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 Burer-Monteiro 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 High-Dimensional Optimal Transport Lars Ruthotto (Emory University) |
Data Science Seminar |

April 13, 2021 |
Quantile-based 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 (Technion-Israel 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 Ben-Artzi (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 Gromov-Hausdorff and Gromov-Wasserstein 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 Cryo-EM 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 Low-dimensional 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 |
Filter-decomposed 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 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 (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 Anderson-Lee (The Boeing Company), Alexander Diaz-Lopez (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 (Bristol-Myers Squibb), William Vélez (University of Arizona) |
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 |
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 |
Welcome Remarks |
2020 Field of Dreams Conference |

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 |
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 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 |