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Hello & Welcome

I Am

About Me

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.

  • Machine Learning
  • Probabilistic Methods
  • Sociotechnical Systems
  • 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 senior staff research scientist at DeepMind, London, having joined in 2013, where we work towards the goal of developing intelligent and general-purpose learning systems. I also lead a non-profit organisation called the Deep Learning Indaba, whose mission is to Strengthen African Machine Learning and Artificial Intelligence.

I was a programme chair for DALI2019, a programme co-chair for ICLR2019, the Senior Programme Chair for ICLR2020 and the General Chair for ICLR2021. I am a member of the Royal Society’s Diversity Committee (2020-2023), and was elected to the Board of Directors of ICML andd ICLR in 2019.

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.

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

Applications of machine learning for important problems, specifiically in healthcare and environment.

Sociotechnical Systems

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

Transformation

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

Community and Leadership

Action at the grassroots and community 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.

Talks

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

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TechAide 2020

Imaginations of Good, Missions for Change

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Queering Machine Learning

Queer In AI @ ICML2020
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Bayesian Learning (4 Parts)

MLSS 2020
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Decolonising Artificial Intelligence

Intercultural Digital Ethics 2019
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Machinery of Grace

TEDxLSTM 2019 Liverpool
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Case Study in Data Science and AI: Predicting Organ Damage in Hospitals

Edinburg Data Science CDT
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Racialised Lives and the Life Beyond

Equality in Science 2019
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Machine Learning for Environmental Grand Challenges

Cam Environmental Risk
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Deep Generative Models

UAI Tutorial 2017
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How do We Support Underrepresented Groups

Royal Society Diversity Conf.
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Planting the Seeds of Probabilistic Thinking

MLSS 2018, Madrid
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Variational Inference

NeurIPS 2016 Tutorial
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Observations and Inspirations

Sheffield ML Retreat 2017
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Variational Inference

Imperial ML Tutorials

Media

Podcasts, Interviews, Media coverage

Education & Experience

A summary of some of my roles and educational path.

2013 -

Research Scientist

DeepMind, London. Senior Staff Scientist

2017 -

Founder and Trustee

Deep Learning Indaba

2020-2022

Associate Fellow

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

Boards and Committees

2019-2020

Royal Society, Digital Technology and the Planet

2019-2022

Board of Directors, International Conference on Machine Learning

2019-2022

Board of Directors, International Conference on Learning Representations

2020-2023

Royal Society Diversity Committee

2020-2021

Partnership on AI, AI and Shared Prosperity Initiative

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.

2016 - 2018

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.

2016 - 2018

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

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

Machines

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

Events Log

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

Upcoming

 

2020

 

2019

 

2018

 

2017

 

2016 and prior

2020 © Shakir Mohamed