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 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.
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.
I seek to describe problems and processes using the language of probability to make consistent reasoning from evidence.
Develop methods and algorithms for approximate Bayesian inference and high-dimensional inference and integration.
I've spent much timestudying a specific class of distributional approximation methods and its applications in practice.
Applications of machine learning for important problems, specifiically in healthcare and environment.
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.
Action at the grassroots and community service.
Supporting knowledge transfer in evidence gathering, policy development, and broader engagement.
I develop my craft of writing through my blog, and give regular talks on different aspects of my work.
Podcasts, Interviews, Media coverage
A summary of some of my roles and educational path.
DeepMind, London. Senior Staff Scientist
Deep Learning Indaba
Leverhulme Centre for the Future of Intelligence, University of Cambridge.
Fellowship from the Canadian Institute for Advanced Research (CIFAR) at the University of British Columbia, Vancouver. Mentor, Nando de Freitas
St John's College, University of Cambridge. Thesis: Generalised Bayesian Matrix Factorisation. Supervisor: Zoubin Ghahramani.
University of the Witwatersrand, Johannesburg. Dissertation: Dynamic Protein Classification: Adaptive Models based on Incremental Learning Strategies. Supervisor: Tshilidzi Marwala.
University of the Witwatersrand, Johannesburg. Chancellor's Medal, SIAMM Gold Medal, Bernard Price Prize.
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.
2020 © Shakir Mohamed