Data Science and Machine Learning for Physics

Presentations

• PearSAN: an inverse design framework for the latent optimization of photonic devices using Pearson Correlated Surrogate Annealing

  ORAL

  March 21, 2025, 8:00 AM – March 21, 2025, 8:12 AM

  Publication: Bezick et al. (2024). PearSAN: A Machine Learning Method for Inverse Design using
  Pearson Correlated Surrogate Annealing. Planned Manuscript.

  Presenters

  • Michael Bezick

    • Purdue University

  Authors

  • Michael Bezick

    • Purdue University

  • Blake A Wilson

    • Purdue University

  • Vea Iyer

    • Purdue University

  • Yuheng Chen

    • Purdue University

  • Vladimir M Shalaev

    • Purdue University
    • Elmore Family School of Electrical and Computer Engineering,Birck Nanotechnology Center, Purdue University
    • Elmore Family School of Electrical and Computer Engineering, Purdue Quantum Science and Engineering Institute,Birck Nanotechnology Center, Purdue University

  • Sabre Kais

    • North Carolina State University
    • Purdue University
    • Department of Chemistry, Purdue University, West Lafayette, IN 47907 & Department of Electrical and Computer Engineering, North Carolina State University Raleigh, NC, 2760

  • Alexander V Kildishev

    • Purdue University

  • Alexandra Boltasseva

    • Purdue University
    • Elmore Family School of Electrical and Computer Engineering,Birck Nanotechnology Center, Purdue University
    • Elmore Family School of Electrical and Computer Engineering, Purdue Quantum Science and Engineering Institute,Birck Nanotechnology Center, Purdue University

  • Brad Lackey

    • Microsoft
    • Microsoft Quantum

  View abstract →

• Beyond Explainability: Towards Interpretable Machine Learning for Physics

  ORAL

  March 21, 2025, 8:12 AM – March 21, 2025, 8:24 AM

  Presenters

  • Kacper Jakub Cybinski

    • University of Warsaw

  Authors

  • Kacper Jakub Cybinski

    • University of Warsaw

  • Anna Dawid

    • Leiden University

  View abstract →

• Cosmic Cartography: Photometric Redshifts for Next-Generation Sky Surveys

  ORAL

  March 21, 2025, 8:24 AM – March 21, 2025, 8:36 AM

  Presenters

  • Biprateep Dey

    • University of Toronto

  Authors

  • Biprateep Dey

    • University of Toronto

  • Jeffrey A Newman

    • University of Pittsburgh

  • Brett Andrews

    • University of Pittsburgh

  • Ann Lee

    • Carnegie Mellon University

  • Rafael Izbicki

    • University of Sao Carlos

  View abstract →

• Generalized aliasing: a new paradigm for learning and inference

  ORAL

  March 21, 2025, 8:36 AM – March 21, 2025, 8:48 AM

  Publication: https://arxiv.org/pdf/2408.08294

  Presenters

  • Gus L.W. Hart

    • Brigham Young University

  Authors

  • Gus L.W. Hart

    • Brigham Young University

  • Mark K Transtrum

    • Brigham Young University

  • Tyler Jarvis

    • Brigham Young University

  • Jared P Whitehead

    • Brigham Young University

  View abstract →

• Oral: Gaussian Process Active Learning for 5-Parameter Heisenberg Hamiltonian Phase Diagram

  ORAL

  March 21, 2025, 8:48 AM – March 21, 2025, 9:00 AM

  Presenters

  • Edward Jansen

    • Adelphi University

  Authors

  • Edward Jansen

    • Adelphi University

  View abstract →

• Recruiting Outside Talent to Find the World's Smallest Machines

  ORAL

  March 21, 2025, 9:00 AM – March 21, 2025, 9:12 AM

  Presenters

  • Braxton B Owens

    • Brigham Young University

  Authors

  • Braxton B Owens

    • Brigham Young University

  View abstract →

• Learning collective motions in soft matter by dynamic mode decomposition

  ORAL

  March 21, 2025, 9:12 AM – March 21, 2025, 9:24 AM

  Presenters

  • Meng Shen

    • California State University, Fullerton

  Authors

  • Meng Shen

    • California State University, Fullerton

  View abstract →