Negar Arabzadeh
Postdoctoral Fellow at UC Berkeley
This is Negar Arabzadeh. I am a postdoctoral researcher at UC Berkeley, working with Professor Matei Zaharia. I completed my PhD at the University of Waterloo, where I was advised by Dr. Charles Clarke. My research lies at the intersection of information retrieval and the evaluation of—and with—large language models (LLMs) in information access systems.
I am on the academic job market starting in 2026.
News
2026
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Best Paper Award at ECIR 2026 for “ReFormeR: Learning and Applying Explicit Query Reformulation Patterns.”
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Best Industry Talk Award at WSDM 2026 for “Can LLMs Uphold Research Integrity? Evaluating the Role of LLMs in Peer Review Quality.”
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“QueryGym: A Toolkit for Reproducible LLM-Based Query Reformulation” accepted at The Web Conference 2026.
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“PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality” accepted at The Web Conference 2026.
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Presented MAP: Measuring Agents in Production at a NICE Talk — insights from a year-long empirical study on real-world agent deployments.
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Presented MAP: Measuring Agents in Production at Google Sense AI.
2025
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Runner-up Best Paper Award at SIGIR-AP 2025 for “Adversarial Attacks against Neural Ranking Models via In-Context Learning.”
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Attended my first NeurIPS! It was pretty OVERWHELMING.
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Presented “Restructuring the Corpus Makes RAG Work for Math” at the Math AI workshop, NeurIPS 2025.
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Presented “DeepScholar-Bench: A Live Benchmark and Automated Evaluation for Generative Research Synthesis” at the LLM Evaluation workshop, NeurIPS 2025.
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Presented “Towards Automatically Optimizing Retrieval Augmented AI Systems” at the ML for Systems workshop, NeurIPS 2025.
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Released MAP: Measuring Agents in Production — a whole-year-long project.
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“Can LLMs Uphold Research Integrity? Evaluating the Role of LLMs in Peer Review Quality” accepted at WSDM 2026 — Best Industry Paper Award.
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Attended CIKM in Seoul, South Korea — presented one applied research paper, one short paper, and an industry talk.
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Graduated with my PhD from the University of Waterloo — thesis nominated for the Gold Thesis Award.
Right now I am working on agentic IR, RAG-related problems, and using retrieval for reasoning-intensive tasks. Reach out if you have ideas to discuss — I am always happy to collaborate.