Campuses:

Talks

Date Title / Speaker Event
April 22, 2019 Lecture
Thomas Hou (California Institute of Technology)
Data Science Seminar
February 08, 2019 Lecture
Karyn Sutton (The Institute for Disease Modeling)
Industrial Problems Seminar
January 28, 2019 Lecture
Guanglin Xu (University of Minnesota, Twin Cities)
Data Science Seminar
December 10, 2018 Lecture
Lori Ziegelmeier (Macalester College)
Data Science Seminar
November 29, 2018 Math Dept Colloquium Lecture
Lexing Ying (Stanford University)
Data Science Seminar
November 28, 2018 Lecture
Lexing Ying (Stanford University)
Data Science Seminar
November 26, 2018 Lecture
Lexing Ying (Stanford University)
Data Science Seminar
November 19, 2018 Lipschitz Regularized Deep Neural Networks Converge and are Robust to Adversarial Perturbations
Adam Oberman (McGill University)
Data Science Seminar
November 16, 2018 Lecture
Raye Sosseh (Seagate Technology)
Industrial Problems Seminar
November 12, 2018 Lecture
Rebecca Willett (University of Chicago)
Data Science Seminar
November 05, 2018 Lecture
Matthew Jacobs (University of California, Los Angeles)
Data Science Seminar
November 02, 2018 Lecture
Joao Montero (Medtronic)
Industrial Problems Seminar
October 29, 2018 Lecture
Pratik Chaudhari (University of California, Los Angeles)
Data Science Seminar
October 26, 2018 Generalization and regularization in deep learning for nonlinear inverse problems
Maarten De Hoop (Rice University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 26, 2018 Primal-dual algorithms and their applications
Ming Yan (Michigan State University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 26, 2018 Addressing spatial uncertainty during remote sensing data analysis
Alina Zare (University of Florida)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 On the Use of Gaussian Process Models for Problems in CubeSat Data Interpolation
Eric Miller (Tufts University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Matched-pair machine learning for hyperspectral target detection
Amanda Ziemann (Los Alamos National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Advances in Supervised and Semi-Supervised Machine Learning for Image Analysis of Multi-Modal Geospatial Imagery Data
Saurabh Prasad (University of Houston)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Novel Machine Learning Methods for Extraction of Features Characterizing Complex Datasets and Models
Velimir Vesselinov (Los Alamos National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Mapping low-fidelity physics to high-fidelity physics with Deep Learning
Felix Herrmann (Georgia Institute of Technology)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Regularization and Compression via Tensor Dictionaries
Misha Kilmer (Tufts University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 Machine Learning for Background Estimation in Multispectral Imagery
James Theiler (Los Alamos National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 Harmonization and Fusion of Global Scale Data
Nathan Longbotham (Descartes Labs, Inc.)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 GEO-AI - the birth of a new discipline
Eldad Haber (University of British Columbia)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 Space-borne SAR interferometry: Three Decades of Innovation and Problem Solving
Manoochehr Shirzaei (Arizona State University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 Learning generative models of monostatic and bistatic synthetic aperture radar imagery
Emre Ertin (The Ohio State University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 Indomitable segmentation and pooling: A new perspective on clairvoyant fusion
Alan Schaum (Naval Research Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Machine Learning in Imaging and Inverse Problems: Where is it Going?
Charles Bouman (Purdue University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 On the effectiveness of joint inversion
Jodi Mead (Boise State University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Multiscale methods for neural image processing
Tom Goldstein (University of Maryland)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Information-theoretic approaches for multiscale simulations and data assimilation
Francesca Boso (Stanford University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Machine learning in pre- and post-imaging seismic data with different roles of wave physics
Weichang Li (Aramco Services Company)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Machine Learning Applied to Discern Fault Characteristics
Paul Johnson (Los Alamos National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Inverse methods for estimating fracture transmissibilities in porous media
Clint Dawson (The University of Texas at Austin)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Geometric separation and applications to hyperspectral image analysis
Demetrio Labate (University of Houston)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Hierarchical deep generative networks for Bayesian inverse problems
Pengchuan Zhang (Microsoft Research)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Large Sample Asymptotics of Graph-based Methods in Machine Learning: Mathematical Analysis and Implications
Nicolas Garcia-Trillos (University of Wisconsin, Madison)
Data Science Seminar
October 22, 2018 Fast and Accurate Maximum-Likelihood Estimation of Parameterized Spectral Densities that Jointly Characterize Bivariate Two- Dimensional Random Fields
Frederik Simons (Princeton University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Overview of today’s joint inversion methodology and its future into the machine-learning era for geophysical imaging
Monica Maceira (Oak Ridge National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 New Techniques in Optimization and Their Applications to Deep Learning and Related Inverse Problems
Stanley Osher (University of California, Los Angeles)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 15, 2018 Lecture
Raj Nadakuditi (University of Michigan)
Data Science Seminar
October 12, 2018 Lecture
Jennifer Schumacher (3M)
Industrial Problems Seminar
October 08, 2018 A PDE Approach to a Prediction Problem Involving Randomized Strategies
Nadejda Drenska (University of Minnesota, Twin Cities)
Data Science Seminar
October 05, 2018 Sample-Based Optimal Pricing
Omar Besbes (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 05, 2018 Lecture
Krishnamurthy Iyer (Cornell University)
Forging a New Discipline: Data-driven Supply Chain Management
October 05, 2018 Where to find the next passenger on e-hailing platform? - A reinforcement learning approach
Sharon Di (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 05, 2018 Lecture
Vivek Farias (Massachusetts Institute of Technology)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Dynamic Assortment Planning under Various Discrete Choice Models
Xi Chen (New York University)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Closing the Gap: A Learning Algorithm for the Lost-Sales Inventory System with Lead Times
Cong Shi (University of Michigan)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Distributionally Robust Linear and Discrete Optimization with Marginals
Karthik Natarajan (Singapore University of Technology and Design)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Lecture
Xin Chen (University of Illinois at Urbana-Champaign)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Smart Predict, then Optimize
Adam Elmachtoub (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Approximation Algorithms for Network Revenue Management
Huseyin Topaloglu (Cornell University)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Lecture
Philip Kaminsky (University of California, Berkeley)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 A Conditional Gradient Approach for Nonparametric Estimation of Mixing Distributions
Srikanth Jagabathula (New York University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Lecture
Vineet Goyal (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Interpretable Optimal Stopping
Velibor Misic (University of California, Los Angeles)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Predicting with Proxies
Hamsa Bastani (Wharton School of the University of Pennsylvania)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Auction Design for ROI-Constrained Buyers
Ilan Lobel (New York University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Lecture
David Shmoys (Cornell University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Procurement in the twenty first century: new approaches to old problems
Awi Federgruen (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Lecture
Georgia Perakis (Massachusetts Institute of Technology)
Forging a New Discipline: Data-driven Supply Chain Management
October 01, 2018 Lecture
Tyler Whitehouse (Gigantum)
Data Science Seminar
September 28, 2018 If a tree falls in the woods and nobody hears, does it make a sound? (Or, making sure your code runs anywhere.)
Tyler Whitehouse (Gigantum)
Industrial Problems Seminar
September 24, 2018 Genetics of mRNA and Protein Expression in Large Yeast Populations
Frank Albert (University of Minnesota, Twin Cities)
Data Science Seminar
September 17, 2018 ExxonMobil information sessions for Ph.D. students
Jeremy Bedard (ExxonMobil), Alison Cozard (ExxonMobil)
Industrial Problems Seminar
September 17, 2018 The Role of the Translation Distribution in Multi-reference Alignment
William Leeb (University of Minnesota, Twin Cities)
Data Science Seminar
September 14, 2018 The Unfulfilled Fourth Industrial Revolution
Marcus Braun (DataRobot)
Industrial Problems Seminar
September 14, 2018 ExxonMobil information sessions for Ph.D. students
Jeremy Bedard (ExxonMobil), Alison Cozard (ExxonMobil)
Industrial Problems Seminar
September 13, 2018 ExxonMobil information sessions for Ph.D. students
Jeremy Bedard (ExxonMobil), Alison Cozard (ExxonMobil)
Industrial Problems Seminar
August 15, 2018 Statistics for a Computational Topologist Part II
Brittany Terese Fasy (Montana State University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Two-Parameter Persistence for Virtual Ligand Screening
Bryn Keller (Intel Corporation)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Computation with Degree-Rips Bifiltrations
Roy Zhao (University of California, Berkeley)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Software Tutorial
Michael Lesnick (Princeton University), Matthew Wright (St. Olaf College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Multiparameter Interleavings
Magnus Botnan (Vrije Universiteit Amsterdam)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Statistics for a Computational Topologist, Part I
Brittany Terese Fasy (Montana State University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Computing Minimal Presentations of Bipersistence Modules in Cubic Time
Michael Lesnick (Princeton University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Visualizing Two-parameter Persistence
Matthew Wright (St. Olaf College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Quiver Representation Theory + Multiparameter Persistence
Magnus Botnan (Vrije Universiteit Amsterdam)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Computation of Persistent Homology, Part II
Ulrich Bauer (Technical University of Munich)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Morse Theory and Persistent Homology Computation
Gregory Henselman (University of Pennsylvania)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 An Introduction to Multi-D Persistent Homology
Michael Lesnick (Princeton University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Computation of Persistent Homology, Part I
Ulrich Bauer (Technical University of Munich)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Applications of Persistence
Lori Ziegelmeier (Macalester College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Introduction to Persistent Homology
Matthew Wright (St. Olaf College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 10, 2018 Mathematics of Big Data & Machine Learning
Jeremy Kepner (Massachusetts Institute of Technology)
Data Science Seminar
June 28, 2018 Mechanical Relaxation of Incommensurate 2D Heterostructures in Configuration Space
Mitchell Luskin (University of Minnesota, Twin Cities)
Working Group on Multiscale Strategies
June 27, 2018 Stability and Convergence of the String Method
Brian Van Koten (University of Chicago)
Working Group on Multiscale Strategies
June 27, 2018 Anomalous diffusion in two homogenization problems
Gautam Iyer (Carnegie Mellon University)
Working Group on Multiscale Strategies
June 26, 2018 A Survey of Recent Results on Mass Transport
Gideon Simpson (Drexel University)
Working Group on Multiscale Strategies
June 26, 2018 Model-Form Uncertainty Quantification for Probabilistic Graphical Models and Applications to Electronic-Structure-based Chemical Kinetics
Markos Katsoulakis (University of Massachusetts)
Working Group on Multiscale Strategies
June 25, 2018 Coarse-graining out of equilibrium: from particles to dissipative PDEs
Celia Reina (University of Pennsylvania)
Working Group on Multiscale Strategies
June 25, 2018 Long time behaviour and phase transitions for the McKean-Vlasov equation
Grigorios Pavliotis (Imperial College London)
Working Group on Multiscale Strategies
June 22, 2018 Microstructure, wrinkling and origami in nematic elastomer sheets
Paul Plucinsky (University of Minnesota, Twin Cities)
Working Group on Multiscale Strategies
June 21, 2018 Symmetry, deformations and the search for unprecedented materials from first principles
Amartya Banerjee (Lawrence Berkeley National Laboratory)
Working Group on Multiscale Strategies
June 20, 2018 On fluctuations in particle systems and their scaling limits
Johannes Zimmer (University of Bath)
Working Group on Multiscale Strategies
June 20, 2018 A Hamilton-Jacobi theory for the hydrodynamic limit large deviation of nonlinear heat equation from stochastic Carleman particles
Jin Feng (University of Kansas)
Working Group on Multiscale Strategies
June 19, 2018 Mechanics using quantum mechanics
Phanish Suryanarayana (Georgia Institute of Technology)
Working Group on Multiscale Strategies
June 18, 2018 Challenges and recent progress in large-scale electronic structure calculations
Vikram Gavini (University of Michigan)
Working Group on Multiscale Strategies

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