Meet with Modal @ NeurIPS
Infrastructure for research that moves fast.
Modal is heading to NeurIPS 2025, the leading conference for machine learning research and innovation.
We’re joining thousands of researchers, engineers, and practitioners exploring the frontiers of AI; from foundation models to optimization, multimodal systems, and beyond.
RSVP on Luma to:
Book a 1:1 with our Modal experts via this page for deeper technical discussions (we'll reach out to you!)
Secure a special Modal GPU themed swag
Where to Meet with Modal
Tuesday 12/2 to Friday 12/5 - Kiosk 9 on the showfloor
Tuesday, 12/2- AI Leadership Dinner Hosted by Modal and Encord [Full] RSVP here for the waitlist -> https://luma.com/mogw4x6l
Thursday, 12/4 - Happy Hour with New Theory -> RSVP here https://partiful.com/e/mfyx2JGs7AZwv3PXv18I
Friday, 12/5 - AI Leaders Luncheon hosted by Erik, CEO of Modal and Akshat, CTO of Modal -> RSVP here https://luma.com/sfup0j3g
Saturday, 12/6 - ML for Systems Happy Hour after the Saturday workshops with Gemini and Preference Model. RSVP here -> https://luma.com/92xgoogm
🧑🔬 Meet the Modal Research Team
Akshat Bubna — Co-Founder & CTO
Co-founder and CTO at Modal, building AI infrastructure that developers actually enjoy using. Previously Staff SWE at Scale AI; MIT Math + CS alum and former IOI medalist. Thinks obsessively about developer experience, tight feedback loops, and making agents and humans equally productive on modern compute stacks.
Dr. Charles Frye - Developer Advocate
PhD in Neuroscience from UC Berkeley; former educator at Weights & Biases and The Full Stack. Known for deep dives like “Reverse-engineering FlashAttention-4.” Author of the https://modal.com/gpu-glossary/readme
Dr. Ben Shababo - Forward-Deployed ML Engineer
PhD in Neuroscience from UC Berkeley, advisors: Hillel Adesnik, Liam Paninski (Columbia); formerly Loyal and Science Corporation. Computational scientist and builder who lives at the intersection of statistics, machine learning, and real-world instrumentation. Domain expert in ML for real-time, voice, and comp. bio use cases.
Dr. Benjamin Cowen — Forward-Deployed ML Engineer
Former Assistant Research Professor in Electrical Engineering (NYU PhD) with deep experience in acoustic/oceanic sensing and unrolled/ADMM-style optimization methods, plus stints spanning NVIDIA AV, national-lab science, and applied ML. At Modal, focuses on performance engineering and system design for high-throughput ML workloads.
Jason Mancuso — Forward-Deployed ML Engineer
Former research engineer at Cape Privacy (Dropout Labs) and contributor to OpenMined / PySyft.
Timothy Feng — Member of Technical Staff
Pushing the frontier of open-source LLM inference through top-down performance engineering. Former Together AI research intern, MIT CS/EE alum, and longtime competitive programmer (2× IOI gold), into building cool, fast systems that make models fly.