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Data Science, ML and Active Matter

FOCUS · T53 · ID: 1066996






Presentations

  • Data-driven approaches to predict and understand the dynamics of active nematics

    ORAL · Invited

    Publication: Joshi, C; Ray, S; Lemma, L; Varghese, M.; Sharp, G; Dogic, Z; Baskaran, A*; Hagan, MF*, "Data-driven discovery of active nematic hydrodynamics", doi.org/10.48550/arXiv.2202.12854

    Presenters

    • Michael F Hagan

      Brandeis Univ, Department of Physics & MRSEC, Brandeis University, Waltham, MA, Brandeis University

    Authors

    • Michael F Hagan

      Brandeis Univ, Department of Physics & MRSEC, Brandeis University, Waltham, MA, Brandeis University

    View abstract →

  • Learning a compact representation of the nematic director of active nematics

    ORAL

    Presenters

    • Phu N Tran

      Brandeis University

    Authors

    • Phu N Tran

      Brandeis University

    • Zvonimir Dogic

      University of California, Santa Barbara

    • Aparna Baskaran

      Brandeis Univ, Brandeis University

    • Pengyu Hong

      Brandeis University

    • Michael F Hagan

      Brandeis Univ, Department of Physics & MRSEC, Brandeis University, Waltham, MA, Brandeis University

    View abstract →

  • Categorizing spatiotemporal dynamics of bacterial swarm fronts

    ORAL

    Presenters

    • Alasdair Hastewell

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    Authors

    • Alasdair Hastewell

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    • Hannah Jeckel

      University of Basel, Biozentrum, University of Basel

    • Andreea-Oana Chelban

      Biozentrum, University of Basel

    • Gabriel Rodriguez-Roig

      Florida International University

    • Knut Drescher

      University of Basel, Biozentrum, University of Basel

    • Jorn Dunkel

      Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT

    View abstract →

  • Neural networks for data-driven models of cell mechanics

    ORAL

    Presenters

    • Matthew Schmitt

      University of Chicago

    Authors

    • Matthew Schmitt

      University of Chicago

    • Jonathan Colen

      University of Chicago

    • Stefano Sala

      Loyola University Chicago

    • Margaret Gardel

      University of Chicago

    • Patrick W Oakes

      Loyola University Chicago

    • Vincenzo Vitelli

      University of Chicago

    View abstract →