other59.1%

Coauthors

All papers

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  1. De novo design of protein structure and function with RFdiffusion

    Authors: Joseph L. Watson, David Juergens, Nathaniel R. Bennett, Brian L. Trippe, Jason Yim, Helen E. Eisenach, Woody Ahern, Andrew J. Borst, Robert J. Ragotte, Lukas F. Milles, Basile I. M. Wicky, Nikita Hanikel, Samuel J. Pellock, Alexis Courbet, William Sheffler, Jue Wang, Preetham Venkatesh, Isaac Sappington, Susana Vázquez Torres, Anna Lauko, Valentin De Bortoli, Émile Mathieu, Sergey Ovchinnikov, Regina Barzilay, Tommi Jaakkola, Frank DiMaio, Minkyung Baek, David Baker - Nature 2023 cited by 2,154

  2. A Deep Learning Approach to Antibiotic Discovery

    Authors: Jonathan Stokes, Kevin Yang, Kyle L. Swanson, Wengong Jin, Andrés Cubillos-Ruiz, Nina M. Donghia, Craig R. MacNair, Shawn French, Lindsey A. Carfrae, Zohar Bloom‐Ackermann, Victoria M. Tran, Anush Chiappino-Pepe, Ahmed H. Badran, Ian W. Andrews, Emma J. Chory, George M. Church, Eric D. Brown, Tommi Jaakkola, Regina Barzilay, James J. Collins - Cell 2020 cited by 2,341

  3. DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

    Authors: Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola - ICLR 2023 cited by 789

  4. Graph neural networks

    Authors: Gabriele Corso, H. Stärk, Stefanie Jegelka, Tommi Jaakkola, Regina Barzilay - Nature Reviews Methods Primers 2024 cited by 347

  5. Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii

    Authors: Gary Liu, Denise B. Catacutan, Khushi Rathod, Kyle Swanson, Wengong Jin, Jody C. Mohammed, Anush Chiappino-Pepe, Saad A. Syed, Meghan Fragis, Kenneth Rachwalski, Jakob Magolan, Michael G. Surette, Brian K. Coombes, Tommi Jaakkola, Regina Barzilay, James J. Collins, J Stokes - Nature Chemical Biology 2023 cited by 328

  6. Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

    Authors: Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth, Tommi S. Jaakkola - ICML 2024 cited by 334

  7. SE(3) diffusion model with application to protein backbone generation

    Authors: Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola - ICML 2023 cited by 347

  8. Boltz-1 Democratizing Biomolecular Interaction Modeling

    Authors: Jeremy Wohlwend, Gabriele Corso, Saro Passaro, Noah Getz, Mateo Reveiz, Ken Leidal, Wojtek Swiderski, Liam Atkinson, Tally Portnoi, Itamar Chinn, Jacob Silterra, Tommi Jaakkola, Regina Barzilay - 2024 cited by 409

  9. Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

    Authors: Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Xu Zhao, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah R. Lawrence, H. Stärk, Shurui Gui, Carl N. Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru‐Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Žitnik, Anima Anandkumar, Stefano Ermon, Píetro Lió, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji - Foundations and Trends® in Machine Learning, Found. Trends Mach. Learn. 2025 cited by 141

  10. Applications of Deep Learning in Molecule Generation and Molecular Property Prediction

    Authors: W. Patrick Walters, Regina Barzilay - Accounts of Chemical Research 2020 cited by 383

  11. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction

    Authors: Adam Yala, Constance D. Lehman, Tal Schuster, Tally Portnoi, Regina Barzilay - Radiology 2019 cited by 735

  12. Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem

    Authors: Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi S. Jaakkola - ICLR 2023 cited by 347

  13. A Graph-Convolutional Neural Network Model for the Prediction of Chemical Reactivity

    Authors: Connor W. Coley, Wengong Jin, Luke Rogers, Timothy F. Jamison, Tommi Jaakkola, William H. Green, Regina Barzilay, Klavs F. Jensen - Chemical Science 2018 cited by 696

  14. Fast protein backbone generation with SE(3) flow matching

    Authors: Jason Yim, Andrew M. Campbell, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Víctor García Satorras, Bastiaan S. Veeling, Regina Barzilay, Tommi Jaakkola, Frank Noé - arXiv (Cornell University) 2023 cited by 103

  15. Crystal Diffusion Variational Autoencoder for Periodic Material Generation

    Authors: Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi S. Jaakkola - ICLR 2022 cited by 445

  16. Generative models for molecular discovery: Recent advances and challenges

    Authors: Camille Bilodeau, Wengong Jin, Tommi Jaakkola, Regina Barzilay, Klavs F. Jensen - Wiley Interdisciplinary Reviews Computational Molecular Science 2022 cited by 310

  17. Junction Tree Variational Autoencoder for Molecular Graph Generation

    Authors: Wengong Jin, Regina Barzilay, Tommi S. Jaakkola - ICML 2018 cited by 1,678

  18. Prediction of Organic Reaction Outcomes Using Machine Learning

    Authors: Connor W. Coley, Regina Barzilay, Tommi Jaakkola, William H. Green, Klavs F. Jensen - ACS Central Science 2017 cited by 823

  19. Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography

    Authors: Peter G. Mikhael, Jeremy Wohlwend, Adam Yala, Ludvig Karstens, Justin Xiang, A. Takigami, Patrick Bourgouin, PuiYee Chan, Sofiane Mrah, Wael Amayri, Yu‐Hsiang Juan, Cheng‐Ta Yang, Yung‐Liang Wan, Gigin Lin, Lecia V. Sequist, Florian J. Fintelmann, Regina Barzilay - Journal of Clinical Oncology 2023 cited by 250

  20. Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction

    Authors: Saro Passaro, Gabriele Corso, Jeremy Wohlwend, Mateo Reveiz, Stephan Thaler, Vignesh Ram Somnath, Noah Getz, Tally Portnoi, Julien Roy, H. Stärk, David Kwabi-Addo, Dominique Beaini, Tommi Jaakkola, Regina Barzilay - 2025 cited by 447

  21. Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction

    Authors: Connor W. Coley, Regina Barzilay, William H. Green Jr., Tommi S. Jaakkola, Klavs F. Jensen - Journal of Chemical Information and Modeling, J. Chem. Inf. Model. 2017 cited by 515

  22. Conformal Language Modeling

    Authors: Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay - ICLR 2024 cited by 167

  23. Dirichlet Flow Matching with Applications to DNA Sequence Design

    Authors: Hannes Stärk, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi S. Jaakkola - ICML 2024 cited by 131

  24. Toward robust mammography-based models for breast cancer risk

    Authors: Adam Yala, Peter G. Mikhael, Fredrik Strand, Gigin Lin, Kevin Smith, Yung‐Liang Wan, Leslie R. Lamb, Kevin S. Hughes, Constance D. Lehman, Regina Barzilay - Science Translational Medicine 2021 cited by 268