I am a Senior Machine Learning Scientist at Amazon Research Cambridge and a Visitor Researcher of the department of Mathematics and Statistics of Lancaster University. My research focuses on machine learning aspects of data science, mainly on the development of 'surrogate modelling' approaches for optimization and experimental design. I am interested in probabilistic modelling techniques, such as Gaussian processes, that allow to quantify uncertainly and improve the data efficiency of autonomous systems.
Amazon Research Cambridge
Poseidon House, Castle Park, Cambridge CB3 0RD
- Phone: +44 (0)1223 376700
- Mail(s): gojav [a] amazon.com
Workshops and summer schools
Gaussian Process Summer School, Sheffield, UK, 12-14 September 2017 (with Mauricio Alvarez Neil Lawrence, Rich Wilkinson, Jeremy Oakley and MLSitran).
Gaussian Process and Bayesian optimization Masterclass, Lancaster, UK, 6-7 February 2016 (with Neil Lawrence).
NIPS workshop in Bayesian optimization, Barcelona, Spain, 10 December 2016 (with Roberto Calandra, Frank Hutter, Bobak Shahriari and Ryan Adams).
Gaussian Process Summer School, Sheffield, UK, 12-14 September 2016 (with Neil Lawrence, Rich Wilkinson, Jeremy Oakley and MLSitran).
Workshop on Uncertainly Quantification, Sheffield, UK, 5 September 2017 (with Neil Lawrence, Rich Wilkinson, Jeremy Oakley and MLSitran).
Course in Bayesian Optimization, Pereira, Colombia, 27-130 October 2015 (with Mauricio Alvarez).
Gaussian Process Summer School, Sheffield, UK, 14-16 September 2015 (with Neil Lawrence and MLSitran).
Workshop on Gaussian Processes for Global Optimization, Sheffield, UK, 17 September 2015 (with Neil Lawrence and MLSitran).
, Python package for Bayesian Optimization.
, Python package for Gaussian processes.
February 2017: In Berlin, at the Gaussian processes approximation workshop, talking about Bayesian Optimization with Tree-structured Dependencies.
February 2017: At Lancaster university for a Masterclass in Bayesian optimization.
September 2016: I start my new position in Amazon, Cambridge!
April 2016: Our paper "Variational Auto-encoded Deep Gaussian Processes" (with Zhenwen Dai, Andreas Damianou and Neil Lawrence) is accepted in ICLR'16.
December 2015: Our works "GLASSES: Relieving The Myopia Of Bayesian Optimisation" (with Michael Osborne and Neil D. Lawrence) and "Batch Bayesian Optimization via Local Penalization" (with Z. Dai, P. Hennig and N. Lawrence) are accepted in AISTATS'16.
December 2015: In Montreal at NIPS 2015, with two posters at the Workshop in Bayesian Optimization and giving a talk and the workshop in Computational Biology.
October 2015: Our COST Action Proposal OC-2015-1-19400 "European Cooperation for Statistics of Network data science" has been accepted for funding. With Erst Wit and others.
October 2015: At the Pereira University of Technology, Pereira, Colombia, giving a course on Bayesian Optimization (invited by Mauricio Alvarez).
October 2015: our paper "Protein biogenesis machinery is a driver of replicative aging in yeast" is accepted for publication in eLife (with Georges E Janssens, Anne C Meinema, Javier González, Justina C Wolters, Alexander Schmidt, Victor Guryev, Rainer Bischoff, Ernst C Wit, Liesbeth M Veenhoff, Matthias Heinemann).