Researcher

Hamid Palangi

Hamid Palangi is an AI researcher whose work spans information retrieval, language models and reasoning. He studied electrical engineering and Teaching English as a Foreign Language, earned an M.Sc. at Sharif and began doctoral work at UBC. At Microsoft, he worked on ToxiGen and coauthored Orca and Orca 2; his sentence-embedding research for search received the IEEE Signal Processing Society's 2018 Best Paper Award. He is a Staff Research Scientist at Google, an Affiliate Associate Professor at the University of Washington and an advisor for Koidra.

Timeline

  1. By 2012

    Early life and engineering studies

    He studies electrical engineering at a teacher-training university in Tehran and earns a bachelor's in Teaching English as a Foreign Language. After earning an M.Sc. at Sharif University, he works for about a year as a start-up engineer and moves to Vancouver for a Ph.D. at UBC; by 2012, he is three months into the program.

  2. 2012

    A UBC workshop

    At a departmental workshop in 2012, Microsoft Research's Li Deng presents deep-learning models for speech recognition, which introduces him to the field. His Ph.D. in Electrical and Computer Engineering at UBC covers compressive sensing, speech recognition, web search and information retrieval.

  3. 2018–2019

    Sentence embeddings for search

    His coauthored sentence-embedding work for web search and information retrieval receives the IEEE Signal Processing Society's 2018 Best Paper Award (Test of Time), which the society presents in 2019.

  4. 2017–2020

    Research at Microsoft

    From 2017 to 2020, he works on neuro-symbolic question answering, image reasoning, algebraic math problems, image captioning and multimodal retrieval. By 2020, he is a Senior Researcher at Microsoft Research Lab (AI) in Redmond, focused on natural-language processing and reasoning across language and vision.

  5. 2022

    ToxiGen and hate speech

    In 2022, he coauthors ToxiGen, a large-scale machine-generated dataset for adversarial and implicit hate speech detection. The team uses large language models and careful prompt engineering to generate implicit hate examples across 13 minority identity groups.

  6. 2023

    Orca and Orca 2

    In 2023, he coauthors the Orca and Orca 2 papers on small language models. Orca learns from GPT-4's step-by-step reasoning traces; Orca 2 trains 7-billion- and 13-billion-parameter models on tailored synthetic data to improve reasoning.

  7. 2026

    ScholarPeer for peer review

    In 2026, he coauthors ScholarPeer, a multi-agent framework for automated peer review. It checks claims against literature and audits technical soundness to support researchers and reviewers.

  8. As of October 2026

    Research roles at Google and UW

    As of October 2026, he is a Staff Research Scientist at Google, an Affiliate Associate Professor at the University of Washington and an advisor for Koidra. He leads research projects and mentors staff and interns.

Sources and credits

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  1. Series to Highlight Young Professionals in Signal Processing: Dr. Hamid Palangi signalprocessingsociety.org. Checked 19 October 2026.
  2. Welcome - Hamid Palangi hamidpalangi.com. Checked 19 October 2026.
  3. Search engine-enhancing research from UBC and Microsoft wins best paper award apsc.ubc.ca. Checked 19 October 2026.
  4. (De)ToxiGen: Leveraging large language models to build more robust hate speech detection tools microsoft.com. Checked 19 October 2026.
  5. Orca - Microsoft Research: Publications microsoft.com. Checked 19 October 2026.
  6. Orca 2: Teaching Small Language Models How to Reason microsoft.com. Checked 19 October 2026.
  7. Hamid Palangi research.google. Checked 19 October 2026.
  8. Speakers | SURGeLLM surgellm.github.io. Checked 19 October 2026.