Hello & Welcome

I Am

About Me

AI with social-purpose. I work across fields in generative AI and sociotechnical foresight, to develop solutions for global challenges, equity and safety, participation and African AI leadership.

  • Generative Machine Learning
  • Weather & Climate
  • Sociotechnical AI
  • Transformation

I am a scientist and engineer in the fields of statistical machine learning and artificial intelligence. I am most interested in research that combines multiple disciplines and views of machine learning and its applications. I shape my efforts around three conceptual pillars: Probabilistic Foundations of Learning and Intelligence, Addressing Global Challenges, and Transformation. I work towards developing methods focussed on probabilistic reasoning that lead to systems for agent-based decision-making. I work towards the application of machine learning to global challenges in healthcare and environment, and towards social Transformation that supports greater diversity, responsibility, and freedom. I love exploring and writing about the connections between different computational, epistemological, and social paradigms and maintain a blog at blog.shakirm.com.

I am a Director for research at Google DeepMind in London; I joined DeepMind as a small startup in 2013. I am also a founder and Chair of the Board of Trustees of the Deep Learning Indaba, a non-profit whose mission is to Strengthen African Machine Learning and Artificial Intelligence. I'm an Associate Fellow at the Leverhulme Centre for the Future of Intelligence at the University of Cambridge, and an Honorary Professor in the Department of Computer Science at University College London (UCL).

I was a programme chair for DALI2019, a programme co-chair for ICLR2019, the Senior Programme Chair for ICLR2020, the General Chair for ICLR2021, and a co-General Chair for NeurIPS 2022. I am a member of the Royal Society’s Diversity and Inclusion Committee (2020-2025). I am a member of the Board of Directors of ICML, ICLR, and NeurIPS.

Before moving to London, I held a Junior Research Fellowship from the Canadian Institute for Advanced Research (CIFAR) as part of the programme on Neural Computation and Adaptive Perception. I was based in Vancouver at the University of British Columbia in the Laboratory for Computational Intelligence (LCI) with Nando de Freitas. I completed my PhD with Zoubin Ghahramani at the University of Cambridge, where I was a Commonwealth Scholar to the United Kingdom and a member of St John’s College. I am from South Africa, and completed my previous degrees in Electrical and Information Engineering at the University of the Witwatersrand, Johannesburg.


Links to overviews, slides and videos of some of my talks.

AI for Science Summit

Generative Science

Stanford HAI Fall Conference

Responsibiilities of the Pioneer

ICML 2023 Keynote

ML with Social Purpose


Elevating our Evaluations

Climate Informatics 2023

Generative Models

Tackling Clim. Change 2021

ML for Net Zero

NAACL 2021 Keynote

Generating Reality

NeurIPS2020 BioRL

Pain and ML

NeurIPS2020 ML-RSA

Through the Eyes of Birds and Frogs

TechAide 2020

Imaginations of Good, Missions for Change


Queering Machine Learning

Queer In AI @ ICML2020

Bayesian Learning (4 Parts)

MLSS 2020

Decolonising Artificial Intelligence

Intercultural Dig. Ethics 2019

Machinery of Grace

TEDxLSTM 2019 Liverpool

Case Study in Data Science and AI: Predicting Organ Damage in Hospitals

Edinburg Data Science CDT

Racialised Lives and the Life Beyond

Equality in Science 2019

Machine Learning for Environmental Grand Challenges

Cam Environmental Risk

Deep Generative Models

UAI Tutorial 2017

How do We Support Underrepresented Groups

Royal Society Diversity Conf.

Planting the Seeds of Probabilistic Thinking

MLSS 2018, Madrid

Variational Inference

NeurIPS 2016 Tutorial

Observations and Inspirations

Sheffield ML Retreat 2017

Variational Inference

Imperial ML Tutorials

Research Areas & Activities

I have a broad range of interests in Machine learning and artificial intelligence that takes a broad view of the field and the many other areas it shapes and that in turn shapes it.

Probabilistic Modelling

I seek to describe problems and processes using the language of probability to make consistent reasoning from evidence.

Bayesian Analysis

Develop methods and algorithms for approximate Bayesian inference and high-dimensional inference and integration.

Variational Inference

I've spent much timestudying a specific class of distributional approximation methods and its applications in practice.

Global Challenges

Tackling big problems in healthcare, weather and climate.

Sociotechnical Systems

Crtical research practuce to understand how ML shapes and is shaped by society.


Committed to thought and action towards social Transformation that supports greater diversity, responsibility, and freedom.

Community and Leadership

Action at the grassroots, community service, board membership, advisory service.

Engagement and Policy

Supporting knowledge transfer in evidence gathering, policy development, and broader engagement.

Writing and Teaching

I develop my craft of writing through my blog, and give regular talks on different aspects of my work.


Podcasts, Interviews, Media coverage

Roles, Leadership & Experience

A summary of some of my roles and educational path.

2013 -

Research Director

DeepMind, London. Director for science, technology and society.

2017 -

Co-founder and Chair of the Board of Trustees

Deep Learning Indaba


Associate Fellow

Leverhulme Centre for the Future of Intelligence, University of Cambridge.


Honorary Professor

Department of Computer Science, University College London (UCL)

Boards and Committees


Oversight Board, Ada Lovelace Institute


Board of Directors, Neural Information Processing Systems Foundation


Chair, International Scientific Advisory Committee for the Pan-Canadian AI Strategy


Board of Directors, International Conference on Learning Representations


Royal Society Diversity and Inclusion Committee

2011 - 2013

Junior Research Fellowship

Fellowship from the Canadian Institute for Advanced Research (CIFAR) at the University of British Columbia, Vancouver. Mentor, Nando de Freitas

2007 - 2011

PhD in Statistical Machine Learning

St John's College, University of Cambridge. Thesis: Generalised Bayesian Matrix Factorisation. Supervisor: Zoubin Ghahramani.

2006 - 2007

Master of Science in Engineering (MSc(Eng)), Distinction

University of the Witwatersrand, Johannesburg. Dissertation: Dynamic Protein Classification: Adaptive Models based on Incremental Learning Strategies. Supervisor: Tshilidzi Marwala.

2002 - 2005

Bachelor of Science in Information Engineering (BSc(Eng)), Distinction

University of the Witwatersrand, Johannesburg. Chancellor's Medal, SIAMM Gold Medal, Bernard Price Prize.

Past Boards and Committees


Board of Directors, International Conference on Machine Learning


Partnership on AI, AI and Shared Prosperity Initiative


Royal Society, Digital Technology and the Planet


Dearest, note how these two are alike: This harpsichord pavane by Purcell And the racer’s twelve-speed bike. The machinery of grace is always simple. This chrome trapezoid, one wheel connected To another of concentric gears, Which Ptolemy dreamt of and Schwinn perfected, Is gone. The cyclist, not the cycle, steers. And in the playing, Purcell’s chords are played away. So this talk, or touch if I were there, Should work its effortless gadgetry of love, Like Dante’s heaven, and melt into the air. If it doesn’t, of course, I’ve fallen. So much is chance, So much agility, desire, and feverish care, As bicyclists and harpsichordists prove Who only by moving can balance, Only by balancing move. --Michael Donaghy


A log of things I'm up to and upcoming events.

















2016 and prior

2023 © Shakir Mohamed