Programs, Workshops & Conferences
2026 BIRS Workshop
Integrating Data- and Physics-Driven Methods for Decision Making under Uncertainty
Co-organized with R. White, L. L. R. Ramirez, and T. Bui-Thanh.
Casa Matematica Oaxaca, May 31 - June 5, 2026
This workshop brings together researchers from scientific computing, optimization, statistics, and machine learning to explore the integration of data-driven and physics-based methods for decision making under uncertainty. The aim is to foster new collaborations and identify open challenges at the intersection of these fields, with applications in science and engineering.
2025 CBMS AMML Conference
CBMS Conference: Research at the Interface of Applied Mathematics and Machine Learning
Co-organized with L. Cappanera, Y. He, and M. Wang.
University of Houston, December 8-12, 2025
NSF Award DMS-2430460
This NSF/CBMS Regional Research Conference focuses on research at the interface of applied mathematics and machine learning. The conference features a distinguished lecturer series alongside contributed talks and poster sessions, aiming to introduce researchers and students to cutting-edge developments at this important interface.
2025 ChAMELEON Summer School
Computational and mAthematical MEthods in machine LEarning, Optimization and iNference (ChAMELEON)
NSF Award DMS-2145845
The ChAMELEON summer school provides training in computational and mathematical methods in machine learning, optimization, and inference. It is designed for graduate students and early-career researchers seeking to deepen their understanding of the mathematical foundations underlying modern data science and scientific computing methodologies.
2023 Dagstuhl Seminar
Inverse Biophysical Modeling and Machine Learning in Personalized Oncology
Schloss Dagstuhl – Leibniz Center for Informatics, January 8-13, 2023
This Dagstuhl Seminar brought together researchers from medical imaging, biophysical modeling, inverse problems, machine learning, and oncology to discuss challenges and opportunities in personalized oncology. The seminar focused on how mathematical modeling, computational methods, and data-driven approaches can be combined to advance patient-specific diagnosis, prognosis, and treatment planning in cancer care.