During 2026–27, the CMSA will host a seminar on New Technologies in Mathematics, organized by Michael Douglas and Luca Pesce. This seminar will take place on Wednesdays from 2:00 pm–3:00 pm (Eastern Time). The meetings will take place in Room G10 at the CMSA, 20 Garden Street, Cambridge MA 02138, and some meetings will take place virtually on Zoom or be held in hybrid formats. To learn how to attend, join the seminar mailing list or contact Michael Douglas (mdouglas@cmsa.fas.harvard.edu).
The schedule will be updated as talks are confirmed.
Seminar videos can be found at the CMSA Youtube site: New Technologies in Mathematics Playlist
Speaker: William Hamilton, McGill University and MILA Title: Graph Representation Learning: Recent Advances and Open Challenges Abstract: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum […]
https://youtu.be/bjRqmlI_SFs Speaker: Andrea Montanari, Departments of Electrical Engineering and Statistics, Stanford Title: Self-induced regularization from linear regression to neural networks Abstract: Modern machine learning methods --most noticeably multi-layer neural networks-- […]
Speaker: Jeffrey Pennington, Google Brain Title: Triple Descent and a Fine-Grained Bias-Variance Decomposition Abstract: Classical learning theory suggests that the optimal generalization performance of a machine learning model should occur […]
https://youtu.be/aVB1qFPeEmo Speakers: Boaz Barak and Yamini Bansal, Harvard University Dept. of Computer Science Title: Generalization bounds for rational self-supervised learning algorithms, or "Understanding generalizations requires rethinking deep learning" Abstract: The […]
https://youtu.be/uUUeTYzMu0Q Speaker: Florent Krzakala, EPFL Title: Some exactly solvable models for machine learning via Statistical physics Abstract: The increasing dimensionality of data in the modern machine learning age presents new […]
https://youtu.be/t4xRwWxTzSg Speaker: Eric Mjolsness, Departments of Computer Science and Mathematics, UC Irvine Title: Towards AI for mathematical modeling of complex biological systems: Machine-learned model reduction, spatial graph dynamics, and symbolic […]
https://youtu.be/zj_Xc2QG-vw Speaker: Yang-Hui He, Oxford University, City University of London and Nankai University Title: Universes as Big Data, or Machine-Learning Mathematical Structures Abstract: We review how historically the problem of […]
Speaker: James Gray - Virginia Tech Title: Machine learning and su(3) structures on six manifolds Abstract: In this talk we will discuss the application of Machine Learning techniques to obtain numerical […]
https://youtu.be/UnYrWuOzOlc Speaker: Josef Urban, Czech Technical University Title: AI and Theorem Proving Abstract: The talk will discuss the main approaches that combine machine learning with automated theorem proving and automated […]
Speaker: Christian Szegedy Title: Language Modeling for Mathematical Reasoning Abstract: In this talk, I will summarize the current state of the art of transformer based language models and give examples on […]
Speaker: Carl Allen and Ivana Balažević - University of Edinburgh School of Informatics Title: Knowledge graph representation: From recent models towards a theoretical understanding Abstract: Knowledge graphs (KGs), or knowledge bases, are […]
https://youtu.be/OoimTbnSe7I Speaker: Nikunj Saunshi, Dept. of Computer Science, Princeton University Title: A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks Abstract: Autoregressive language models pretrained on large corpora […]