Clements Scientific Computing Seminar

A Seminar Series by Leading Researchers in Scientific Computing and Applied mathematics

Fall, 2024 (126 Clements Hall)

  • September 19 (Thursday)   Jerome Darbon, applied math, Brown
  • October 17 (Thursday)  Yi Sun, math, usc
  • October 30 (Thursday)   tba
  • November 14 (Thursday)  Hui Cao, Physics, Yale
  • December 5 (Thursday)  tba

Spring, 2024 (126 Clements Hall)

  • February 14 (Wednesday), Zhimin Zhang,  WSU,A Family of Finite Element Stokes Complexes In Three Dimensions
  • February 29 (Thursday), Qiang Du, Applied Physics and Applied Math,  Columbia, Nonlocal models on bounded domains: formulation, analysis and computation
  • March 22 (Friday), George Yin, Math, Uconn, Computational Nonlinear Filtering  A Deep Learning Approach
  • April 11 (Thursday), Haizhao Yang, Math, UMD,  Finite Expression Method: A Symbolic Approach for Scientific Machine Learning
  • April 25 (Thursday)  Paul Dupuis, Applied Math, Brown, Interacting Particle Methods for Moment Generating Functions, Quasistationary Distributions, and Ergodic Control

Fall, 2023  ( 126 Clements Hall)

Spring, 2023 (Harold Clark Simmons Hall 207)

  • March 9, Thursday, 3:45pm, Prof. Dal Negro Luca, ECE, Boston University, Physics-informed adaptive networks for electromagnetic inverse problems: why neural networks must learn physics before guessing
  • April 13, Thursday, 3:45pm, Prof. Jack F. Douglas, Materials Science and Engineering Division, NIST, ZENO: A Computational Path-Integration Method for Nanoparticle and Polymer Characterization
  • May 9, Tuesday 3:45pm, Prof. Paul Dupuis, Applied Math, Brown University (re-scheduled to Spring, 2024).

Fall, 2022  ( 126 Clements Hall)

  • September 14, Wednesday, 3:45pm, Prof. Dongbin Xiu, Dept of Math., OSU, Data Driven Modeling of Unknown Systems with Deep Neural Networks
  • October 5, Wednesday, 3:45pm,   Prof. Haomin Zhou, Dept of Math., Gatech, Inverse Weak Adversarial Networks (iWAN): A Computational Method for High-dimensional Inverse Problems
  • October 19, Wednesday, 3:45pm,  Prof. Chun Liu, Dept of Math., IIT, Energetic variational approaches: dynamic boundary conditions and thermal effects
  • October 26, Wednesday, 3:45pm, Prof. A. Bensoussan, School of Management, UTD,  Control on Hilbert Spaces And Mean Field Control
  • November 2, Wednesday, 3:45pm,  tba
  • November 16, Wednesday, 3:45pm, Prof. Youssef Marzouk, MIT
  • December 7, Wednesday, 3:45pm , tba (date tentative), 


Spring, 2022 (126 Clements Hall)

  • February 18, Friday, 3:30pm, Prof. Lu Lu, Dept of Chemical and Biomolecular Engineering, U. Penn,   Learning nonlinear operators using deep neural networks for diverse applications
  • March 3, Thursday, 3:45pm, Prof. Yuan Gao, Dept of Math, Purdue University, Droplets with moving contact line and insoluble surfactant: Onsager’s principle, variational inequality, computations
  • March 4, Friday, 11am, Prof. Jianguo Liu, Dept of Math, Duke University, Macroscopic dynamics for nonequilibrium biochemical reactions from a Hamiltonian viewpoint
  • March 31, Thursday, 3:45pm, Prof. Bjorn Engquist,  Dept of Math, UT Austin, Stochastic gradient descent algorithm for global optimization
  • April 14, Thursday, 3;45pm (zoom) Prof. Stas Molchanov, Math, UNC Charlotte, Dynamo – Theorem (Review) (on zoom)
  • April 28,  Thursday, 3;45pm. Prof. Jiguang Sun, Dept of Math, Michigan Tech University, A deterministic-statistical approach to reconstruct moving sources using sparse partial data

Fall, 2021  (126 Clements Hall)

  • October 7, Thursday, 3:45pm, Prof. Kui Ren, Math, Columbia University, Revisiting the Classical Least-Squares Formulation for Computational Learning and Inversion (on zoom)
  • October 28, Thursday, 3:45pm, Prof. Per-Gunnar Martinsson, ICES, UT Austin, Direct solvers for elliptic PDEs
  • November 11, Thursday, 3:45pm,  Prof.  Alexandre Tartakovsky, Civil and Environmental Engineering, UIUC, Physics-Informed Machine Learning Method for Large-Scale Data Assimilation Problems (on zoom).
  • December 2, Thursday, 3:45pm,  Prof. Xingjie Li, Math, UNC Charlotte. Coarse – Graining of stochastic system

Spring, 2020 (126 Clements Hall)

  • January 30, Thursday, 3:45pm, Prof. Yuehaw Khoo, Stat. U. of Chicago, Multimarginal optimal transport and density functional theory
  • February 11, Tuesday, 3:45pm, Prof. George Karniadakis, Brown University, Physics Informed Neural Networks for Physical Problems & Biological Problems
  • February 20, Thursday, 3:45pm, Prof. Shi Jin, INS, Shanghai Jiaotong Univ., Random Batch Methods for Classical and Quantum N-body Problems
  • February 27, Thursday, 3:45pm, Prof. Hongkai Zhao, Math, UCI, Intrinsic complexity: from approximation of random vectors and random fields to solutions of PDEs
  • March 12,  Thursday, 3:45pm, Prof. Ren-cang Li, Math, UT Arlington

Fall, 2019 (126 Clements Hall)

  • September 19,  Thursday, 3:45pm,  Jiequn Han, Math., Princeton University, Uniformly Accurate Machine Learning Based Hydrodynamic Models for Kinetic Equation
  • September 16-27, 3:30pm or 5pm, Prof. Andriy Baumketner, Condensed matter physics, Ukraine Academy of Sciences, 10 lectures on Monte Carlo Method for Problems in Mathematics, Physics and Biology
  • October 3, Thursday, 3:45pm,  Chiwang Shu, Applied Math, Brown University,  Discontinuous Galerkin Method for Convection Dominated Partial Differential Equations
  • October 17, Thursday, 3:45pm, tba
  • October  31, Thursday, 3:45pm,   Guillaume Bal,  Stats and Math, U. of Chicago, Topological invariants for interface modes.
  • November 14, Thursday, 3:45pm, Max Gunzburger, Dept of Sci. Compt, FSU,  Integral equation modeling for anomalous diffusion and nonlocal mechanics
  • November 21, Thursday, 3:45pm,  Xiaoliang Wan, Math, Capture small-noise-induced rare events in differential equations
  • December 5, Thursday, 3:45pm Prof. Shi-li Zhang, Solid State Electronics, Uppsala University, Nano-pores and DNA sensing

Spring, 2019 (126 Clements Hall)

  • February 7, Thursday, 3:45 pm, Guofei Pang, Applied Math, Brown, Physics-informed neural networks: A deep learning framework for solving forward and inverse problems of PDEs and fractional PDEs
  • February 28, Thursday, 3:45 pm, Eitan Tadmor, Math, Univ. of Maryland, Emergent behavior in collective dynamics
  • March 20, Wednesday, 3:30 pm, Greg Gbur, Physics, UNC Charlotte, Infinite Hotels in Swirling Beams of Light
  • April 4,  Thursday, 3:45 pm, Shiwei Zhang, Physics, WM, Flatiron Institute, Ab- initio computations in quantum many-body systems 
  • April 10, Wednesday, 3:30pm, Elton Hsu, Math, Northwestern, Brown motions, history, theory, and application
  • April 18,  Thursday, 3:45 pm, Longfei Li, Math, LSU, A stable partitioned FSI algorithm for incompressible flow and deforming beams
  • May 2,  Thursday, 3:45 pm, Jianfeng Lu, Math, Duke, Solving large-scale leading eigenvalue problem


Fall, 2018 (126 Clements Hall)

  • September 6, Thursday, 3:45pm, Mi Sun Min, Math & CS, Argonne National Lab, High-order methods for multi-physics applications
  • September 20,  Thursday, 3:45pm, Zhiqing Xu, Courant Institute,Understanding training and generalization in deep learning through Fourier analysis
  • October 3, Wednesday, 3:30pm, Chia Wei Hsu, Physics, Yale, Bound states in the continuum and transmission eigenchannels in complex media
  • November 1, Thursday, 3:45 pm, Qing Nie, Math, UCI, Data-driven multiscale modeling of cell fate dynamics
  • November 8, Thursday, 3:45pm,  Ming Gu, Math, Berkeley, Advanced techniques for low-rank matrix approximation
  • November 15, Thursday, 3:45pm, Eric Michielssen, E.E., U. of Michigan, Butterfly+ Fast Direct Solvers for Highly Oscillatory Problems
  • November 29, Thursday, 3:45pm, Liliana Borcea , Math, U. of Michigan, Reduced order model for active array data processing in inverse scattering 

Spring, 2018 (126 Clements Hall)

  • February 8, Thursday, 3:45pm,   Mamikon Gulian, Applied Math, Brown, Fractional Laplacians in Bounded Domains, Levy Processes, and Feynman-Kac Formulas
  • February 22, Thursday, 3:45pm,  Prof. Jianguo Liu, Math, Duke, Analysis of some machine learning algorithms:  stochastic gradient descent and online PCA
  • March 15, Thursday, 3:45pm,  Prof. Anne Gelb, Math, Dartmouth, Reducing the effects of bad data measurements using variance based weighted joint sparsity
  • March 29, Thursday, 3:45pm, Prof. George Biros, ICES, UT Austin, Randomized linear algebra for hierarchical and kernel matrices
  • April 12, Thursday, 3:45pm,  Prof. Michael Mascagni, Math & CS, Florida State, The “White Rat” of Numerical Reproducibility
  • April 26, Thursday, 3:45pm, Prof. Lin Lin, Math, Berkeley, Accelerating Hartree-Fock-like equations

Fall, 2017 (126 Clements Hall)

  • October 18, Wednesday, 3:30pm, Prof. Alex Figotin, Math, UC Irvin, Multi-transmission-line-beam interactive system
  • October 26, Thursday, 4:00pm,  Prof. George Yin, Math, Wayne State U., Switching Diffusions and Applications
  • November 16, Thursday, 4:00pm,  Prof. Lexing Ying, Math, Stanford, Entropic spectral methods for Boltzmann equation
  • November 30, Thursday, 4:00pm, Prof. Adrianna Gillman, Math, Rice, An efficient and high order accurate direct solution technique for variable coefficient elliptic PDEs