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\begin{document}

% ──── Header ────
\begin{center}
  {\fontsize{28}{34}\selectfont\bfseries\color{primary} Dr.\\ Alexandra Chen}\\[8pt]
  {\color{lightgray}\rule{8cm}{0.5pt}}\\[8pt]
  {\small
    \faIcon{envelope}\;\href{mailto:a.chen@stanford.edu}{a.chen@stanford.edu} \quad
    \faIcon{phone}\;+1 (650) 555-0142 \quad
    \faIcon{map-marker-alt}\;Stanford, CA\\[4pt]
    \faIcon{globe}\;\href{https://alexchen.io}{alexchen.io} \quad
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\vspace{4pt}

% ──── Summary ────
\section{Summary}

Machine learning researcher with 8+ years of experience in natural language processing and large language models. Published 25+ papers at top venues (NeurIPS, ICML, ACL, EMNLP) with 3,800+ citations. Led research teams developing foundation models deployed to millions of users. Seeking faculty positions in computer science.

% ──── Education ────
\section{Education}

\cventry{Ph.D.\\ in Computer Science}{2016 -- 2021}{Stanford University}{Stanford, CA}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=2pt]
  \item Thesis: ``Efficient Transformers for Long-Range Sequence Modeling''
  \item Advisor: Prof.\\ Christopher Manning \quad Committee: Profs.\\ Percy Liang, Dan Jurafsky
  \item Stanford Graduate Fellowship (SGF) recipient
\end{itemize}

\cvsep

\cventry{M.S.\\ in Computer Science}{2014 -- 2016}{Carnegie Mellon University}{Pittsburgh, PA}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=2pt]
  \item Focus: Machine Learning and Language Technologies
  \item GPA: 4.0/4.0 \quad Dean's List all semesters
\end{itemize}

\cvsep

\cventry{B.S.\\ in Mathematics and Computer Science}{2010 -- 2014}{MIT}{Cambridge, MA}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=2pt]
  \item Summa Cum Laude \quad Phi Beta Kappa
  \item Undergraduate thesis on spectral graph theory (awarded departmental prize)
\end{itemize}

% ──── Experience ────
\section{Professional Experience}

\cventry{Senior Research Scientist}{2023 -- Present}{Google DeepMind}{Mountain View, CA}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=2pt]
  \item Lead a team of 8 researchers developing next-generation language models
  \item Designed novel attention mechanisms reducing compute by 40\% at scale
  \item Core contributor to Gemini model family; responsible for efficiency improvements
  \item Mentored 4 PhD interns, all placed at top research labs or faculty positions
\end{itemize}

\cvsep

\cventry{Research Scientist}{2021 -- 2023}{Meta AI (FAIR)}{Menlo Park, CA}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=2pt]
  \item Developed sparse mixture-of-experts models for efficient inference
  \item Led the retrieval-augmented generation (RAG) project for factual consistency
  \item Published 8 papers; 2 received spotlight/oral designations at NeurIPS
  \item Open-sourced model checkpoints downloaded 500K+ times
\end{itemize}

\cvsep

\cventry{Research Intern}{Summers 2018, 2019}{OpenAI}{San Francisco, CA}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=2pt]
  \item Contributed to GPT-2 training infrastructure and evaluation framework
  \item Developed techniques for reducing hallucination in text generation
\end{itemize}

% ──── Selected Publications ────
\section{Selected Publications}
{\small
\begin{enumerate}[leftmargin=1.5em, itemsep=3pt]
  \item \textbf{A.\\ Chen}, J.\\ Smith, R.\\ Patel. ``FlashLinear: Sub-Quadratic Attention via Structured State Spaces.'' \textit{NeurIPS 2024}. \textbf{(Oral, top 0.5\%)}
  \item \textbf{A.\\ Chen}, M.\\ Johnson. ``Scaling Laws for Mixture-of-Experts Language Models.'' \textit{ICML 2024}.
  \item L.\\ Wang, \textbf{A.\\ Chen}, K.\\ Lee. ``Retrieval-Augmented Generation with Learned Relevance.'' \textit{ACL 2023}. \textbf{(Best Paper Award)}
  \item \textbf{A.\\ Chen}, T.\\ Brown, S.\\ Narang. ``Efficient Long-Context Transformers via Sliding Window Attention.'' \textit{NeurIPS 2022}. \textbf{(Spotlight)}
  \item \textbf{A.\\ Chen}, C.\\ Manning. ``Linear Transformers with Gated Retention.'' \textit{ICLR 2021}.
\end{enumerate}
}

% ──── Awards ────
\section{Awards \& Honors}

\begin{multicols}{2}
\begin{itemize}[leftmargin=1.5em, nosep, itemsep=3pt]
  \item ACL Best Paper Award, 2023
  \item MIT Technology Review 35 Under 35, 2024
  \item Stanford Graduate Fellowship, 2016--2021
  \item NSF Graduate Research Fellowship, 2016
  \item CRA Outstanding Undergraduate Award, 2014
  \item Phi Beta Kappa, MIT Chapter, 2014
\end{itemize}
\end{multicols}

% ──── Skills ────
\section{Technical Skills}

\begin{tabularx}{\textwidth}{@{}lX@{}}
\textbf{Languages:} & Python, C++, CUDA, Julia, Rust \\
\textbf{Frameworks:} & PyTorch, JAX, TensorFlow, Hugging Face, DeepSpeed, Megatron-LM \\
\textbf{Infrastructure:} & Kubernetes, Slurm, TPU Pods, multi-node GPU training (up to 2048 GPUs) \\
\textbf{Specialties:} & Large language models, efficient attention, distributed training, NLP \\
\end{tabularx}

% ──── Service ────
\section{Academic Service}

\begin{itemize}[leftmargin=1.5em, nosep, itemsep=3pt]
  \item \textbf{Area Chair}: NeurIPS 2024, ICML 2024, ACL 2023
  \item \textbf{Reviewer}: NeurIPS, ICML, ICLR, ACL, EMNLP, JMLR, TACL (100+ reviews total)
  \item \textbf{Workshop Organizer}: ``Efficient NLP'' at EMNLP 2023; ``Scaling Laws'' at ICML 2024
  \item \textbf{Invited Talks}: Google, Microsoft, Meta, Amazon, Apple, NVIDIA, 15+ universities
\end{itemize}

\end{document}
