Be a part of the computer science boom with #MBZUAI's Computer Science Department and acquire the skills to fill an estimated 3.5 million jobs required by 2026 (Gitnux Market Data).

[1/n] Excited to announce our tutorial on "ML Systems for Large Models & Federated Learning" #CVPR2025 with Professor Qirong Ho and Professor Samuel Horváth MBZUAI is now publicly available! Please check: The Tutorial Video: bit.ly/3PIv2MY Our Website: bit.ly/3RrO0bZ

You can now find our FjORD (NeurIPS'21 spotlight) implementation (arxiv.org/abs/2102.13451) in Flower (github.com/adap/flower/tr…)! Implemented with Samuel Horváth for the Flower Summer of Reproducibility.

Next Wednesday (Nov 15), at 1pm UTC, I will be giving a talk at Federated Learning One World Seminar (FLOW) about "The Future of #Consumer #EdgeAI #Computing". Tune in if you want to hear more on how we envision the next gen of the consumer device ecosystem. Paper pre-print: arxiv.org/abs/2210.10514

The summer #intern programme of Brave for 2024 is out! We are #hiring research sci/eng interns in our team. If pursuing a PhD and interested in #EfficientML, #DistributedML, #LLMs & on-device #measurements, reach out. Applications: brave.com/careers/?gh_ji…

I am on the job market for a Tenure Track Assistant Professor position! I work on optimization (stochastic optimization, distributed optimization, min-max problems/variational inequalities). If you are aware of some great options, please DM me. My website: eduardgorbunov.github.io

Honoured to be invited at the 2nd MBZUAI Workshop on Collaborative Learning (mbzuai-cl.github.io/2023/). I'll be covering our latest work on trainable decompositions for efficiency called Maestro (accepted at WANT-AI@NeurIPS'23). Tune in for more. Pre-print: arxiv.org/abs/2308.14929

📢: The 112th FLOW talk is on Wednesday (7th February) at **1 pm UTC**. Eduard Gorbunov (MBZUAI) will discuss "Variance Reduction is an Antidote to Byzantines." Please register to our mailing list: bit.ly/3WVplLU.

This Thursday (tomorrow), I will present our work on high-probability convergence for composite and distributed problems with heavy-tailed noise at #ICML2024. Come to the talk (Hall A1, Oral 5B Optimization 2) at 11:00 and to the poster at 11:30 - 13:00 (Hall C 4-9 #1014).

📢: The 120th FLOW talk is on Wednesday (9th October) at **5 pm UTC**. Nic Lane (Cambridge ML Systems Lab, Flower) will discuss "The Future of Large Language Models (and AI) is Federated." Please register for our mailing list at bit.ly/3WVplLU.

I am giving a FLOW talk tomorrow (via Zoom). Hopefully, I'll see many of you there!

Happy to announce our ICML Conference 2025 workshop: "The Next Wave of On-Device Learning for Foundation Models" Details👇 1/3

📣 Flower Labs visits the Mohamed bin Zayed University of Artificial Intelligence (@MBZUAI)! We are excited to announce that Research Scientist, Mohammad Naseri (Mohammad Naseri), will be visiting MBZUAI this week and giving a talk on Thursday, May 1. If you are in the area, and

We welcome submissions on efficient foundation models, on-device learning, and distributed learning to our ICML Conference workshop. Deadline: May 23rd Steve Laskaridis, Samuel Horváth, Berivan Isik, Peter Kairouz, Christina Giannoula, bilge, Angelos Katharopoulos, Martin Takac, nic lane

🚨 Deadline has been extended to May 26th! 🚨

I’m pleased to share that, starting August 1, I will be joining MBZUAI (MBZUAI) as an Assistant Professor in the Department of Statistics and Data Science. My research focuses on optimization for machine learning, with an emphasis on stochastic methods, federated learning,

Do you feel FL research is stuck with methods that do not work well in realistic scenarios? 🤔 🫵We got you! Introducing 🚀Generalized Heavy-Ball Momentum (GHBM)🚀, accepted at TMLR: the FL algorithm with both SOTA theoretical guarantees and much better empirical results. 🧵1/9

🚀 Join @MBZUAI (Abu Dhabi) to advance efficient & distributed ML! 🔹 Postdoctoral Associate — apply.interfolio.com/170202 🔹 Visiting Student — apply.interfolio.com/170203 Apply now and help shape the future of #MachineLearning. #AI #Postdoc #PhD #Careers

Looking for postdocs to join my Optimization & Machine Learning Lab @ KAUST! Write to me by the end of November 2025 if you want to apply. richtarik.org richtarik.org/i_papers.html richtarik.org/i_team.html richtarik.org/i_join.html

I am organizing "Workshop on Distributed Training in the Era of Large Models" at KAUST during November 24-26, 2025. If you have done some cool work in the area, you might want to attend. The talks are invite-only. I'll soon start sending invites. More info later!