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thinking about distributed and collaborative ml 🤔


ML Research @ University of Cambridge & Flower Labs;
community lead: ml-theory @ cohere labs.

Updates

  • 🏅 July 2026: Received ICML 2026 Gold Reviewer Award.
  • 📰 🇰🇷 July 2026: LorDO accepted to ICML 2026. See you in Seoul.
  • 📰 🇧🇷 April 2026: MT-DAO and DES-LOC accepted to ICLR 2026. See you in Rio.
  • 📰 🇩🇪 March 2026: Panza accepted to CPAL 2026. See you in Tubingen.

Research
Read research overview

At present, my machine learning interests are centred around distributed, efficient and collaborative machine learning. In particular, I have a great affinity towards paradigms such as federated learning and neural network compression, and the interplay this has with optimisation theory. Generally speaking, the motivating factor for this is that I am circumspect towards the promise of centralised machine learning paradigms, which require enormous amounts of data and computational resources to achieve their state-of-the-art performance. Instead, I believe that there is much benefit to be derived from investigating alternate paradigms that can scale while promoting privacy inherently, supported by sound mathematical foundations.

If you find any of my research interesting, or you would like to collaborate on any ideas, please do not hesitate to reach out.

year title authors tags paper code misc
2026 The Red Queen Gödel Machine: Co-Evolving Agents and Their Evaluators iacob, jovanović, shen, burkhardt, kurmanji, tastan, sani, venanzi, odonnat, cao, marino, qiu, lane 🤖 arXiv
2026 FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs sani, cao, kurmanji, iacob, jovanovic, gao, zhao, lane 🌳🌀 arXiv
2026 PreLort: Prefix-Nested LoRA for Federated Fine-Tuning under Rank Heterogeneity waseem, tastan, jovanovic, lane, lukas, nandakumar, horvath 🌳🌀 arXiv
2026 LoRDO: Distributed Low-Rank Optimization with Infrequent Communication jovanović, iacob, safaryan, modoranu, sani, shen, qiu, alistarh, lane 🌳📈 ICML 2026
2025 MT-DAO: Multi-Timescale Distributed Adaptive Optimizers with Local Updates iacob, jovanović, safaryan, kurmanji, sani, horváth, shen, qiu, lane 🌳📈 ICLR 2026 top 3% of papers
2025 DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models iacob, sani, safaryan, giampouras, horváth, jovanović, kurmanji, aleksandrov, shen, qiu, lane 🌳📈 ICLR 2026 top 5% of papers
2025 Position: It's Time to Act on the Risk of Efficient Personalized Text Generation iofinova, jovanović, alistarh, 🔖 arxiv
2025 Panza: Design and Analysis of a Fully-Local Personalized Text Writing Assistant nicolicioiu, iofinova, jovanović, kurtic, nikdan, panferov, markov, shavit, alistarh 💻🗣️🌀 CPAL 2026 and ICLR 2025 Workshop on Foundation Models in the Wild bonus video
2024 Second-Order Optimisation and Imbalanced Class Distribution in Emotional Analysis jovanović 🌀📈 MPhil Thesis @ Cambridge
2023 Rumour Detection in the Wild: A Browser Extension for Twitter jovanović & ross 💻🗣️🌀 NLP-OSS @ EMNLP2023 ACL
2023 EDAC: Efficient Deployment of Audio Classification Models For COVID-19 Detection jovanović*, mihaly* & donaldson* 🌳🌀 arxiv preprint
More info... Awarded second place IBM prize in MLP course awards at UoE.

education

experience

  • camlsys and flower labs logos

    May 2025 - Present

    research assistant and research scientist intern | camlsys & flower labs

    Conducting research focusing on federated learning applied to the (pre)training of large scale models.

  • DAS logo

    Oct 2024 - March 2025

    research assistant | institute of science and technology austria Alistarh Group

    Working as a research assistant under the supervision of Dan Alistarh in the Distributed Algorithms and Systems (DAS) group focusing on compressed federated (pre)training of foundation models.

  • Summer 2023 - Summer 2023

    app. ai research intern | jp morgan chase & co. (Applied Innovation of Artificial Intelligence (AI2))

    Developed unsupervised learning methods, with an associated parallel data processing pipeline, for anomaly detection which increased previous performance by 30%.

  • Summer 2022 - Summer 2022

    ml eng intern | jp morgan chase & co. (Applied Innovation of Artificial Intelligence (AI2))

    Pursued personal research in Natural Language Processing, building a search engine, powered by dense passage retrieval, with q&a capabilities. Assisted researchers in delivering proof of concept projects, onboarding them to CI/CD platforms.

academic service

10/2025 - present supervision university of cambridge

  • shrey biswas part ii thesis on model merging
  • francesco simioni masters thesis on latent representations in federated learning (accepted at MobiUK)

2/2025 - present reviewing

  • journals tmlr
  • conferences neurips 2026, icml 2026 (Gold Reviewer Award)
  • workshops icml 2026 adaptfm (technical program chair), aaai 2026 flca, iclr 2025 mcdc

volunteering

02/2023 - present ml systems & theory co-lead

  • At the Cohere Labs open-science community, I have the privilege of being one of the co-leads for the ML Systems & Theory group. This is designed to provide a platform for exploring research ideas and open questions at this intersection.

collaboration
view here

I have had the fortune to work with many kind and talented individuals throughout my young career. In particular, thank you to the following individuals for inspiring me (in no particular order):
alessandro palmarini
simon yu
sree harsha nelaturu