Peter Eckmann

Peter Eckmann

Incoming CS PhD
Stanford University

Welcome! I’m an incoming Computer Science PhD student at Stanford University. Previously, I was an undergraduate at UC San Diego, where I worked with Dr. Rose Yu and Dr. Mike Gilson. My primary research interests are in machine learning and its applications to drug discovery. My work has involved generative modeling, molecular dynamics, and few-shot learning for small molecule drug discovery.

Education

  • PhD student, Stanford University (starting Sept. 2025)
  • Undergraduate, University of California San Diego (Sept. 2021 - June 2025)
    • B.S. Computer Science, 3.944 GPA

Honors and Awards

  • Stanford Graduate Fellowship (awarded Mar. 2025)
  • NSF Graduate Research Fellowship (awarded Apr. 2025)
  • Finalist, Outstanding Undergraduate Researcher Award, North American colleges and universities, Computing Research Association (Dec. 2023)
  • NSF Research Experiences for Undergraduates Award (June - Sept. 2023)
  • Regents Scholarship, UC San Diego (2021 - 2025)

Conference Publications

  • Eckmann P, Wu D, Heinzelmann G, Gilson MK, Yu R (2025). MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning. Presented at 42nd International Conference on Machine Learning (ICML) (2025, July 13-19). [PDF] [Code]
  • Eckmann P, Sun K, Zhao B, Feng M, Gilson MK, Yu R (2022). LIMO: Latent Inceptionism for Targeted Molecule Generation. Presented at 39th International Conference on Machine Learning (ICML) (2022, June 17-23). [PDF] [Code]

Journal Publications

  • Eckmann P, Anderson J, Yu R, Gilson MK (2024). Ligand-Based Compound Activity Prediction via Few-Shot Learning. Journal of Chemical Information and Modeling, 64 (14), 5492-5499. [PDF] [Code]
  • Ayoubi R, Ryan J, Biddle MS, Alshafie W, Fotouhi M, Bolivar SG, Moleon VR, Eckmann P, Worrall D, McDowell I, Southern K, Reintsch W, Durcan TM, Brown C, Bandrowski A, Virk H, Edwards AM, McPherson P, Laflamme C (2023). Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications. eLife, 12:RP91645. [PDF]
  • Eckmann P, Bandrowski A (2023). PreprintMatch: a tool for preprint publication detection applied to analyze global inequities in scientific publishing. PLoS ONE 18(3): e0281659. [PDF] [Code]
  • Bandrowski A, Pairish M, Eckmann P, Grethe J, Martone ME (2023). The Antibody Registry: ten years of registering antibodies. Nucleic Acids Research, 51(D1), D358-D367. [PDF]
  • Schulz R, Barnett A, Bernard R, Brown NJ, Byrne JA, Eckmann P, Gazda MA, Kilicoglu H, Prager EM, Salholz-Hillel M, Ter Riet G, Vines T, Vorland CJ, Zhuang H, Bandrowski A, Weissgerber TL (2022). Is the future of peer review automated? BMC Research Notes, 15(1), 1-5. [PDF]
  • Menke J, Eckmann P, Ozyurt IB, Roelandse M, Anderson N, Grethe J, Bandrowski A (2022). Establishing Institutional Scores With the Rigor and Transparency Index: Large-scale Analysis of Scientific Reporting Quality. Journal of Medical Internet Research, 24(6), e37324. [PDF]
  • Weissgerber T, Riedel N, Kilicoglu H, Labbé C, Eckmann P, Ter Riet G, Byrne J, Cabanac G, Capes-Davis A, Favier B, Saladi S, Grabitz P, Bannach-Brown A, Schulz R, McCann S, Bernard R, Bandrowski A (2021). Automated screening of COVID-19 preprints: can we help authors to improve transparency and reproducibility? Nature Medicine 27:6-7, 2021. [PDF]

Preprints

  • Thumuluri V, Eckmann P, Gilson MK, Yu R (2024). Technical report: Improving the properties of molecules generated by LIMO. arXiv:2407.14968 [cs.LG]. [PDF]
  • Eckmann P, Wu D, Heinzelmann G, Gilson MK, Yu R (2024). MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling. arXiv:2402.10387 [q-bio.BM]. [PDF]

Invited Talks

  • Learning on Graphs and Geometry (LoGG) Reading Group, Valence Labs (Mar. 2024). MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling. [Link]

Patents

  • Yu R, Eckmann P, Sun K, Zhao B, Feng M, Gilson MK (2023). Computational architecture to generate representations of molecules having targeted properties. United States patent pending US20240005179A1. June 16, 2023. [Link]

Conference Abstracts

  • Eckmann P, Bandrowski A. PreprintMatch: a new tool to match manuscripts across multiple similarity metrics. International Neuroinformatics Coordinating Facility Assembly, held virtually (2021, April 19-29) [Poster presentation]. [Link]
  • Eckmann P, Riedel N, Kilicoglu H, Labbé C, Ter Riet G, Byrne J, Cabanac G, Capes-Davis A, Favier B, Saladi S, Grabitz P, Bannach-Brown A, Schulz R, McCann S, Bernard R, Weissgerber T, Bandrowski A. Automated screening of COVID-19 preprints: can we help authors to improve transparency and reproducibility? Annual Meeting, Association for Interdisciplinary Meta-Research and Open Science (AIMOS), held virtually (2020, December 3-4) [Poster presentation]. [Link]
  • Eckmann P, Riedel N, Kilicoglu H, Labbé C, Ter Riet G, Byrne J, Cabanac G, Capes-Davis A, Favier B, Saladi S, Grabitz P, Bannach-Brown A, Schulz R, McCann S, Bernard R, Weissgerber T, Bandrowski A. Automated screening of COVID-19 preprints: can we help authors to improve transparency and reproducibility? Research Reproducibility 2020, held virtually (2020, December 2-3) [Oral presentation]. [Link]

Review Activity

Reviewer, International Conference on Learning Representations (ICLR) 2025