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    \small
    \href{mailto:aai30@cam.ac.uk}{aai30@cam.ac.uk} \ \ |\ \ 
    \href{tel:+447587052460}{+44 7587 052460} \ \ |\ \ 
    \href{https://github.com/Iacob-Alexandru-Andrei}{GitHub} \ \ |\ \ 
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% --- DATA ---
\firstname{Alex}
\familyname{Iacob}
\title{Cambridge} 

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% ================= EDUCATION =================
\section{Education}
\edentry[0.5em]{Oct 22--Present}{PhD in Computer Science}{\textsb{University of Cambridge}}{}{}{
\begin{itemize}[leftmargin=*]%
  \item Third-year PhD Candidate in Machine Learning Systems. \textsb{Advisor: Dr. Nicholas Lane}.
  \item Specialization: \textsb{Distributed Optimization} for training foundation models across geo-distributed datacenters under strict bandwidth/VRAM constraints.
\end{itemize}}

\edentry[0.5em]{Oct 21--Jul 22}{MPhil Advanced Computer Science}{\textsb{University of Cambridge}}{}{}{
\begin{itemize}[leftmargin=*]%
  \item \textsb{Distinction (Rank 5/36, 84\%)}. \textsb{Advisor: Dr. Nicholas Lane}.
  \item Dissertation: \textit{The Local-Global Trade-off in Federated Learning}.  Published at \textsb{EuroMLSys}.
\end{itemize}}

\edentry[0.5em]{Oct 18--Jul 21}{BSc Computer Science}{\textsb{King's College London}}{}{}{
\begin{itemize}[leftmargin=*]%
  \item \textsb{First-Class Honours (85\%)}. Recipient of the \textsb{Undergraduate Research Fellowship Award}.
\end{itemize}}

% ================= SELECTED PUBLICATIONS =================
\section{Selected Publications}

% --- UPDATED LABELS: SINGLE ROW FORMAT ---
\cvitem[0.8em]{\textsb{Oral Top 1.8\% ICLR-25}}{\textsb{Alex Iacob}, et al. ``DEPT: Decoupled Embeddings for Pre-training Language Models''. }

\cvitem[0.8em]{\textsb{Top 3\% ICLR-26}}{\textsb{Alex Iacob}, et al. ``MT-DAO: Multi-Timescale Distributed Adaptive Optimizers with Local Updates''. }

\cvitem[0.8em]{\textsb{Top 5 \% ICLR-26}}{\textsb{Alex Iacob}, et al. ``DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models''.}

\cvitem[0.8em]{\textsb{Best Paper FL@FM}}{\textsb{Alex Iacob}, et al. ``Worldwide Federated Training of Language Models''. Published at the Federated Learning in the Age of Foundation Models venue at \textit{NeurIPS 2024}.}

% ================= WORK EXPERIENCE =================
\section{Work Experience}
\cventry[0.8em]{May. 24--Present}{Research Scientist}{Flower Labs}{Cambridge}{}{
  \begin{itemize}[leftmargin=*]%
    \item \textbf{Model Training:} Pre-trained \textbf{1-13B} models on \textbf{hundreds of billions of tokens} outperforming baselines such as SmolLM2 and OLMo2 in downstream tasks with matched compute.
    \item \textbf{Engineering:} Developed the aggregation layer for \textbf{Flower Photon}, unifying \textbf{32 H100 GPUs} across \textbf{4 geo-distributed datacenters} (US/EU) by leveraging \textbf{Local SGD}-based methods.
   \item \textbf{Research:} Published \textbf{DEPT}, enabling arbitrary vocabulary scaling with limited memory/bandwidth. Created two local-update adaptive optimizers, providing \textbf{convergence guarantees for heterogeneous loss functions}, established new SOTA.
    \item \textbf{Optimization:} Migrated pre-training codebase to \textbf{torchtitan} and \textbf{torchft}. Achieving a \textbf{4x wall-clock speedup} over baseline Python implementation. 
  \end{itemize}}

\cventry[0.8em]{Jan. 23--Present}{Teaching Assistant}{University of Cambridge}{}{}{
  \begin{itemize}[leftmargin=*]%
    \item Authored the primary lab codebase for the university's \textsb{first} Federated Learning course.
  \end{itemize}}

\cventry[0.8em]{Jun. 20--Oct. 22}{Undergraduate Research Fellow}{King's College London}{}{}{
\begin{itemize}[leftmargin=*]%
  \item Applied computational social choice techniques to \textsb{multi-agent system decision-making}.
\end{itemize}}

% ================= TECHNICAL SKILLS =================
\section{Technical Skills}
\cvitem{Tools}{PyTorch, \textsb{torchtitan}, \textsb{torchft}, Docker, WandB, Slurm, Hydra}
\cvitem{Distributed ML}{4D Parallelism (FSDP/TP/PP/SP), Multi-Node Training, Local SGD}
\cvitem{Research Areas}{Optimizer Design, Mixture-of-Experts,  Distributed LLM Pre-training, Unlearning}

% ================= EXTENDED PUBLICATIONS =================
\section{Extended Publications}

\cvitem[0.3em]{MLSys '25}{L. Sani, \textsb{Alex Iacob}, et al. ``Photon: Federated LLM Pre-Training''.}

\cvitem[0.3em]{NeurIPS '25}{W. F. Shen, X. Qiu, M. Kurmanji, \textsb{Alex Iacob}, et al. ``LLM Unlearning via Neural Activation Redirection''.}

\cvitem[0.3em]{ICLR '26}{W. Zhao, Y. Chen, W. Ma, Y. Tang, S. Hu, S. X. Hu, \textsb{Alex Iacob}, et al. ``Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods''.}

\cvitem[0.3em]{NeurIPS FL@FM '24}{L. Sani, \textsb{Alex Iacob}, et al. ``The Future of Large Language Model Pre-training is Federated''. }

\cvitem[0.3em]{MobiUK '23}{\textsb{Alex Iacob}, et al. ``Robust and private multi-modal federated human activity recognition''.}

\cvitem[0.3em]{MLSys On-device '23}{\textsb{Alex Iacob}, et al. ``Privacy in multimodal federated human activity recognition''. In: \textit{3rd On-Device Intelligence Workshop}, \textit{MLSys ’23}.}

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