
Arash Behboodi
@behboodiarash
Director of Engineering at Qualcomm AI research - generally interested in math related areas in AI and Info theory. Also background in philosophy.
ID: 1709592555833143296
04-10-2023 15:34:13
30 Tweet
57 Followers
102 Following



Our work on historical insights at scale using machine learning is now out in Science Advances! Very proud of this team effort, bridging disciplines and institutions—@MPIWG TU Berlin BIFOLD ML Group, TU Berlin 📜science.org/doi/10.1126/sc…


Today, we're joined by Arash Behboodi, director of engineering at Qualcomm Research & Technologies to discuss the papers and workshops Qualcomm will be presenting at the #NeurIPS2024 conference. We dig into the challenges and opportunities presented by differentiable simulation in wireless systems,

Hey everyone, I'm so excited to share my recent interview on AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Sam Charrington for the The TWIML AI Podcast podcast. Check it out! twimlai.com/go/711 via The TWIML AI Podcast

with Sam Charrington, I also talk about differentiable simulation, our D3S3 workshops and our recent paper on information theoretic approach to conformal prediction arxiv.org/abs/2405.02140 (w Alvaro Correia, Fabio Valerio Massoli and Christos Luizos), twimlai.com/go/711




Conformal prediction is doing list decoding. Want to know more? Check out our poster today at #NeurIPS2024, from 4:30 to 7:30, East hall. Alvaro Correia will present our work on an information theoretic approach to conformal prediction! I will be around too!


Great to see this Johann Brehmer, well deserved!

Our D3S3 workshop happening now at #NeurIPS2024! Prof. Anima Anandkumar talking about neural operators.




The less talked about part of AI for Science is probably AI for social science and humanities, yet bearing so many promises IMO. Cool to see such works Oliver Eberle @eberleoliver.bsky.social



As demand for inference increases due to chain-of-thought reasoning, inference-time scaling, and applied AI, the need for LLM efficiency is more important than ever. Check out this The TWIML AI Podcast podcast about Qualcomm #AI Research's LLM efficiency techniques. twimlai.com/podcast/twimla…

