Head of Frontier AI Research | EAI | at AstraZeneca
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Machine Learning and imaging, computer vision, NLP, SaaS and Web technologies with strong python and front end/javascript. Using: TensorFlow, Numpy, Keras, Pandas, OpenCV, PIL, Angular, MaterialCSS, KnockoutJS, Node.js, GIT, Bower, Casper, Grunt, Underscore, Bootstrap, requireJS, D3, JavaScript, JQuery, EXT.js, PhoneGap, GWT, Google App Engine, Google Compute Cloud, ActionScript, SenchaTouch, Adobe AIR, Python, Java, Spring, .NET, CSS[1|2|3], HTML[5], GIMP, Photoshop, Illustrator, Eclipse/Aptana, AppScale, KVM, PyCuda and CUDA... Always aiming to make genuinely useful and usable applications which scale to any size and run on any platform (Windows, OSX, Linux, Android, iPhone, iPad, WebOS, Blackberry). Specialties: Architecture, SaaS, web-based technology, scaling, computer vision machine learning, heterogeneous processing. JavaScript, Node.js, JQuery, Python.
King's College London
MSci (incomplete), Physics with the Philosophy of Science
January 1, 1997 – January 1, 2000
AstraZeneca
Head of Frontier AI Research
June 1, 2026 – Present
AstraZeneca
Head of Machine Cognition
February 1, 2026 – June 1, 2026
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Head of Machine Perception
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Director, Computer Vision
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Instines
August 1, 1998 – August 1, 2003
Smart Expert system for diagnosing specific learning difficulties in dyslexic teens and adults. A battery of standardised tests are assessed with trained machine learning algorithms to produce a diagnosis.
Cultural Fit Analysis
The candidate's diverse experience, ranging from founding startups to leading large enterprise AI initiatives, suggests adaptability and a broad perspective. Their involvement in both research and product development roles indicates a blend of innovation and practical application, which could be a strong cultural fit for organizations valuing both. The focus on AI/ML in life sciences aligns well with the target role of ML Engineer, especially in a research-heavy or applied science context. The long tenure at AstraZeneca, with multiple promotions, indicates loyalty and the ability to thrive within a large corporate structure, while the earlier startup experience shows an entrepreneurial spirit.
Soft Skills & Operational Fit
The candidate's career trajectory, particularly within AstraZeneca, demonstrates strong leadership, strategic thinking, and the ability to drive frontier AI research. Their entrepreneurial background suggests self-motivation, problem-solving, and a results-oriented approach. The descriptions of reducing hosting costs and designing multi-million user systems indicate operational awareness and efficiency. However, without specific psychometric or communication test results, a detailed assessment of stress handling, team collaboration, or communication clarity in a live setting is not possible.