Boston Computation Club
Boston Computation Club
Max von Hippel
The Boston Computation Club is a small seminar group focused on mathematical computer science, and computational mathematics. Its name is plagiarized from the London Computation Club. Boston Computation Club meetings occur roughly every other week, on weekends, around 5pm EDT (modulo speaker availability). The usual format is a 20m presentation followed by 40m of discussion. Some, but not all, meetings are posted on YouTube and in podcast form.
Experiments with vibecoding hardware, Lewis Coriolan
Lewis Coriolan is a hacker, inventor, and entrepreneur, with wide-ranging interests. Today he joined us to talk about his experimentation vibe-coding hardware. This was a really cool talk and a glimpse at what's possible now with frontier models in hard-tech. It was also an important geopolitical conversation, as these developments severely lower the technological advantage that developed nations have over smaller countries or less well organized adversaries.
Oct 31
41 min
From percolation theory to recursive self-improvement and AI risk, Olle Häggström
Olle Häggström is a pure mathematician. Today, he joined us to tell the story of how his entire field of mathematics was essentially conquered by large language models in a short period of time, and to discuss the lessons about AI safety that he drew from this experience. This was a challenging and interesting conversation and, I think, a really compelling listen if you are not yet convinced of the imminency of AGI (or ASI).
Oct 28
55 min
Sum-check protocol: categorical view, Alex Sorokin
Alex is a friend of mine and a mathematician.  He did his PhD in mathematics with other Alex (Martsinkovsky), who has presented at the seminar group previously.  We're huge fans of both Alexes at the Boston Computation Club and we hope you enjoy this talk as much as we did!
Sep 8
46 min
P-stability for 3-uniform Hypergraphs, Daniel Yu
Today Daniel Yu gave a pure math talk on an extension he performed independently of work he had conducted during his math semester abroad in Budapest.
Sep 8
1 hr 4 min
Understanding patterns of adoption and adaptation of open models on local systems, Woohyeuk (Kevin) Lee
Today Woohyeuk (Kevin) Lee joined us to discuss local AI (and the question of just how local it really is). This is exciting work at the intersection of computer science and social science! Enjoy.
Sep 8
35 min
Cellular automata and artificial life in the deep learning era, Casey Martin
Casey Martin is a dirtbag intellectual, local savant, and recent PhD in the Boulder metro area. He's a party favorite and today he joined us to discuss cellular automata and their generalizations. Enjoy!
Sep 8
1 hr 9 min
06/26/26: Tracing Introspection Across Model Depth, Zach Maas
Zach Maas is an independent AI safety & mechanistic interpretability researcher in Boulder, Colorado, funded by Coefficient Giving. Today Zach joined us to talk about some of his recent work tracing introspection across model depth. This is, I think, the first mech interp talk we've hosted other than ChessGPT, and it was a good one! We hope you enjoy it as much as we did!
Jul 3
48 min
An Extremely Short Proof of the Hairy Ball Theorem with Peter McGrath
Today Peter McGrathAn Extremely Short Proof of the Hairy Ball Theorem. Peter is a professor of mathematics at NC State, where he researches geometric analysis, minimal surfaces, PDEs. Today's talk was an elegant presentation of the classical result -- Peter makes it accessible, and explains each concept in a clear and transparent manner. This was a really fun talk and really back to our roots as a group, doing pure math on an iPad and loving it! We hope you enjoy the talk as much as we did!
Apr 18
58 min
Logic.py: Bridging the Gap between LLMs and Constraint Solvers with Pascal Kesseli
Pascal Kesseli is a software engineer and technical lead at Microsoft AI, with a PhD in Computer Science from Oxford (or a DPhil? Or whatever they call PhDs on that side of the pond). Today Pascal joined us to discuss work he completed while at META FAIR, focused on the conjoining of large language models with symbolic reasoning systems (ultimately, dispatch to SAT) as well as future research directions building on said work.
Mar 9
57 min
2/17/26: Approximately Aligned Decoding with Daniel Melcer
Daniel Melcer is a PhD student at Northeastern University, where he researches formal methods, reinforcement learning, and large language models, among other things. Daniel also has the most colorful hair in the business (bright red for this talk, other colors for other occasions). Today he joined us to talk about some really exciting work he completed at Amazon, and to expand on his general vision of where constrained inference problems are heading in the future.
Feb 18
48 min
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