Current position

• October 2025 – present.
  Full Professor of Machine Learning, Department of Engineering, University of Cambridge, UK.
• September 2025 – present
  Head of Research, Boltzbit Limited.
• November 2024 – present
  Chief AI Officer, Angstrom AI.
• September 2020 – present
  Director, Cambridge ELLIS unit, University of Cambridge, UK.
• December 2020 – present
  Faculty member, Cambridge Center for AI in Medicine, Cambridge, UK.

Past Positions

• October 2022 – September 2025.
  Professor of Machine Learning, Department of Engineering, University of Cambridge, UK.
• November 2020 – August 2025
  Senior scientific advisor, Boltzbit Limited.
• October 2021 – October 2022
  Associate Professor in Machine Learning, Department of Engineering, University of Cambridge, UK.
• September 2016 – October 2021
  University Lecturer in Machine Learning, Department of Engineering, University of Cambridge, UK.
• May 2018 – Oct 2020.
  Visiting Researcher. Microsoft Research Cambridge, UK.
• September 2014 – August 2016.
  Postdoctoral fellow in the Harvard Intelligent Probabilistic Systems group, School of Engineering and Applied Sciences, Harvard University, working with Prof. Ryan Adams on Bayesian optimization and other machine learning problems.
• June 2011 – August 2014.
  Postdoctoral researcher at the Machine Learning Group, Department of Engineering, University of Cambridge, working with Prof. Zoubin Ghahramani on probabilistic models for matrix data and other machine learning techniques.
• October 2013 – August 2014.
  Research Associate, Wolfson College, Cambridge.
• December 2010 – May 2010.
  Teaching assistant, Computer Science Department, Universidad Autónoma de Madrid, Spain.

Short Biography

José Miguel Hernández-Lobato is Full Professor of Machine Learning in the Department of Engineering at the University of Cambridge, where he is also Co-Director of the Cambridge ELLIS Unit and a Turing Fellow at the Alan Turing Institute. His research focuses on probabilistic machine learning, deep generative models, Bayesian optimization, and uncertainty quantification, with a particular emphasis on applications to molecular design, chemistry, data compression and healthcare. He received his PhD in Computer Science from Universidad Autónoma de Madrid and has held postdoctoral research positions at Harvard University and the University of Cambridge and was a visiting researcher at Microsoft Research, Cambridge. His research work has been widely recognized through numerous awards and fellowships, including an EPSRC Turing AI Acceleration Fellowship, election as a Fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS) and director of the ELLIS research program on Machine Learning for Molecule Discovery. In addition to his academic work, he actively collaborates with industry and is involved in multiple AI-driven startups and advisory roles.

Contact Information

Department of Engineering
University of Cambridge
Trumpington Street
Cambridge CB2 1PZ, UK
Email: jmh233-at-cam.ac.uk
Office: Room BE4-49

Curriculum Vitae

My CV can be downloaded from this link [pdf].