During 2024–25, the CMSA will host a seminar on New Technologies in Mathematics, organized by Michael Douglas and Samy Jelassi. 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, please fill out this form, 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

From Word Prediction to Complex Skills: Data Flywheels for Mathematical Reasoning

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

https://youtu.be/OYOuSAAE7QQ New Technologies in Mathematics Seminar Speaker: Anirudh Goyal (University of Montreal) Title: From Word Prediction to Complex Skills: Data Flywheels for Mathematical Reasoning Abstract: This talk examines how large language models (LLMs) evolve from simple word prediction to complex skills, with a focus on mathematical problem solving. A major driver of AI products today is the […]

How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

https://youtu.be/C6NDdnSaluU New Technologies in Mathematics Seminar Speaker: Aryo Lotfi (EPFL) Title: How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad Abstract: Can Transformers predict new syllogisms by composing established ones? More generally, what type of targets can be learned by such models from scratch? Recent works show that Transformers can be Turing-complete in terms of […]

Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

https://youtu.be/KOgh-FFDlvg New Technologies in Mathematics Seminar Speaker: Dylan Foster, Microsoft Research Title: Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning Abstract: Imitation learning (IL) aims to mimic the behavior of an expert in a sequential decision making task by learning from demonstrations, and has been widely applied to robotics, autonomous driving, and autoregressive language […]

Frontier of Formal Theorem Proving with Large Language Models: Insights from the DeepSeek-Prover Series

Virtual

https://youtu.be/qC60ZgsIFvk New Technologies in Mathematics Seminar Speaker: Huajian Xin, DeepSeek Title: Frontier of Formal Theorem Proving with Large Language Models: Insights from the DeepSeek-Prover Series Abstract: Recent advances in large language models have markedly influenced mathematical reasoning and automated theorem proving within artificial intelligence. Yet, despite their success in natural language tasks, these models face notable obstacles […]

Thinking Like Transformers – A Practical Session

Virtual

New Technologies in Mathematics Seminar Speaker: Gail Weiss, EPFL Title: Thinking Like Transformers - A Practical Session Abstract: With the help of the RASP programming language, we can better imagine how transformers---the powerful attention based sequence processing architecture---solve certain tasks. Some tasks, such as simply repeating or reversing an input sequence, have reasonably straightforward solutions, […]

Can Transformers Reason Logically? A Study in SAT-Solving

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

https://youtu.be/o7uac6DuzcQ New Technologies in Mathematics Seminar Speaker: Leyan Pan, Georgia Tech Title: Can Transformers Reason Logically? A Study in SAT-Solving Abstract: Transformer-based LLMs have apparently demonstrated capabilities that resembles human reasoning. In our recent work, we investigated the Boolean reasoning abilities of decoder-only Transformers equipped with Chain-of-Thought, establishing that a Transformer model can decide all […]

Discovering Data Structures: Nearest Neighbor Search and Beyond

Virtual

https://youtu.be/_BgheUBw_Lw New Technologies in Mathematics Seminar Speaker: Omar Salemohamed, Mila Title: Discovering Data Structures: Nearest Neighbor Search and Beyond Abstract: As neural networks learn increasingly sophisticated tasks—from image recognition to mastering the game of Go—we ask: can deep learning discover data structures entirely from scratch? We introduce a general framework for data structure discovery, which adapts to […]

Datasets for Math: From AIMO Competitions to Math Copilots for Research

Virtual

New Technologies in Mathematics Seminar Speaker: Simon Frieder, Oxford Title: Datasets for Math: From AIMO Competitions to Math Copilots for Research Abstract: This talk begins with a brief exposition of the AI Mathematical Olympiad (AIMO) on Kaggle, now in its second iteration, outlining datasets and models available to contestants. Taking a broader perspective, I then examine 1) […]

Machine Learning G2 Geometry

Hybrid

https://youtu.be/3gRquXqwtU8 New Technologies in Mathematics Seminar Speaker: Elli Heyes, Imperial College Title: Machine Learning G2 Geometry Abstract: Compact Ricci-flat Calabi-Yau and holonomy G2 manifolds appear in string and M-theory respectively as descriptions of the extra spatial dimensions that arise in the theories. Since 2017 machine-learning techniques have been applied extensively to study Calabi-Yau manifolds but until […]

Discovery in Mathematics with Automated Conjecturing

Hybrid - G10

https://youtu.be/2tmmafZxBIw New Technologies in Mathematics Seminar Speaker: Randy Davila, RelationalAI and Rice University Title: Discovery in Mathematics with Automated Conjecturing Abstract: Automated conjecturing is a form of artificial intelligence that applies heuristic-driven methods to mathematical discovery. Since the late 1980s, systems such as Fajtlowicz’s Graffiti, DeLaViña’s Graffiti.pc, and TxGraffiti have collectively contributed to over 130 publications in […]

AlphaProof: when reinforcement learning meets formal mathematics

Virtual

https://youtu.be/TFBzP78Jp6A New Technologies in Mathematics Seminar Speaker: Thomas Hubert (Google DeepMind) Title: AlphaProof: when reinforcement learning meets formal mathematics Abstract: Galileo, the renowned Italian astronomer, physicist, and mathematician, famously described mathematics as the language of the universe. Progress since only confirmed his intuition as the world we live in can be described with extreme precision […]

Learning Dynamical Transport without Data

CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

New Technologies in Mathematics Seminar Speaker: Michael Albergo (Harvard) Title: Learning Dynamical Transport without Data Abstract: Algorithms based on dynamical transport of measure, such as score-based diffusion models, have resulted in great progress in the field of generative modeling. However, these algorithms rely on access to an abundance of data from the target distribution. A […]