PeopleofSuperintelligence

Researcher

Burn Lewis

Also known as Burn L. Lewis

Burn Lewis is an AI researcher whose published work spans speech and language processing, question answering, code generation, and software security. In 2008, he coauthored the GALE Type System, a shared format for connecting speech, translation, and information-extraction engines. He contributed to IBM's Watson and DeepQA question-answering team, and the IBM Watson team received the 2013 AAAI Feigenbaum Prize. Later, he coauthored D2A for vulnerability detection, Varangian for static analysis, and Ansible Wisdom for generating IT automation scripts from natural language. By 2024, he was affiliated with IBM while coauthoring research on D2A and code vulnerability identification.

Now at
IBM
Works
9
Citations
202
h-index
5

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2008

    The GALE Type System

    In 2008, he coauthors a paper that describes the GALE Type System, a shared format for connecting speech-recognition, translation, and information-extraction engines.

  2. 2010

    Working on Watson

    By 2010, he contributes to IBM's Watson and DeepQA team, which develops a question-answering system for real-time competition with Jeopardy! champions.

  3. 2013

    A Feigenbaum Prize

    The IBM Watson team receives the 2013 AAAI Feigenbaum Prize, and Burn Lewis is among its named members. The award recognizes a synthesis of symbolic knowledge representation, natural language understanding, and statistical machine learning for real-time factual question answering.

  4. 2021

    Training vulnerability detectors

    In 2021, he coauthors D2A, a dataset built from code versions before and after bug fixes to train machine-learning models for vulnerability identification and flag false alarms from static-analysis tools.

  5. 2022

    A Git bot for static analysis

    In 2022, he coauthors Varangian, a Git bot for augmented static analysis. The team builds D2A from repository commit history to create labeled data for machine-learning systems that suppress static-analysis false alarms.

  6. 2023

    Generating Ansible code

    In 2023, he coauthors Ansible Wisdom, a transformer-based tool that turns natural-language prompts into Ansible-YAML code for IT automation.

  7. By 2024

    Research at IBM

    By 2024, he is affiliated with IBM and coauthors a study that trains classic machine-learning and deep-learning models on D2A for vulnerability identification.

Most-cited works

  1. D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential Analysis2021 · IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) · 146 citations
  2. Invited: Automated Code generation for Information Technology Tasks in YAML through Large Language Models2023 · ACM IEEE Design Automation Conference · 28 citations
  3. Timely and Efficient AI Insights on EHR: System Design2020 · 10 citations
  4. Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT2024 · Empirical Software Engineering · 8 citations
  5. Aggregating distributed STT, MT, and information extraction engines: the GALE interoperability-demo system2008 · Interspeech (USB) · 5 citations

From OpenAlex, as of 19 October 2026.

  1. Google alumni founded or led 81 other organizations, the most among the labs we compareIncludes IBM. We trace 194 organizations founded or led by AI lab alumni, and 202 career moves between the labs.
  2. The company share of AI researchers’ top papers rose from 2% to 32%Includes IBM. We estimate where leading AI researchers worked when their most-cited papers appeared. The company share rose from 2% in 1975–1979 to 32% in 2020–2024.
  3. Google has the highest combined h-index among AI organizationsIncludes IBM. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  4. Google had the most people shaping AI every year from 2014 to 2025Our 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

Photo: We have no published photo of Burn Lewis yet. Send us a free-licensed photo.

  1. A data format enabling interoperation of speech recognition, translation and information extraction engines: The GALE type system research.ibm.com. Checked 18 October 2026.
  2. The AI Behind Watson — The Technical Article aaai.org. Checked 18 October 2026.
  3. Feigenbaum Prize cs.stanford.edu. Checked 18 October 2026.
  4. D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential Analysis arxiv.org. Checked 18 October 2026.
  5. Varangian: A Git Bot for Augmented Static Analysis research.ibm.com. Checked 18 October 2026.
  6. Automated Code generation for Information Technology Tasks in YAML through Large Language Models arxiv.org. Checked 18 October 2026.
  7. Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT research.ibm.com. Checked 18 October 2026.