Researcher

Boris Katz

Boris Katz is a principal research scientist at MIT CSAIL and the creator of START, an early Web question-answering system. As a Moscow University undergraduate in the 1960s, he taught a computer to read and solve math problems and arrived in Boston from the Soviet Union in 1978. START answered reporters' questions from the JPL press room during the 1989 Voyager 2 Neptune encounter and became the first question-answering system on the Web in 1993. In 2006, his InfoLab technology inspired Siri; by 2011, StartMobile enabled natural-language phone interaction and ideas from START contributed to IBM's Watson. His 2020 work explored grounded language understanding, and his 2025 paper examined guided network learning; as of October 2026, he heads InfoLab and works with PhD student Christopher Wang on language and the brain.

Now at
MIT CSAIL
Works
198
Citations
3,456
h-index
30
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 1960s

    A program for math problems

    As an undergraduate at Moscow University in the 1960s, he teaches a computer to read and solve math problems.

  2. 1978

    Leaving the Soviet Union

    He arrives at Logan International Airport in Boston with his family in 1978 as a Soviet emigrant.

  3. 1989–1993

    START from Voyager to Web

    During the Voyager 2 Neptune encounter in 1989, START answers reporters' questions from the JPL press room. In 1993, it becomes the first question-answering system on the Web. Katz is its creator.

  4. 2006

    An inspiration for Siri

    In 2006, technology from his InfoLab group becomes a major inspiration for Apple's Siri.

  5. 2011

    StartMobile and Watson

    By 2011, StartMobile lets mobile phone users interact with their devices through natural language. Ideas from START also enter IBM's Watson, which defeats Jeopardy! champions in 2011.

  6. 2020

    Compositional networks for language

    In 2020, he coauthors “Compositional Networks Enable Systematic Generalization for Grounded Language Understanding,” which helps agents generalize language understanding to commands grounded in vision.

  7. 2025

    Guided learning for neural networks

    In 2025, he coauthors “Training the Untrainable: Introducing Inductive Bias via Representational Alignment,” which shows that brief guidance can improve neural networks previously thought untrainable.

  8. As of October 2026

    MIT CSAIL InfoLab leadership

    As of October 2026, he is a principal research scientist and head of MIT CSAIL's InfoLab. He works with PhD student Christopher Wang on models and datasets that map language through the brain.

Career

  1. Since 2000MIT CSAILPrincipal Research Scientist
  2. 1987–2026Massachusetts Institute of Technology

Education

  1. Lomonosov Moscow State UniversityUndergraduate

Most-cited works

  1. ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models2019 · 291 citationsWith Joshua B. Tenenbaum
  2. Quantitative evaluation of passage retrieval algorithms for question answering2003 · 282 citationsWith Jimmy Lin
  3. Learning Physical Descriptions From Functional Definitions, Examples, And Precedents1982 · 192 citationsWith Patrick H. Winston and Thomas O. Binford
  4. Annotating the world wide web using natural language1997 · 163 citations
  5. Omnibase: Uniform Access to Heterogeneous Data for Question Answering2002 · Lecture notes in computer science · 128 citationsWith Jimmy Lin

Sources and credits

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  1. The man who helped invent virtual assistants thinks they’re doomed without a new AI approach technologyreview.com. Checked 18 October 2026.
  2. Katz Family Re-United After 3 Years | The Harvard Crimson thecrimson.com. Checked 18 October 2026.
  3. Boris Katz's Home Page people.csail.mit.edu. Checked 18 October 2026.
  4. CSAIL's Boris Katz On NPR | MIT CSAIL csail.mit.edu. Checked 18 October 2026.
  5. [2008.02742] Compositional Networks Enable Systematic Generalization for Grounded Language Understanding arxiv.org. Checked 18 October 2026.
  6. Guided learning lets “untrainable” neural networks realize their potential | MIT News | Massachusetts Institute of Technology news.mit.edu. Checked 18 October 2026.
  7. Christopher Wang | CSAIL Alliances cap.csail.mit.edu. Checked 18 October 2026.