Azalia Mirhoseini
Assistant Professor of Computer Science
Develops machine learning for systems and chip design, and efficient scaling of large language models.
Azalia Mirhoseini's lab at Stanford works on accelerators, chips & architecture, efficient training & inference and large language models. 13 papers since 2023, 6 at top venues, mostly ICML and NeurIPS. 10 PhD students. 6 alumni. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 46%
- PhD students
- 10
- MS students
- 0
- alumni listed
- 6
Papers by yearfrom the lab homepage, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 9 papers2025 · T1 5
- 3 papers2024 · T1 1
- 0 papers2023 · T1 0
T1 venuesOtherVenues: ICML, NeurIPS, CoRL
Research focuspaper titles that use each topic's words
- Large language models8 papers
- Efficient training & inference4 papers
- scaling2 papers
- Accelerators, chips & architecture1 paper
- chip design0 papers
Paper list
From the lab homepage.
20261 paper
- Conference on Language ModelingDistill to Detect: Exposing Stealth Biases in LLMs through Cartridge Distillation (opens in a new tab)
20259 papers
- ES-FoMo (Oral) III @ICMLCartridges: Lightweight and general-purpose long context representations via self-study (opens in a new tab)
- MAS@ICMLCHESS: Contextual Harnessing for Efficient SQL Synthesis (opens in a new tab)
- ICML (T1)How Do Large Language Monkeys Get Their Power (Laws)? (opens in a new tab)
- ICML (T1)KernelBench: Can LLMs Write Efficient GPU Kernels? (opens in a new tab)
- CoRL (T1)RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models (opens in a new tab)
- NeurIPS (T1)SPRINT: Enabling Interleaved Planning and Parallelized Execution in Reasoning Models (opens in a new tab)
- Conference on Language ModelingSynthetic Data Generation & Multi-Step RL for Reasoning & Tool Use (opens in a new tab)
- International Conference on LLM-Aided DesignThink, Prune, Train, Improve: Scaling Reasoning Without Scaling Models (opens in a new tab)
- NeurIPS (T1)Weaver: Shrinking the Generation-Verification Gap with Weak Verifiers (opens in a new tab)
20243 papers
- ICML (T1)Archon: An Architecture Search Framework for Inference-Time Techniques (opens in a new tab)
- Conference on Language ModelingCATS: Contextually-Aware Thresholding for Sparsity in Large Language Models (opens in a new tab)
- ES-FoMo-II @ICMLHydragen: High-Throughput LLM Inference with Shared Prefixes (opens in a new tab)
Where alumni went6 listed
Apply to StanfordFall 2027
Stanford Computer Science PhD
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- English
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Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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