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 
November 07, 2020 
Fields of Success  Stories from Math Alliance Alumni Julia AndersonLee (The Boeing Company), Alexander DiazLopez (Villanova University), April Harry (Rover.com), Anarina Murillo (Brown University), Roberto Soto (California State University), Oscar Vega (California State University) 
2020 Field of Dreams Conference 
November 07, 2020 
Report of the Math Alliance Leadership David Goldberg (Purdue University), Phil Kutzko (The University of Iowa), Kyndra Middleton (Howard University) 
2020 Field of Dreams Conference 
November 07, 2020 
Panel 5: Preparing for Graduate School Joe Omojola (Southern University at New Orleans), Vanessa Quiñonez (Sagrado Global), Isaac Wright (Pennsylvania State University) 
2020 Field of Dreams Conference 
November 07, 2020 
Panel 4: Preparing for your First Professional Position (graduate students) Ariel Leslie (Lockheed Martin), Leslie McClure (Drexel University), Reginald McGee (College of the Holy Cross) 
2020 Field of Dreams Conference 
November 07, 2020 
Morning Remarks Kyndra Middleton (Howard University) 
2020 Field of Dreams Conference 
November 06, 2020 
Active Community Detection with Maximal Expected Model Change Dan Kushnir (Nokia Bell Labs) 
Industrial Problems Seminar 
November 06, 2020 
Plenary Conversation 1 Ranthony Edmonds (The Ohio State University), Phil Kutzko (The University of Iowa), Victoria Uribe (Arizona State University) 
2020 Field of Dreams Conference 
November 06, 2020 
Guided Conversation 3: Mentoring Across the Continuum (faculty) Edray Goins (Pomona College), William Vélez (University of Arizona) 
2020 Field of Dreams Conference 
November 06, 2020 
Panel 3: Careers in Government and Industry Edray Goins (Pomona College), Roosevelt Johnson (Math Alliance), Calandra Moore (Department of Defense), David Murillo (American Express), Venkat Sethuraman (BristolMyers Squibb), William Vélez (University of Arizona) 
2020 Field of Dreams Conference 
November 06, 2020 
Panel 1: The Value of Undergraduate Research Experiences (undergraduate students) Alexander Barrios (Carleton College), Melissa Gonzalez (Occidental College), Zsuzsanna Szaniszlo (Valparaiso University) 
2020 Field of Dreams Conference 
November 06, 2020 
Guided Conversation 2: Best Practices for Mentoring Graduate Students (faculty) Edray Goins (Pomona College) 
2020 Field of Dreams Conference 
November 06, 2020 
Guided Conversation 1: Best Practices for Mentoring Undergraduate Students (faculty) William Vélez (University of Arizona) 
2020 Field of Dreams Conference 
November 06, 2020 
Panel 2: Maximizing Productivity in Graduate School (graduate students) Ayo Adeniran (Pomona College), Syvillia Averett (College of Coastal Georgia), Julianne Vega (Kennesaw State College) 
2020 Field of Dreams Conference 
November 06, 2020 
Welcome Remarks 
2020 Field of Dreams Conference 
November 03, 2020 
Machine Learning Methods for Solving Highdimensional Meanfield Game Systems Levon Nurbekyan (University of California, Los Angeles) 
Data Science Seminar 
October 30, 2020 
Estimating the Impact of Travel, Rest, and Playing at Home in the National Football League Tom Bliss (National Football League (NFL)) 
Industrial Problems Seminar 
October 27, 2020 
Clustering Highdimensional 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 COVID19 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 
LargeScale Semisupervised Learning via Graph Structure Learning over Highdense 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 
MultiPerspective, Simultaneous Embedding and Theoretically Guaranteed Projected Power Method for the Multiway 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 IllConditioned Gaussian Graphical Models Raghu Meka (University of California, Los Angeles) 
Theory and Algorithms in Graphbased Learning 
September 18, 2020 
Learning Discrete Graphical Models: Exact & Neural Network Assisted Methods Marc Vuffray (Los Alamos National Laboratory) 
Theory and Algorithms in Graphbased Learning 
September 18, 2020 
Learning Restricted Boltzmann Machines Ankur Moitra (Massachusetts Institute of Technology) 
Theory and Algorithms in Graphbased 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 Graphbased Learning 
September 17, 2020 
Community Detection Using Total Variation and Surface Tension Zach Boyd (University of North Carolina, Chapel Hill) 
Theory and Algorithms in Graphbased Learning 
September 17, 2020 
Vertex Nomination, Consistent Estimation, and Adversarial Modification Vince Lyzinski (University of Maryland) 
Theory and Algorithms in Graphbased Learning 
September 17, 2020 
LInfinity Variational Problems on Graphs: Applications and Continuum Limits Leon Bungert (FriedrichAlexanderUniversität ErlangenNürnberg), Tim Roith (FriedrichAlexanderUniversität ErlangenNürnberg) 
Theory and Algorithms in Graphbased Learning 
September 16, 2020 
Computational Complexity and Forbidden Graph Patterns Puck Rombach (University of Vermont) 
Theory and Algorithms in Graphbased Learning 
September 16, 2020 
BiasVariance Tradeoffs in Joint Spectral Embeddings Daniel Sussman (Boston University) 
Theory and Algorithms in Graphbased Learning 
September 16, 2020 
When Labelling Hurts: Learning to Classify LargeScale Data with Minimal Supervision Angelica AvilesRivero (University of Cambridge) 
Theory and Algorithms in Graphbased Learning 