Campuses:

Talks

Date Title / Speaker Event
March 19, 2021 Lecture
Daniel Kaslovsky (Automox)
Industrial Problems Seminar
March 02, 2021 Lecture
Jianfeng Lu (Duke University)
Data Science Seminar
February 23, 2021 Lecture
Facundo Mémoli (The Ohio State University)
Data Science Seminar
February 09, 2021 Lecture
Kenth Monsen (Telenor)
Data Science Seminar
February 02, 2021 Lecture
Wenjing Liao (Georgia Institute of Technology)
Data Science Seminar
January 29, 2021 Lecture
Hany Farag (Canadian Imperial Bank of Commerce (CIBC))
Industrial Problems Seminar
January 26, 2021 Lecture
Amir Sagiv (Columbia University)
Data Science Seminar
January 22, 2021 Lecture
Edo Liberty (HyperCube)
Industrial Problems Seminar
January 19, 2021 Lecture
Dimitris Giannakis (Courant Institute of Mathematical Sciences)
Data Science Seminar
December 15, 2020 Lecture
Barak Sober (Duke University)
Data Science Seminar
December 08, 2020 Lecture
Matthew Hirn (Michigan State University)
Data Science Seminar
December 04, 2020 Lecture
Julie Thompson (Boston Scientific)
Industrial Problems Seminar
December 01, 2020 Lecture
Xiuyuan Cheng (Duke University)
Data Science Seminar
November 24, 2020 Lecture
Gal Mishne (University of California, San Diego)
Data Science Seminar
November 17, 2020 Lecture
Alexander Cloninger (University of California, San Diego)
Data Science Seminar
November 13, 2020 Lecture
Ivana Seric (Philadelphia 76ers)
Industrial Problems Seminar
November 13, 2020 Gradient Flows in the Wasserstein Metric: From Discrete to Continuum via Regularization
Katy Craig (University of California, Santa Barbara)
Optimal Control, Optimal Transport, and Data Science
November 12, 2020 Information in Mean Field Control
Aaron Palmer (University of British Columbia)
Optimal Control, Optimal Transport, and Data Science
November 12, 2020 Prediction with Expert Advice: A PDE Perspective on a Model Problem from Online Machine Learning
Robert Kohn (New York University)
Optimal Control, Optimal Transport, and Data Science
November 12, 2020 Stochastic Methods for Optimal Transport in Machine Learning Applications
Aude Genevay (Massachusetts Institute of Technology)
Optimal Control, Optimal Transport, and Data Science
November 12, 2020 Wasserstein Control of Mirror Langevin Monte Carlo
Kelvin Shuangjian Zhang (École Normale Supérieure)
Optimal Control, Optimal Transport, and Data Science
November 11, 2020 A Fast Approach to Optimal Transport: The Back-and-forth Method
Matthew Jacobs (University of California, Los Angeles)
Optimal Control, Optimal Transport, and Data Science
November 11, 2020 Active Learning and Optimal Experimental Design
Eldad Haber (University of British Columbia)
Optimal Control, Optimal Transport, and Data Science
November 11, 2020 Optimal Control of Fluid Transport Networks
Anatoly Zlotnik (Los Alamos National Laboratory)
Optimal Control, Optimal Transport, and Data Science
November 11, 2020 Streaming Computation of Optimal Weak Transport Barycenters
Elsa Cazelles (University of Chile)
Optimal Control, Optimal Transport, and Data Science
November 10, 2020 A PDE Interpretation of Prediction with Expert Advice
Nadejda Drenska (University of Minnesota, Twin Cities)
Optimal Control, Optimal Transport, and Data Science
November 10, 2020 Natural Graph Wavelet Packets
Naoki Saito (University of California, Davis)
Data Science Seminar
November 10, 2020 Mathematical Approaches to Deep Learning: Model Uncertainty, Robustness and Regularization
Adam Oberman (McGill University)
Optimal Control, Optimal Transport, and Data Science
November 10, 2020 On The Convergence of MMD GANs: A Theory via Parametric Kernelized Gradient Flows
Youssef Mroueh (IBM)
Optimal Control, Optimal Transport, and Data Science
November 10, 2020 Deep Learning and Optimal Control
Weinan E (Princeton University)
Optimal Control, Optimal Transport, and Data Science
November 09, 2020 Summarizing and Analyzing Data using Optimal Transport
Justin Solomon (Massachusetts Institute of Technology)
Optimal Control, Optimal Transport, and Data Science
November 09, 2020 Graphical Optimal Transport
Yongxin Chen (Georgia Institute of Technology)
Optimal Control, Optimal Transport, and Data Science
November 09, 2020 Learned Adversarial Regularisers
Carola Schoenlieb (University of Cambridge (Cambridge, GB))
Optimal Control, Optimal Transport, and Data Science
November 09, 2020 The Quadratic Wasserstein Metric for Inverse Data Matching Problems
Yunan Yang (New York University)
Optimal Control, Optimal Transport, and Data Science
November 06, 2020 Active Community Detection with Maximal Expected Model Change
Dan Kushnir (Nokia Bell Labs)
Industrial Problems Seminar
November 03, 2020 Machine Learning Methods for Solving High-dimensional Mean-field Game Systems
Levon Nurbekyan (University of California, Los Angeles)
Data Science Seminar
October 30, 2020 Lecture
Tom Bliss (National Football League (NFL))
Industrial Problems Seminar
October 27, 2020 Clustering High-dimensional Data with Path Metrics: A Balance of Density and Geometry
Anna Little (The University of Utah)
Data Science Seminar
October 23, 2020 An Introduction to Image Compression, Old and New
Chris Finlay (Deep Render)
Industrial Problems Seminar
October 20, 2020 How COVID-19 has Changed the World and What the Future Holds
Michael Osterholm (University of Minnesota, Twin Cities)
Data Science Seminar
October 16, 2020 Systems Modeling in Biopharma
Helen Moore (Applied BioMath)
Industrial Problems Seminar
October 13, 2020 Geometric Methods in Statistics, Optimization, and Sampling
Tyler Maunu (Massachusetts Institute of Technology)
Data Science Seminar
October 06, 2020 Large-Scale Semi-supervised Learning via Graph Structure Learning over High-dense Points
Li Wang (University of Texas at Arlington)
Data Science Seminar
October 02, 2020 Combinatorial Algorithms for National Security
Cynthia Phillips (Sandia National Laboratories)
Industrial Problems Seminar
September 29, 2020 Multi-Perspective, Simultaneous Embedding and Theoretically Guaranteed Projected Power Method for the Multi-way Matching Problem
Vahan Huroyan (University of Arizona)
Data Science Seminar
September 25, 2020 The Technical and Organizational Challenges of Data Science
Catherine (Katy) Micek (3M)
Industrial Problems Seminar
September 22, 2020 Matrix Denoising with Weighted Loss
William Leeb (University of Minnesota, Twin Cities)
Data Science Seminar
September 18, 2020 SIAM Internship Panel
Montie Avery (University of Minnesota, Twin Cities)
Industrial Problems Seminar
September 18, 2020 Learning Ill-Conditioned Gaussian Graphical Models
Raghu Meka (University of California, Los Angeles)
Theory and Algorithms in Graph-based Learning
September 18, 2020 Learning Discrete Graphical Models: Exact & Neural Network Assisted Methods
Marc Vuffray (Los Alamos National Laboratory)
Theory and Algorithms in Graph-based Learning
September 18, 2020 Learning Restricted Boltzmann Machines
Ankur Moitra (Massachusetts Institute of Technology)
Theory and Algorithms in Graph-based Learning
September 17, 2020 On Wasserstein Gradient Flows and the Search of Neural Network Architectures
Nicolas Garcia Trillos (University of Wisconsin, Madison)
Theory and Algorithms in Graph-based Learning
September 17, 2020 Community Detection Using Total Variation and Surface Tension
Zach Boyd (University of North Carolina, Chapel Hill)
Theory and Algorithms in Graph-based Learning
September 17, 2020 Vertex Nomination, Consistent Estimation, and Adversarial Modification
Vince Lyzinski (University of Maryland)
Theory and Algorithms in Graph-based Learning
September 17, 2020 L-Infinity Variational Problems on Graphs: Applications and Continuum Limits
Leon Bungert (Friedrich-Alexander-Universität Erlangen-Nürnberg), Tim Roith (Friedrich-Alexander-Universität Erlangen-Nürnberg)
Theory and Algorithms in Graph-based Learning
September 16, 2020 Computational Complexity and Forbidden Graph Patterns
Puck Rombach (University of Vermont)
Theory and Algorithms in Graph-based Learning
September 16, 2020 Bias-Variance Tradeoffs in Joint Spectral Embeddings
Daniel Sussman (Boston University)
Theory and Algorithms in Graph-based Learning
September 16, 2020 When Labelling Hurts: Learning to Classify Large-Scale Data with Minimal Supervision
Angelica Aviles-Rivero (University of Cambridge)
Theory and Algorithms in Graph-based Learning
September 15, 2020 Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization
Yifei Lou (University of Texas at Dallas)
Theory and Algorithms in Graph-based Learning
September 15, 2020 On Anisotropic Diffusion Equations for Label Propagation
Lisa-Maria Kreusser (University of Cambridge)
Theory and Algorithms in Graph-based Learning
September 15, 2020 Graph Structure of Neural Networks
Jure Leskovec (Stanford University)
Theory and Algorithms in Graph-based Learning
September 15, 2020 Using Continuum Limits To Understand Data Clustering And Classification
Franca Hoffmann (California Institute of Technology)
Theory and Algorithms in Graph-based Learning
September 14, 2020 A Fast Graph-Based Data Classification Method with Applications to 3D Sensory Data in the Form of Point Clouds
Ekaterina Rapinchuk (Michigan State University)
Theory and Algorithms in Graph-based Learning
September 14, 2020 Reducibility and Statistical-Computational Gaps from Secret Leakage
Guy Bresler (Massachusetts Institute of Technology)
Theory and Algorithms in Graph-based Learning
September 14, 2020 Robust Group Synchronization via Cycle-Edge Message Passing
Gilad Lerman (University of Minnesota, Twin Cities)
Theory and Algorithms in Graph-based Learning
September 14, 2020 A Self-avoiding Approximate Mean Curvature Flow
Simon Masnou (Université Claude-Bernard (Lyon I))
Theory and Algorithms in Graph-based Learning
September 11, 2020 Flying High with Math
Sharon Arroyo (The Boeing Company), Shabnam Khamooshi (The Boeing Company)
Industrial Problems Seminar
September 08, 2020 Does Deep Learning Solve the Phase Retrieval Problem?
Ju Sun (University of Minnesota, Twin Cities)
Data Science Seminar
August 18, 2020 Fairness, Accountability, and Transparency: (Counter)-Examples from Predictive Models in Criminal Justice
Kristian Lum (University of Pennsylvania)
Data Science Seminar
August 04, 2020 A Network Science Approach for Controlling Epidemic Outbreaks
Anil Vullikanti (University of Virginia)
Data Science Seminar
July 15, 2020 Interview with Dr. Pamela E. Harris
Pamela Harris (Williams College)
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 14, 2020 Mentor Discussion: Effective Mentoring Skills Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 14, 2020 Student Discussion: Grad School Life Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 14, 2020 Panel Discussion Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 14, 2020 Finding and Solving My Problem – A Conversation with Dr. Adrian Coles
Adrian Coles (Eli Lilly and Company)
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 14, 2020 Introduction Activity
William Vélez (University of Arizona)
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 13, 2020 Student and Mentor Activities
Joy Dolo (Actor and Writer), John Gebretatose (Actor and Writer), Nicole Joseph (Vanderbilt University)
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
July 13, 2020 Student and Mentor Activities
Joy Dolo (Actor and Writer), John Gebretatose (Actor and Writer), Nicole Joseph (Vanderbilt University)
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop
June 23, 2020 Computational Science for COVID-19 Pandemic Planning and Response
Madhav Marathe (University of Virginia)
Data Science Seminar
June 09, 2020 Data and Models for COVID-19 Decision-Making
Forrest Crawford (Yale University)
Data Science Seminar
May 22, 2020 AI for COVID-19: An Online Virtual Care Approach
Xavier Amatriain (Curai)
Industrial Problems Seminar
May 19, 2020 Transmission Dynamics of Influenza and SARS-CoV-2: Environmental Determinants, Inference and Forecast
Jeffrey Shaman (Columbia University)
Data Science Seminar
April 26, 2020 Lecture
Bruno Sinopoli (Washington University in St. Louis)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 On the Role of Well-posedness in Homotopy Methods for the Stability Analysis of Nonlinear Feedback Systems
Randy Freeman (Northwestern University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 Using Parallel Computing Insights to Design and Analyze Control Architectures
Victor Zavala (University of Wisconsin, Madison)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 Autonomous and Resilient Control of Dynamical Systems Using Reinforcement Learning
Bahare Kiumarsi (Michigan State University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 Bridging Model-based Robust Control and Model-free Reinforcement Learning
Bin Hu (University of Illinois at Urbana-Champaign)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 Vulnerability and Robustness of Deep Reinforcement Learning Agents
Soumik Sarkar (Iowa State University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 Markov Decision Processes and Sparse Linear Regression: A Combinatorial Optimization Viewpoint
Srinivasa Salapaka (University of Illinois at Urbana-Champaign)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Long-term Fairness Implications of AI-driven Decision Making in Competitive Markets
Parinaz Ardabili (The Ohio State University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Lecture
David Rahman (University of Minnesota, Twin Cities)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Dashboard Mechanisms for Online Marketplaces
Jason Hartline (Northwestern University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Design of Information Sharing Mechanisms in Markets and Service Systems
Krishnamurthy Iyer (University of Minnesota, Twin Cities)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Strategic Political Communication Across Channels: Theory and Data
Sanmay Das (Washington University in St. Louis)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Incentivizing Collaboration in Heterogeneous Teams via Common-Pool Resource Games
Vaibhav Srivastava (Michigan State University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Security Games with Additive Utilities
Sourabh Bhattacharya (Iowa State University)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Lecture
Cedric Langbort (University of Illinois at Urbana-Champaign)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Control Synthesis under Spatiotemporal Specifications
Dimitra Panagou (University of Michigan)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Lecture
Vijay Gupta (University of Notre Dame)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 25, 2020 Developments in Computational Approaches for Model Predictive Control
Ilya Kolmanovsky (University of Michigan)
Postponed: The 9th Midwest Control and Game Theory Workshop

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