May 03, 2022 
Free Boundary Problems on Lattices
Charles Smart (Yale University)

Data Science Seminar 
April 29, 2022 
Simplifying Federated Learning Jobs With Flame
Myungjin Lee (Cisco)

Industrial Problems Seminar 
April 26, 2022 
A Distributed Linear Solver via the Kaczmarz Algorithm
Eric Weber (Iowa State University)

Data Science Seminar 
April 19, 2022 
A Characteristicsbased Approach to Computing Tukey Depths
Martin MolinaFructuoso (North Carolina State University)

Data Science Seminar 
April 12, 2022 
How Well Can We Generalize Nonlinear Learning Models in High Dimensions??
Inbar Seroussi (Weizmann Institute of Science)

Data Science Seminar 
April 08, 2022 
Data Science in Business vs. Academia
Philippe Barbe (Paramount)

Industrial Problems Seminar 
April 05, 2022 
Method of Moments: From Sample Complexity to Efficient Implicit Computations Joao Pereira (The University of Texas at Austin) 
Data Science Seminar 
April 01, 2022 
Creating Value in PE Using Advanced Analytics
Erik Einset (Global Infrastructures Partners)

Industrial Problems Seminar 
March 29, 2022 
Relaxing Gaussian Assumptions in High Dimensional Statistical Procedures
Larry Goldstein (University of Southern California)

Data Science Seminar 
March 25, 2022 
MultiAgent Autonomy and Beyond: A Mathematician’s Life at GDMS
Ben Strasser (General Dynamics Mission Systems)

Industrial Problems Seminar 
March 22, 2022 
Using Artificial Intelligence to Model and Support the Management of Multimorbid Patients Martin Michalowski (University of Minnesota, Twin Cities) 
Data Science Seminar 
March 18, 2022 
Musings from a Computer Vision Career
Evan Ribnick (Reveal Technology)

Industrial Problems Seminar 
March 15, 2022 
Autodifferentiable Ensemble Kalman Filters
Daniel SanzAlonso (University of Chicago)

Data Science Seminar 
March 01, 2022 
On Multiclass Adversarial Training, Perimeter Minimization, and Multimarginal Optimal Transport Problems
Nicolas Garcia Trillos (University of Wisconsin, Madison)

Data Science Seminar 
February 25, 2022 
Data Science @ Meta Zeinab Takbiri (Facebook) 
Industrial Problems Seminar 
February 22, 2022 
Integrative Discriminant Analysis Methods for Multiview Data
Sandra Safo (University of Minnesota, Twin Cities)

Data Science Seminar 
February 18, 2022 
Towards a Better Evaluation of Football Players
Eric Eager (ProFootballFocus (PFF))

Industrial Problems Seminar 
February 15, 2022 
Graph Clustering Dynamics: From Spectral to Mean Shift
Katy Craig (University of California, Santa Barbara)

Data Science Seminar 
February 11, 2022 
Best Practices A Data Scientist Should Know
Hande Tuzel (Sabre Corporation)

Industrial Problems Seminar 
February 08, 2022 
Decomposing LowRank Symmetric Tensors Joe Kileel (The University of Texas at Austin) 
Data Science Seminar 
February 04, 2022 
DataModel Fusion to Predict the Impacts of Climate Change on Mosquitoborne Diseases
Carrie Manore (Los Alamos National Laboratory)

Industrial Problems Seminar 
February 01, 2022 
Stability and Generalization in Graph Convolutional Neural Networks
Ron Levie (LudwigMaximiliansUniversität München)

Data Science Seminar 
January 28, 2022 
Pointers on AI/ML Career Success
Paritosh Desai (Google Inc.)

Industrial Problems Seminar 
January 25, 2022 
Intelligent Randomized Algorithms for the Low CPRank Tensor Approximation Problem
Alex Gittens (Rensselaer Polytechnic Institute)

Data Science Seminar 
December 14, 2021 
New Methods for Disease Prediction using Imaging and Genomics
Eran Halperin (UnitedHealth Group)

Data Science Seminar 
December 10, 2021 
From Perception to Understanding: The Third Wave of AI
Tetiana Grinberg (Intel Corporation)

Industrial Problems Seminar 
December 03, 2021 
Licensed to Analyze? An InDepth Look at the Data Science Career: Defining Roles, Assessing Skills Hamit Hamutcu (Initiative for Analytics and Data Science Standards (IADSS)) 
Industrial Problems Seminar 
November 23, 2021 
The Scattering Transform for Texture Synthesis and Molecular Generation Michael Perlmutter (University of California, Los Angeles) 
Data Science Seminar 
November 19, 2021 
Certified Robustness against Adversarial Attacks in Image Classification
Fatemeh Sheikholeslami (Bosch Center for Artificial Intelligence)

Industrial Problems Seminar 
November 12, 2021 
Lessons Learned in Deploying AI in Manufacturing
Eric Wespi (Boston Scientific)

Industrial Problems Seminar 
November 09, 2021 
NonParametric Estimation of Manifolds from Noisy Data
Yariv Aizenbud (Yale University)

Data Science Seminar 
November 05, 2021 
Data Science @ Instacart
Jeffrey Moulton (Instacart)

Industrial Problems Seminar 
October 29, 2021 
Challenges in Building Intelligent Search Systems
Jiguang Shen (Microsoft Research)

Industrial Problems Seminar 
October 22, 2021 
Predicting Tomorrow: Industrial Forecasting at Scale
Jimmy Broomfield (Target Corporation)

Industrial Problems Seminar 
October 19, 2021 
Data depths meet HamiltonJacobi equations
Ryan Murray (North Carolina State University)

Data Science Seminar 
October 15, 2021 
Data Scientists under attack!! Let's help them together
Sharath Dhamodaran (OptumLabs)

Industrial Problems Seminar 
October 12, 2021 
Organizational Collaboration with Assisted Learning
Jie Ding (University of Minnesota, Twin Cities)

Data Science Seminar 
October 08, 2021 
Research and Opportunities in the Mathematical Sciences at Oak Ridge National Laboratory
Juan Restrepo (Oregon State University)

Industrial Problems Seminar 
October 05, 2021 
Scalable and SampleEfficient Active Learning for GraphBased Classification
Kevin Miller (University of California, Los Angeles)

Data Science Seminar 
October 01, 2021 
Longterm Time Series Forecasting and Data Generated by Complex Systems Kaisa Taipale (CH Robinson) 
Industrial Problems Seminar 
September 28, 2021 
Standardizing the Spectra of Count Data Matrices by Diagonal Scaling
Boris Landa (Yale University)

Data Science Seminar 
September 21, 2021 
Handling model uncertainties via informative GoodnessofFit
Sara Algeri (University of Minnesota, Twin Cities)

Data Science Seminar 
September 17, 2021 
SIAM Internship Panel Montie Avery (University of Minnesota, Twin Cities) 
Industrial Problems Seminar 
September 14, 2021 
PDEinspired Methods for Graphbased Semisupervised Learning Jeff Calder (University of Minnesota, Twin Cities) 
Data Science Seminar 
September 10, 2021 
Being Smart and Dumb: Building the Sports Analytics Industry
Dean Oliver ( NBA's Washington Wizards)

Industrial Problems Seminar 
May 18, 2021 
Measuring the Happiness, Health, & Stories of Society through the Sociotechnical Dynamics of Social Media and Fiction Chris Danforth (University of Vermont) 
Data Science Seminar 
May 04, 2021 
Order in Disorder: Modeling the Crumpling Dynamics of Thin Sheets Jovana Andrejevic (Harvard University) 
Data Science Seminar 
April 27, 2021 
Polynomial Time Guarantees for the BurerMonteiro Method Diego Cifuentes (Massachusetts Institute of Technology) 
Data Science Seminar 
April 23, 2021 
Finding Effective Spreaders for Fast Communication in Small and Large Networks Fern Hunt (National Institute of Standards and Technology) 
Industrial Problems Seminar 
April 20, 2021 
Machine Learning Techniques for HighDimensional Optimal Transport Lars Ruthotto (Emory University) 
Data Science Seminar 
April 13, 2021 
Quantilebased Iterative Methods for Corrupted Systems of Linear Equations Elizaveta Rebrova (University of California, Los Angeles) 
Data Science Seminar 
April 06, 2021 
The Ramanujan Machine: Using Algorithms for the Discovery of Conjectures on Mathematical Constants Ido Kaminer (TechnionIsrael Institute of Technology) 
Data Science Seminar 
March 30, 2021 
Deep Networks and the Multiple Manifold Problem John Wright (Columbia University) 
Data Science Seminar 
March 26, 2021 
Law  Math = Injustice: A Story of Conflict Eric BenArtzi (Gannuity) 
Industrial Problems Seminar 
March 23, 2021 
Adapting the Metropolis Algorithm Jeffrey Rosenthal (University of Toronto) 
Data Science Seminar 
March 19, 2021 
The Engineering of Data Science & The Science of Data Engineering Daniel Kaslovsky (Automox) 
Industrial Problems Seminar 
March 16, 2021 
Consistent Sparse Deep Learning: Theory and Computation Faming Liang (Purdue University) 
Data Science Seminar 
March 02, 2021 
Coordinate Methods for Solving Eigenvalue Problems in High Dimensions Jianfeng Lu (Duke University) 
Data Science Seminar 
February 26, 2021 
Data Science at The New York Times Chris Wiggins (Columbia University) 
Industrial Problems Seminar 
February 23, 2021 
Ultrametric GromovHausdorff and GromovWasserstein Distances Facundo Mémoli (The Ohio State University) 
Data Science Seminar 
February 19, 2021 
Cyber Security: A New Front for Computational Science and Engineering Ali Pinar (Sandia National Laboratories) 
Industrial Problems Seminar 
February 16, 2021 
Learning the Manifold of Molecular Structures in CryoEM Joakim Anden (Royal Institute of Technology (KTH)) 
Data Science Seminar 
February 12, 2021 
Discovering Genetic Networks Using Compressive Sensing Matthew Herman (Fourier Genetics) 
Industrial Problems Seminar 
February 09, 2021 
Coding and Generative Design for 3D Printing Laura Taalman (James Madison University) 
Public Lecture Series 
February 09, 2021 
Using Telco Data to Fight Epidemics Kenth Monsen (Telenor Research) 
Data Science Seminar 
February 05, 2021 
Manufacturing Pitfalls to Avoid in Commercialization Angelique Johnson (MEMStim LLC) 
Industrial Problems Seminar 
February 02, 2021 
Regression of Functions on Lowdimensional Manifolds by Neural Networks Wenjing Liao (Georgia Institute of Technology) 
Data Science Seminar 
January 29, 2021 
Contemporary Problems in Market Risk Modeling Hany Farag (Canadian Imperial Bank of Commerce (CIBC)) 
Industrial Problems Seminar 
January 26, 2021 
An Optimal Transport Perspective on Uncertainty Propagation Amir Sagiv (Columbia University) 
Data Science Seminar 
January 22, 2021 
The Rise of the Vector Database Edo Liberty (Pinecone) 
Industrial Problems Seminar 
January 19, 2021 
Quantum Compiler for Classical Dynamical Systems Dimitris Giannakis (Courant Institute of Mathematical Sciences) 
Data Science Seminar 
January 12, 2021 
What We Talk About When We Talk About Math Lillian Pierce (Duke University) 
Public Lecture Series 
December 15, 2020 
Estimation of Manifolds from Point Clouds: Building Models from Data Barak Sober (Duke University) 
Data Science Seminar 
December 11, 2020 
COVID Modeling: Testing Scenarios and Geographical Networks Natalie Sheils (UnitedHealth Group) 
Industrial Problems Seminar 
December 08, 2020 
Understanding Convolutional Neural Networks Through Signal Processing Matthew Hirn (Michigan State University) 
Data Science Seminar 
December 04, 2020 
Digital Health Technology for Heart Failure Diagnostic Monitoring Julie Thompson (Boston Scientific) 
Industrial Problems Seminar 
December 01, 2020 
Filterdecomposed Convolution in Deep Neural Networks: On Groups, Graphs, and Across Domains Xiuyuan Cheng (Duke University) 
Data Science Seminar 
November 24, 2020 
Multiway Tensor Analysis with Neuroscience Applications Gal Mishne (University of California, San Diego) 
Data Science Seminar 
November 17, 2020 
Fast Statistical and Geometric Distances Between Families of Distributions Alexander Cloninger (University of California, San Diego) 
Data Science Seminar 
November 13, 2020 
The Evolution of Basketball with Data Science 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 Backandforth 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 (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 
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 07, 2020 
Concluding Remarks David Goldberg (Purdue University), Phil Kutzko (The University of Iowa), Oscar Vega (California State University) 
2020 Field of Dreams Conference 
November 07, 2020 
Plenary Conversation II Donald Cole (University of Mississippi), David Goldberg (Purdue University), Fabrice Ulysse (University of Notre Dame), Oscar Vega (California State University) 
2020 Field of Dreams Conference 