CV

Up-to-date as of July 2026. Also available in PDF.

General Information

Full Name Julien Cornebise, Ph.D.
Email julien@cornebise.com
Website www.cornebise.com/julien/
Full CV
Download PDF (July 2026)

Profile

  • A fully integrated profile spanning the whole arc of AI: from fundamental methodological research (Bayesian machine learning and computational statistics, published in Nature and at NeurIPS and ICML), to deployment in high-stakes domains (medicine, human rights, industry, space), to the wider ecosystem around it (academic grant-giving, venture capital from seed to scale-up, and non-profits), with hands-on track record in each.
  • One of the earliest researchers at DeepMind (2012–2016); my work contributed to raise significant early funding which then led to the acquisition by Google in 2014.
  • A founder, builder and leader of teams, with a track record of hiring, mentoring and growing talent, and of setting research direction across research labs, start-ups and non-profits.
  • Combines deep technical rigour with a strong ethical compass and cross-disciplinary range, from mathematical foundations to the societal implications of technology.

Professional Experience

  • 2019 – Present
    Independent AI Researcher & Consultant, Founder & CEO
    WhyHow Ltd
    Strategic and hands-on technical AI consulting to technology start-ups, NGOs and venture-capital firms (speech recognition, vaccine development, cancer detection, satellite imagery), including scientific due diligence for investors.
    • Examples of engagements
      • R&D division of a Fortune-50 pharmaceutical company (2023–2025): Bayesian pharmacokinetics / pharmacodynamics; neural approximations of ODE systems; sequential Monte Carlo in JAX (BlackJAX, Diffrax).
      • Joint venture between a Swiss start-up and a large human-rights archive (2023–2025): bioacoustics ML (YAMNet, AudioSet); event detection of specific conflict-zone activities.
      • Cambridge-based, Series-B, best-in-class ASR (speech-recognition) start-up (2023–2024): speech and audio-LLM advisory; tokenisation, sample efficiency, SALMONN, Whisper.
      • European Space Agency, QueryPlanet (2021–2023): deep-learning super-resolution of satellite imagery. Output: the WorldStrat dataset (NeurIPS 2022) and the HighRes-net open-source toolbox.
      • Formulation and implementation of four big-data coefficients for crowdsourcing and robust dataset creation, with Klaus Krippendorff (2020–2021).
      • Seed-stage biotech start-up (2020–2021): designed their first quantitative approaches (precision-oncology and genomics); interviewed and hired their early ML engineers.
    • Investment due diligence
      • Recurring technical due diligence for several venture-capital firms and family foundations, including a large-scale sustainability growth fund; typically on Series-C-level start-ups.
  • 2021 – 2023
    Co-Founder & Chief Scientific Officer
    ShiftLab
    Co-founded and scaled an AI-driven product lab from 2 to 31 employees; managed a total budget of approximately £6 million.
    • Set and owned the company’s scientific direction and technical backbone.
    • Built the science team; led recruitment and technical interviewing.
    • Executive leadership and strategy alongside the CEO (two co-founders).
    • Three product verticals
      • Computer vision for industrial X-ray defect detection on polymer fabrics.
      • Forecasting for container markets.
      • Generative AI for end-to-end marketing campaigns.
  • 2018 – 2019
    Director of Research, Head of the London Office
    Element AI (founded by Yoshua Bengio, 2018 Turing Award)
    Created and led Element AI’s London office and its “AI for Good” division; built the team from 1 to 12.
    • Projects
      • Troll Patrol (with Amnesty International): analysis of online abuse against women; front-page Financial Times.
      • Satellite-imagery super-resolution (European Space Agency): ESA-challenge finalist; led to HighRes-net and the WorldStrat dataset.
      • Shaqodoon (Somali NGO): automatic speech recognition and classification in Somali; reached the MIT Solve final (top ~4% of applicants).
      • Forensic Architecture: classification of tear-gas canisters used against civilians.
      • Human Rights Watch: automatic analysis of video data and satellite video streams.
      • Global Witness; World Bank (SDGs); UN World Food Programme; Oxfam.
      • DECoVaC: design of experiments with controlled variability; reproducibility in few-shot learning.
    • Partnerships & strategy
      • MILA; the Partnership on AI; AI Commons; the Montreal Data License.
    • Media
      • Front-page Financial Times; Fortune; The Guardian; BBC; TechCrunch; Montreal Gazette; La Presse.
  • 2012 – 2016
    Senior Research Scientist, then Head of the Health Research Team
    DeepMind Technologies Ltd, then Google DeepMind
    • 2012–2015: Senior Research Scientist, Frontiers Research Group
      • One of the five earliest researchers (employee
      • Heavily involved in building the team: helped design the technical screening interviews and conducted extensive interviewing.
    • 2015–2016: Head of the Health Research team, Senior Research Scientist
      • Co-founded and led the Health Research team, growing it from 1 to 10; set its research direction and technical backbone, matching DeepMind’s capabilities to clinicians’ needs under heavy privacy and security constraints.
      • Work with the NHS / Moorfields (retinal diagnosis) and US Veterans Affairs (acute-kidney-injury prediction), widely covered in the press.
  • 2012
    Independent Mathematical Consultant
    For worldwide pharmaceutical statistical and bio-statistical firms. Methodological and algorithmic expertise, data analysis, and software implementation, in Bayesian and more classical statistics.
  • 2011 – 2012
    Postdoctoral Research Associate
    University College London
    Department of Statistical Science
  • 2009 – 2010
    Postdoctoral Fellow
    SAMSI (Duke University, NC) and University of British Columbia (Vancouver)
    A two-year joint postdoctoral fellowship on Sequential Monte Carlo methods: first year at SAMSI (active participant in the SMC annual programme), second year at UBC under Pr. Arnaud Doucet.

Honorary & Advisory Appointments

  • 2021 – Present
    Scientific & Technical Advisor
    The Computational Democracy Project (Pol.is)
    Long-running advisory to the open-source Pol.is platform for large-scale online deliberation.
    • Research roadmap and strategy; reproducibility engineering; hands-on implementation.
    • Research on the opportunities and risks of LLMs for scalable deliberation with Pol.is (2023).
  • 2017 – Present
    Honorary Associate Professor (formerly Honorary Research Associate)
    University College London
    Department of Computer Science
    • PhD examining: two early-assessment (upgrade / transfer) vivas.
    • Temporarily co-supervised a PhD student (project later became FairGEN).
    • Advise faculty on grant applications; mock-interviewed UCL UKRI Future-Leaders-Fellowship candidates.
    • Member, ELLIS (European Lab for Learning & Intelligent Systems).
  • 2017 – Present
    Scientific Advisory Boards & Mentoring
    • Scientific advisory boards: ZOE; Synteny (computational-immunology ML).
    • Informal scientific advisor to numerous start-ups and research projects.
    • Mentoring of early-stage founders and young executives, and of early-career researchers.
  • 2016 – Present
    Pro Bono Scientific Advisor
    Amnesty International (Amnesty Tech)
    Ongoing AI and data-science expertise for human-rights investigations and advocacy.
    • Decode Darfur: detection of destroyed villages from satellite imagery.
    • Detected and mapped NYPD surveillance cameras through crowdsourcing; the resulting data was used in a lawsuit against the NYPD.
    • TikTok and teen mental health: analysis used to help initiate EU regulation.
    • Russian-speech war-crimes project: analysis of intercepted communications.
    • Designed the investigation into Denmark’s welfare algorithm and reviewed the report.

Education

  • 2005 – 2009
    Ph.D. in Mathematical Sciences
    University Paris 6 (Pierre and Marie Curie)
    Speciality: Statistics and Applied Probability. Highest Honors (Mention Très Honorable). Title: “Adaptive Sequential Monte Carlo Methods.” Funded by a National Research Fellowship from the Ministry of Research and Higher Education.
  • 2004 – 2005
    M.Sc. in Mathematics and their Applications, Speciality Statistics
    University Paris 6
    Highest Honors (Mention Très Bien). Graduated 1st of a class of 80.
  • 2000 – 2005
    M.Eng., Computer Science Major
    École Supérieure d’Informatique Électronique Automatique (ESIEA)
    Highest Honors (Mention Très Bien). Graduated 1st of a class of 250. Five-year engineering school with integrated preparatory cycle, accredited by the French national Commission des Titres d’Ingénieur.
  • 2000
    French National Baccalauréat, Scientific Section
    Highest Honors (Mention Très Bien).

Awards & Honours

  • 2025
    Top-10% Area Chair, NeurIPS
  • 2019
    MIT Solve finalist
  • 2018
    Best Reviewer Award, ICLR
  • 2010
    Savage Award, International Society for Bayesian Analysis (Theory and Methods), for best PhD thesis
  • 2008
    Best-student-paper finalist, EUSIPCO

Visiting Research Stays

  • Research visits (2008–2012): University of Bern; University of New South Wales; SAMSI (Duke University); Cornell University; University of Cambridge; LTH / Lund University.

Invited Talks & Academic Presentations

  • Keynotes
    • European Space Agency / ECMWF Workshop on Machine Learning (online, 2021)
    • Anthropology + Technology Conference, Bristol, UK (2019)
    • European Space Agency Φ-Week, Frascati (Rome), Italy (2019)
    • useR! 2019, Toulouse, France
    • International Joint Conference on Artificial Intelligence (IJCAI) 2015, Buenos Aires
  • Invited talks & seminars
    • ML Collective (DLCT reading group), online (2020)
    • Schloss Dagstuhl, Dagstuhl, Germany (2019)
    • Harvard, Cambridge, MA, USA (2019)
    • University of Oxford, Exeter College, Oxford, UK (2019)
    • University of Cambridge, Data Science meetup, Cambridge, UK (2019)
    • UCL Space Week, London, UK (2019)
    • MLSS (Machine Learning Summer School) (2019)
    • CIRM, Marseille, France (2018)
    • University of Cambridge, Downing College, Cambridge, UK (2018)
    • McGill RL Lab, Montréal, Canada (2018)
    • Google StatFoo 2016, Mountain View
    • NIPS 2014 Workshop on Bayesian Optimization, Montreal
    • University of Oxford, Department of Computer Science (2014)
    • ISBA 2012, Kyoto
    • Joint Statistical Meeting (JSM), Miami Beach (2011)
  • Conference & workshop presentations without proceedings (for top-tier ML conferences, see Publications)
    • Workshop on Geometric and Algebraic Statistics 3, Warwick (2011)
    • 2nd International Symposium on Biopharmaceutical Statistics, Berlin (2011)
    • Workshop on Bayesian Semiparametrics for PK/PD inference, SAMSI, Durham (2010)
    • ISBA-Valencia Meeting 2010, Benidorm
    • SAMSI SMC Transition Workshop, Durham (2009)
    • INFORMS Applied Probability Society Conference, Cornell (2009)
    • Joint Statistical Meeting (JSM), Washington D.C. (2009)
    • SAMSI Opening Workshop, Durham (2008)
    • Journées MAS de la SMAI, Rennes (2008)
    • Workshop “New Directions in Monte Carlo Methods”, Fleurance (2007)
    • Workshop on Sequential Monte Carlo Methods (SMC 2006), Oxford
    • Pharmacokinetics UK & Rosenön Meeting (PKUK 2005), Brighton
    • Premières Rencontres de Jeunes Statisticiens, Aussois (2005)

Public Engagement, Policy & Media

  • Government & policy audiences
    • Ofcom, London, UK (2024)
    • Apolitical masterclass for senior civil servants (online, 2023)
    • Centre for Data Ethics & Innovation (CDEI) / DCMS, London, UK (2021)
    • Nesta Collective Intelligence conference, London, UK (2019)
    • Tallinn Digital Summit, Tallinn, Estonia (2019)
    • Council of Europe / ECRI conference, Paris, France (2019)
  • Non-academic conferences, summits & panels
    • European Space Agency Living Planet Symposium, Bonn, Germany (2022)
    • United Nations “AI for Good” Global Summit, Geneva, Switzerland (2017–2019)
    • RightsCon, Tunis, Tunisia (2019)
    • CogX, London, UK (2018, 2019)
    • Eureka Global Innovation Summit, Manchester, UK (2019)
    • NVIDIA GTC, San Jose, CA, USA (2019)
    • SatSummit, Washington DC, USA (2018)
    • TechAIde AI Conference, Montréal, Canada (2018)
  • Educational & professional audiences
    • AI for Charities (WCIT Hall), London, UK (2024)
    • People, Culture & Law Conference (Winckworth Sherwood), London, UK (2023)
    • Greenwich Academy, Greenwich, CT, USA (remote, 2021)
    • The Law Society, London, UK (2019)
    • Naspers (2019)
  • Television
    • Good Morning Britain / ITV (2023)
    • BBC (2018, 2019)
  • Radio / aired podcasts
    • France Culture, “La Science, CQFD,” Radio France (2022)
  • Press
    • Libération (2024)
    • The Guardian (2018, 2019)
    • Financial Times (2018)
    • Fortune (2018)
    • TechCrunch (2018)
    • Montreal Gazette and La Presse (2018)
  • Online podcasts
    • “Everyday AI” podcast (2025–2026)
    • “Learning Bayesian Statistics” podcast, ep.
    • “ChangeMakers” podcast (2019)
    • “Humanitarian AI Today” podcast (2019)
    • “AI for Good” podcast (2018)

Service to the Community & Administrative Duties

  • Editorial roles
    • Associate Editor, Bayesian Analysis (2013–2018).
  • Area Chair / senior program committee
    • NeurIPS 2025 (Area Chair; top-10% ACs).
    • AISTATS 2025 (Area Chair).
    • UAI 2019 (Area Chair / meta-reviewer).
  • Conference reviewing
    • AISTATS 2020; ICML 2020.
    • ICLR 2019 (AI for Social Good); NeurIPS 2018 (AI for Social Good).
    • ICLR 2018 (Best Reviewer Award).
    • NIPS 2015; ICML 2014; Bayes-Pharma 2013; EGC 2012.
    • AISTATS 2011; EGC 2010; COMPSTAT 2010.
  • Journal reviewing
    • Annals of Applied Statistics; Bayesian Analysis; Bernoulli.
    • Statistics and Computing; Technometrics; Computational Statistics and Data Analysis.
    • Journal of Statistical Software; Journal of Statistical Computation and Simulation.
    • ACM Transactions on Modeling and Computer Simulation; IEEE Transactions in Signal Processing.
    • Pattern Recognition Letters; Autonomous Robots.
    • Communications in Nonlinear Science and Numerical Simulations; Inference and Learning in Dynamic Models.
    • Journal of Human Rights Practice.
  • Grant review
    • UKRI Future Leaders Fellowship (Sift Panel member and Roving / Interview Panel member, Rounds 3 and 5).
    • UKRI Talent Panel College (member).
    • European Research Council (registered expert evaluator, 2020).
    • EPSRC.
  • Judging
    • Presiding Judge, IBM Watson AI XPRIZE (2019).
  • Co-organizer of workshops and conferences
    • 2016: LABELS-MICCAI, Large-scale Annotation of Biomedical Data and Expert Label Synthesis Workshop (Springer proceedings editor).
    • 2012: Scientific committee, Bayes-Pharma 2012, Aachen.
    • 2009: SAMSI SMC Transition Workshop, joint with Pr. Arnaud Doucet, Pr. Simon Godsill, Pr. Mike West.
    • 2009: Sessions PMC/SMC Samplers and Bayesian Tracking at JSM 2009, Washington D.C.
  • Organizer of reading and working groups
    • 2011–2012 Weekly reading group CSML / Gatsby / Department of Statistics, UCL.
    • 2011–2012 Weekly working group on Computational Statistics, UCL.
    • 2010 Weekly reading group on Monte-Carlo, Depts of Statistics and Computer Science, UBC (joint with Pr. Arnaud Doucet).
    • 2009 Population Monte Carlo working group, SAMSI SMC programme (joint with Pr. Arnaud Doucet).
    • 2009 Tracking working group, SAMSI SMC programme (joint with Pr. Simon Godsill).
    • 2005–2007 Founder and organizer of the PhD candidates’ seminar, LSTA, University Paris 6.
  • Elected responsibilities
    • 2005–2015 Grand électeur of ESIEA’s class of 2005, alumni representative.
    • 2005–2007 Board of the Faculty of Mathematics, University Paris 6, representing graduate students.
    • 2004–2005 Students’ delegate, Master in Statistics, University Paris 6.

Teaching

  • 2007 – 2008
    Continued Education in Applied Mathematics
    ENST Paris
    Matlab: “New methods of simulation and application to filtering.”
  • 2005 – 2008
    Graduate Teaching Assistant
    University Paris 7 (Denis Diderot)
    Elementary Analysis and Algebra; Introduction to Mathematical Software (Mathematica).
  • 2006 – 2007
    Practical Sessions in Applied Mathematics
    ENST Paris
    Monte-Carlo methods applied to finance.
  • 2001 – 2004
    Undergraduate Teaching Assistant
    ESIEA
    Algorithmics, C and Java.
  • 2002 – 2003
    Instructor in Industry
    P.I.E.R.
    Java programming for industry employees.

Languages & Technical Skills

Languages
French Native language
English Fluent / bilingual (lived and worked in English in the US, Canada and the UK since 2008)
Spanish Intermediate (6 years’ study)
Technical Skills
Programming languages Python (PyTorch, JAX, TensorFlow, scikit-learn), C/C++, Lua (Torch7), R, Matlab, SAS, Mathematica, Java, Bash, SQL, PHP, HTML
System administration Linux, FreeBSD, Apache, SSHd, MySQL, FTPd

Publications, Patents & Talks

References

  • Available upon request.