PeopleofSuperintelligence

Researcher

Dipanjan Das

Dipanjan Das is an AI researcher whose work spans multilingual parsing, language-model analysis, and factuality benchmarks. He earned computer science and language technology degrees at IIT Kharagpur and Carnegie Mellon, and his multilingual sequence-model research won ACL's best paper award in 2011. His coauthored Universal Dependency paper received ACL's 2023 Test-of-Time award, and a BERT study traced how its layers process language. As of October 2026, he is a Senior Director of Research at Google DeepMind, where he leads language-technology teams and contributes to Gemini; in January 2026, he coauthored DeepSearchQA, a benchmark for deep research agents.

Works
104
Citations
12,924
h-index
43
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2005

    A computer science degree

    At IIT Kharagpur, he earns a B.Tech. in Computer Science and Engineering in 2005.

  2. 2008–2012

    Degrees at Carnegie Mellon

    At Carnegie Mellon's Language Technologies Institute, he completes a Master of Language Technologies in 2008 and a PhD in Language and Information Technology in 2012. Google Inc. is his employer upon graduation. His work on multilingual learning of sequence models wins ACL's best paper award in 2011.

  3. 2013

    Universal dependency annotation

    He coauthors Universal Dependency Annotation for Multilingual Parsing at ACL in 2013.

  4. 2019

    BERT's language hierarchy

    In 2019, he coauthors BERT Rediscovers the Classical NLP Pipeline. The study finds that BERT layers process part-of-speech tags first, followed by constituents, dependencies, semantic roles, and coreference.

  5. 2023

    A Test-of-Time award

    ACL names his 2013 Universal Dependency paper a 10-Year Test-of-Time Paper Award winner in 2023.

  6. 2024

    A factuality benchmark for LLMs

    In December 2024, he helps lead FACTS Grounding, a benchmark that measures whether long-form LLM responses stay factually grounded in supplied documents. He serves as program co-chair for COLM 2024, the first conference dedicated to language modeling.

  7. As of October 2026

    Language research at Google DeepMind

    His earlier Google work includes Google Brain and Google Research. In January 2026, he coauthors DeepSearchQA, a 900-prompt benchmark that tests agents on difficult multi-step information-seeking tasks across 17 fields. He is a Senior Director of Research at Google DeepMind, where he leads distributed teams working on language technologies and contributes to Gemini and factual text generation.

Career

  1. Since 2022Google DeepMindSenior Director of Research
  2. 2019–2022University of California, Santa Barbara
  3. 2018–2019Carnegie Mellon University
  4. 2012–2025Google

Education

  1. 2012Carnegie Mellon UniversityPhD in Language and Information Technology
  2. 2008Carnegie Mellon UniversityMaster of Language Technologies
  3. 2005Indian Institute of Technology KharagpurB.Tech. in Computer Science and Engineering

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. A Decomposable Attention Model for Natural Language Inference2016 · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 1,314 citations
  2. BERT Rediscovers the Classical NLP Pipeline2019 · Annual Meeting of the Association for Computational Linguistics (ACL) · 1,304 citations
  3. BLEURT: Learning Robust Metrics for Text Generation2020 · Annual Meeting of the Association for Computational Linguistics (ACL) · 1,001 citations
  4. Gemini: A Family of Highly Capable Multimodal Models2023 · 988 citationsWith Angeliki Lazaridou, Anja Hauth, Clemens Meyer, David Silver, Emily Pitler and Fabio Viola
  5. A Universal Part-of-Speech Tagset2012 · Language Resources and Evaluation Conference (LREC) · 818 citationsWith Ryan McDonald

From OpenAlex, as of 19 October 2026.

  1. The median h-index is 53 at universities and 19 at frontier AI labsIncludes Dipanjan Das. The median h-index is 53 at universities and 19 at frontier AI labs. We compare publishing careers, citations and moves to estimate how universities and frontier labs contribute to AI research.
  2. Google has the highest combined h-index among AI organizationsIncludes Google. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  3. Google alumni founded or led 87 other organizations, the most among the labs we compareIncludes Google. We trace 212 organizations founded or led by AI lab alumni, and 223 career moves between the labs.
  4. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Dipanjan Das research.google. Checked 19 October 2026.
  2. Dipanjan Das - Language Technologies Institute - School of Computer Science - Carnegie Mellon University lti.cmu.edu. Checked 19 October 2026.
  3. Universal Dependency Annotation for Multilingual Parsing aclanthology.org. Checked 19 October 2026.
  4. BERT Rediscovers the Classical NLP Pipeline research.google. Checked 19 October 2026.
  5. ACL Test-of-Time Papers Award Recipients aclweb.org. Checked 19 October 2026.
  6. Dipanjan Das dipanjandas.com. Checked 19 October 2026.
  7. FACTS Grounding: A new benchmark for evaluating the factuality of large language models deepmind.google. Checked 19 October 2026.
  8. DeepSearchQA: Bridging the Comprehensiveness Gap for Deep Research Agents arxiv.org. Checked 19 October 2026.