PeopleofSuperintelligence

Researcher

Peter J. Bentley

Peter Bentley is a computer scientist whose AI research applies evolutionary computation to design. He was born in Colchester in 1972, studied artificial intelligence at the University of Essex under Edward Tsang, and earned a PhD in evolutionary design under Jonathan Wakefield at age 24. In 1998, he surveyed four forms of evolutionary design and edited Evolutionary Design by Computers in 1999. His work later included PASCAL’s machine-learning heart-sound challenge, AI company Braintree, COIL for robot scheduling, and CLEAR for image-based sustainability data. As of October 2026, he is Professor of Digital Biology at UCL, heads its Digital Biology Interest Group, and is a Visiting Professor at Autodesk and a Collaborating Professor at KAIST.

Born
1972
Works
351
Citations
6,895
h-index
42
Badges

Years link to their sources. Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1972

    AI education and doctoral work

    Born in Colchester in 1972, he earns a BSc in artificial intelligence at the University of Essex under Edward Tsang and a PhD in evolutionary design under Jonathan Wakefield at age 24.

  2. 1998

    Surveying evolutionary design

    In 1998, he surveys four forms of evolutionary design: Evolutionary Design Optimisation, Evolutionary Art, Evolutionary Artificial Life Forms and Creative Evolutionary Design.

  3. 1999

    Editing Evolutionary Design by Computers

    In 1999, he edits Evolutionary Design by Computers, a book on evolutionary design.

  4. 2011

    PASCAL heart-sound challenge

    In 2011, he works with Glenn Nordehn, Miguel Coimbra, Shie Mannor and Rita Getz on PASCAL's Classifying Heart Sounds Challenge. It uses public iStethoscope Pro and hospital DigiScope recordings for machine-learning tasks in heart-sound segmentation and classification.

  5. 2016–2019

    Chief technology officer at Braintree

    From 2016 to 2019, he serves as Chief Technology Officer at Braintree, an AI company.

  6. 2023

    COIL for robot scheduling

    With Soo Ling Lim, Paolo Arcaini and Fuyuki Ishikawa, he tests COIL, a machine-learning optimization method, against a genetic algorithm for scheduling autonomous delivery robots. In 2023, COIL finds valid schedules across all tested variants and optimizes 10% faster after learning its latent representation.

  7. 2025

    CLEAR for building sustainability data

    In 2025, with Soo Ling Lim and Fuyuki Ishikawa, he introduces CLEAR, which combines large language models with evolutionary computation to optimize cues for recognizing specialized features in images. They apply it to extract sustainability data from interior and exterior building images.

  8. As of October 2026

    Professor of Digital Biology

    As of October 2026, he is Professor of Digital Biology at UCL, a Visiting Professor at Autodesk and a Collaborating Professor at KAIST. He heads the Digital Biology Interest Group in UCL’s Department of Computer Science.

Career

  1. Since 2022AutodeskVisiting Professor
  2. Since 1997University College LondonProfessor of Digital Biology
  3. NowKAISTCollaborating Professor
  4. 2016–2019BraintreeChief Technology Officer

Education

  1. University of EssexBSc and PhD

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

Most-cited works

  1. Evolutionary Design by Computers1999 · 633 citations
  2. Danger Theory: The Link between AIS and IDS?2003 · Lecture notes in computer science · 329 citations
  3. Immune System Approaches to Intrusion Detection - A Review2007 · 293 citations
  4. Finding Acceptable Solutions in the Pareto-Optimal Range using Multiobjective Genetic Algorithms1998 · Springer eBooks · 250 citations
  5. Three ways to grow designs: a comparison of embryogenies for an evolutionary design problem1999 · 238 citations

From OpenAlex, as of 21 October 2026.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University College London. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes University College London. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  3. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University College London. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  4. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes University College London. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Peter J. Bentley - Wikipedia en.wikipedia.org. Checked 21 October 2026.
  2. Aspects of Evolutionary Design by Computers arxiv.org. Checked 21 October 2026.
  3. Evolutionary Design by Computers educate.elsevier.com. Checked 21 October 2026.
  4. Classifying Heart Sounds Challenge peterjbentley.com. Checked 21 October 2026.
  5. Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery arxiv.org. Checked 21 October 2026.
  6. CLEAR: Cue Learning using Evolution for Accurate Recognition Applied to Sustainability Data Extraction arxiv.org. Checked 21 October 2026.
  7. Classifying Heart Sounds - Approaches to the PASCAL Challenge scitepress.org. Checked 21 October 2026.
  8. AbnormalHeartbeat - Time Series Classification Website timeseriesclassification.com. Checked 21 October 2026.
  9. CLEAR: Cue Learning using Evolution for Accurate Recognition Applied to Sustainability Data Extraction (arXiv v3) arxiv.org. Checked 21 October 2026.
  10. IDSTA 2024 idsta-conference.org. Checked 21 October 2026.