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 |
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 |
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 |
The Quadratic Wasserstein Metric for Inverse Data Matching Problems Yunan Yang (New York 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 |
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 |
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 |
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 |
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 |
October 08, 2019 |
Parallel Transport Convolutional Neural Networks on Manifolds Rongjie Lai (Rensselaer Polytechnic Institute) |
Data Science Seminar |
September 24, 2019 |
The Geometry of Ambiguity in One-dimensional Phase Retrieval Dan Edidin (University of Missouri) |
Data Science Seminar |
September 03, 2019 |
Where and What to Look: Learning to Understand the Visual World in Autistic Brains Catherine Zhao (University of Minnesota, Twin Cities) |
Data Science Seminar |
February 11, 2020 |
Function Space Metropolis-Hastings Algorithms with Non-Gaussian Priors Bamdad Hosseini (California Institute of Technology) |
Data Science Seminar |
October 15, 2019 |
Simple Approaches to Complicated Data Analysis Deanna Needell (University of California, Los Angeles) |
Data Science Seminar |
November 19, 2019 |
Robust Representation for Graph Data Dongmian Zou (University of Minnesota, Twin Cities) |
Data Science Seminar |
December 03, 2019 |
Exploiting Group and Geometric Structures for Massive Data Analysis Zhizhen (Jane) Zhao (University of Illinois at Urbana-Champaign) |
Data Science Seminar |
February 25, 2020 |
Making Small Spaces Feel Large: Practical Illusions in Virtual Reality Evan Rosenberg (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 |
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 |
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 |
May 19, 2020 |
Transmission Dynamics of Influenza and SARS-CoV-2: Environmental Determinants, Inference and Forecast Jeffrey Shaman (Columbia 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 |
August 04, 2020 |
A Network Science Approach for Controlling Epidemic Outbreaks Anil Vullikanti (University of Virginia) |
Data Science Seminar |
June 09, 2020 |
Data and Models for COVID-19 Decision-Making Forrest Crawford (Yale University) |
Data Science Seminar |
March 03, 2020 |
“Living” 3D World Models Leveraging Crowd Sourced Data Jan-Michael Frahm (Facebook) |
Data Science Seminar |
June 23, 2020 |
Computational Science for COVID-19 Pandemic Planning and Response Madhav Marathe (University of Virginia) |
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 11, 2019 |
Data Science in Healthcare Yinglong Guo (UnitedHealth Group) |
Industrial Problems Seminar |
October 03, 2019 |
Language and Interaction in Minecraft Arthur Szlam (Facebook) |
Industrial Problems Seminar |
November 15, 2019 |
Pipelines, Graphs, and the Language of Shopping: Architecting Next Gen Machine Learning Capabilities for Retail Jonah White (Best Buy) |
Industrial Problems Seminar |
February 28, 2020 |
Some Characteristics of Research in Finance Onur Ozyesil (Helm.ai) |
Industrial Problems Seminar |
May 22, 2020 |
AI for COVID-19: An Online Virtual Care Approach Xavier Amatriain (Curai) |
Industrial Problems Seminar |
October 25, 2019 |
Gamma Guidance - The Mathematics Applied to a Launch Vehicle Gary Green (The Aerospace Corporation) |
Industrial Problems Seminar |
February 21, 2020 |
Profiles of Math Careers in the Industry Martin Lacasse (ExxonMobil) |
Industrial Problems Seminar |
September 27, 2019 |
Sampling from an Alternate Universe: Overview of Privacy-preserving Synthetic Data Christine Task (Knexus Research Corporation) |
Industrial Problems Seminar |
January 31, 2020 |
How NextEra Analytics Applies Math to Problems in Coupled Renewable and Energy Storage Systems Madeline Handschy (NextEra Analytics Inc) |
Industrial Problems Seminar |
October 11, 2019 |
Preparation for the MinneMUDAC Competition: Principals of Agricultural Economics I Tim Bodin (Cargill, Inc.) |
Industrial Problems Seminar |
October 11, 2019 |
Preparation for the MinneMUDAC Competition: On Predicting Commodity Closing Prices for Soybeans Kylie Mitchell (Cargill, Inc.) |
Industrial Problems Seminar |
November 22, 2019 |
Machine Learning Problems at Target Mauricio Flores (Target Corporation) |
Industrial Problems Seminar |
October 18, 2019 |
Preparation for the MinneMUDAC Competition: Principals of Agricultural Economics II Tim Bodin (Cargill, Inc.) |
Industrial Problems Seminar |
September 17, 2019 |
Nonlinear PDEs and regularization in machine learning Jeff Calder (University of Minnesota, Twin Cities) |
Recent Progress in Foundational Data Science |
September 16, 2019 |
Envelope Methods Dennis Cook (University of Minnesota, Twin Cities) |
Recent Progress in Foundational Data Science |
September 16, 2019 |
ML under a Modern Optimization Lens Dimitris Bertsimas (Massachusetts Institute of Technology) |
Recent Progress in Foundational Data Science |
September 16, 2019 |
Functional data analysis for activity profiles from wearable devices Ian McKeague (Columbia University) |
Recent Progress in Foundational Data Science |
September 16, 2019 |
Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation Runze Li (The Pennsylvania State University) |
Recent Progress in Foundational Data Science |
September 17, 2019 |
Gaussian Complexity, Metric Entropy, and the Statistical Learning of Deep Nets Andrew Barron (Yale University) |
Recent Progress in Foundational Data Science |
June 26, 2019 |
Very Tiny Knots in Nature
Kenneth Millett (University of California, Santa Barbara)
|
Public Lecture Series |
June 07, 2019 |
Panel Discussion: Emerging Opportunities for Applied Statistics and Quantitative Finance PhDs |
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop |
June 07, 2019 |
Student Activity: Finding your Focus in Graduate School Roy Araiza (Purdue University), Ty Frazier (University of Minnesota, Twin Cities), Richard McGehee (University of Minnesota, Twin Cities), Adrienne Sands (University of Minnesota, Twin Cities) |
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop |
June 07, 2019 |
Mentor Activity: Creating an Action Plan Joe Omojola (Southern University at New Orleans), William Vélez (University of Arizona) |
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop |
June 06, 2019 |
Introduction and Overview William Vélez (University of Arizona) |
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop |
June 06, 2019 |
Data Science: What is it? Why is everyone talking about it? Should you be doing it? (You probably are already) Rebecca Nugent (Carnegie Mellon University) |
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop |
June 06, 2019 |
Student Activity: Support Your vocals like Destiny's Child supported Beyonce Joy Dolo (Actor and Writer), John Gebretatose (Actor and Writer) |
Career Paths in the Mathematical Sciences: An IMA / Math Alliance Workshop |