Campuses:

Talks

Date Title / Speaker Eventsort ascending
November 13, 2020 The Evolution of Basketball with Data Science
Ivana Seric (Philadelphia 76ers)
Industrial Problems Seminar
September 25, 2020 The Technical and Organizational Challenges of Data Science
Catherine (Katy) Micek (3M)
Industrial Problems Seminar
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 14, 2020 Introduction Activity
William Vélez (University of Arizona)
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 Panel Discussion 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 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 Student Discussion: Grad School Life 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
February 03, 2020 On the Final Frontiers in Computational Mathematics
Anders Hansen (University of Cambridge (Cambridge, GB))
IMA Prize Lecture
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 25, 2020 Developments in Computational Approaches for Model Predictive Control
Ilya Kolmanovsky (University of Michigan)
Postponed: The 9th Midwest Control and Game Theory Workshop
April 26, 2020 Lecture
Bruno Sinopoli (Washington University in St. Louis)
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 Control Synthesis under Spatiotemporal Specifications
Dimitra Panagou (University of Michigan)
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 Security Games with Additive Utilities
Sourabh Bhattacharya (Iowa State University)
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 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 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 Dashboard Mechanisms for Online Marketplaces
Jason Hartline (Northwestern 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 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 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 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 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 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 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 07, 2020 Lecture
Kaylee Schwertfeger (University of Minnesota, Twin Cities)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Developing experimental and mathematical models to measure changes in tumor associate macrophage polarization in response to immunotherapy
Elizabeth Wayne (Carnegie Mellon University)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Microenvironmental barriers to immune effector cell infiltration and activity in PDA
Rolf Brekken (UT Southwestern Medical Center)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Lecture
Eugene Koay (University of Texas M. D. Anderson Cancer Center)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Wrap-up Discussion CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 08, 2020 A New Mouse Model Provides Insight Into the Ductal Cell Origin and Microenvironment of Human PDAC
Daniel Billadeau (Mayo Clinic)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 08, 2020 Lecture
Paul Macklin (Indiana University)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 08, 2020 Moving Engineered Organotypic Models Towards the Clinic
David Beebe (University of Wisconsin, Madison)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Opening Remarks and Barriers to Progress
Paolo Provenzano (University of Minnesota, Twin Cities)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Countering Exhaustion in T Cell Immunotherapy
Lance Kam (Columbia University)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Experimental and Computational Approaches to Study Heterogeneity in Dormancy Induction
Samira Azarin (University of Minnesota, Twin Cities)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Lecture
W. Gregory Sawyer (University of Florida)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Enhancing T Cell Migration through Structurally and Mechanically Complex Tumor Microenvironments
Paolo Provenzano (University of Minnesota, Twin Cities)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Lecture
Alexander Anderson (Moffitt Cancer Center)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Model systems toward understanding metastasis and overcoming drug resistance of breast cancer
Shelly Peyton (University of Massachusetts)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Lecture
Edna Cukierman (Fox Chase Cancer Center)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 06, 2020 Wrap-up Discussion CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
April 07, 2020 Tumor-Matrix Interactions in Early Ductal Invasions: integrating histology, mechanobiology and computational modeling
Katarzyna (Kasia) Rejniak (Moffitt Cancer Center)
CANCELED: Quantitative Analysis and Mathematical Modeling to Capture Complex Dynamics of the Tumor Microenvironment
November 09, 2020 Learned Adversarial Regularisers
Carola Schoenlieb (University of Cambridge (Cambridge, GB))
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 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 Mathematical Approaches to Deep Learning: Model Uncertainty, Robustness and Regularization
Adam Oberman (McGill University)
Optimal Control, Optimal Transport, and Data Science
November 11, 2020 Streaming Computation of Optimal Weak Transport Barycenters
Elsa Cazelles (Institut de Recherche en Informatique de Toulouse)
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 Deep Learning and Optimal Control
Weinan E (Princeton University)
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 Active Learning and Optimal Experimental Design
Eldad Haber (University of British Columbia)
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 12, 2020 Wasserstein Control of Mirror Langevin Monte Carlo
Kelvin Shuangjian Zhang (École Normale Supérieure)
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 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 Information in Mean Field Control
Aaron Palmer (University of British Columbia)
Optimal Control, Optimal Transport, and Data Science
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 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 The Quadratic Wasserstein Metric for Inverse Data Matching Problems
Yunan Yang (New York University)
Optimal Control, Optimal Transport, and Data Science
September 15, 2020 On Anisotropic Diffusion Equations for Label Propagation
Lisa-Maria Kreusser (University of Cambridge)
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 16, 2020 Bias-Variance Tradeoffs in Joint Spectral Embeddings
Daniel Sussman (Boston University)
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 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 17, 2020 Vertex Nomination, Consistent Estimation, and Adversarial Modification
Vince Lyzinski (University of Maryland)
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 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 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 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 18, 2020 Learning Restricted Boltzmann Machines
Ankur Moitra (Massachusetts Institute of Technology)
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 14, 2020 A Self-avoiding Approximate Mean Curvature Flow
Simon Masnou (Université Claude-Bernard (Lyon I))
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 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 18, 2020 Learning Ill-Conditioned Gaussian Graphical Models
Raghu Meka (University of California, Los Angeles)
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
February 04, 2020 Different Aspects of Registration Problem
Yuehaw Khoo (University of Chicago)
Data Science Seminar
November 26, 2019 Information Flow and Security Aspects in 1-2-1 Networks
Martina Cardone (University of Minnesota, Twin Cities)
Data Science Seminar
December 06, 2019 Probabilistic Preference Learning with the Mallows Rank Model for Incomplete Data
Arnoldo Frigessi (Oslo University Hospital)
Data Science Seminar
November 12, 2019 Latent Factor Models for Large-scale Data
Xiaoou Li (University of Minnesota, Twin Cities)
Data Science Seminar
May 19, 2020 Transmission Dynamics of Influenza and SARS-CoV-2: Environmental Determinants, Inference and Forecast
Jeffrey Shaman (Columbia University)
Data Science Seminar
November 05, 2019 Topics in Sparse Recovery via Constrained Optimization: Least Sparsity, Solution Uniqueness, and Constrained Exact Recovery
Seyedahmad Mousavi (University of Minnesota, Twin Cities)
Data Science Seminar
September 17, 2019 Optimal Recovery under Approximability Models, with Applications
Simon Foucart (Texas A & M University)
Data Science Seminar
September 10, 2019 Taming Nonconvexity: From Smooth to Nonsmooth Problems and Beyond
Ju Sun (University of Minnesota, Twin Cities)
Data Science Seminar
June 09, 2020 Data and Models for COVID-19 Decision-Making
Forrest Crawford (Yale University)
Data Science Seminar
August 04, 2020 A Network Science Approach for Controlling Epidemic Outbreaks
Anil Vullikanti (University of Virginia)
Data Science Seminar
June 23, 2020 Computational Science for COVID-19 Pandemic Planning and Response
Madhav Marathe (University of Virginia)
Data Science Seminar
March 03, 2020 “Living” 3D World Models Leveraging Crowd Sourced Data
Jan-Michael Frahm (Facebook)
Data Science Seminar
October 29, 2019 Highly Likely Clusterable Data With No Cluster
Mimi Boutin (Purdue University)
Data Science Seminar
October 01, 2019 Citizen Science and Machine Learning at Zooniverse
Darryl Wright (University of Minnesota, Twin Cities)
Data Science Seminar
October 22, 2019 Convergence Rates and Semiconvexity Estimates for the Continuum Limit of Nondominated Sorting
Brendan Cook (University of Minnesota, Twin Cities)
Data Science Seminar
January 21, 2020 Linear Unbalanced Optimal Transport
Matthew Thorpe (University of Cambridge)
Data Science Seminar
February 18, 2020 From Clustering with Graph Cuts to Isoperimetric Inequalities: Quantitative Convergence Rates of Cheeger Cuts on Data Clouds
Nicolas Garcia Trillos (University of Wisconsin, Madison)
Data Science Seminar
January 28, 2020 SEMINAR IS CANCELED - Machine Learning Meets Societal Values

Steven Wu (University of Minnesota, Twin Cities) - SEMINAR IS CANCELED

Data Science Seminar

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