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April 12, 2014
Three of my papers with N. Houlsby and Z. Ghahramani have been accepted for presentation at the International Conference on Machine Learning (ICML) 2014.
February 20, 2014
I gave a talk on Determinantal Point Processes with Hong Ge at the Machine Learning Group in Cambridge. The slides for the talk are available here.
February 12, 2014
I gave a talk on Gaussian process conditional copulas at the first MSR-MLG (Microsoft Research and Machine Learning Group) joint meeting in Cambridge. The video is available here.
October 21, 2013
I will be presenting the workStochastic Inference for Scalable Probabilistic Modeling of Binary Matrices” at the NIPS Workshop Randomized Methods for Machine Learning, this December in Lake Tahoe, USA.
October 12, 2013
I will be giving a talk as part of the Oxford-Man Institute Monday Sandwich Seminar Series in the University of Oxford on Monday 28th. The talk will be about conditional copulas with applications to financial time series.
October 12, 2013
http://jhml.org was set up.

Short Biography

Since 2011 I have been a postdoctoral research associate in the Machine Learning Group at the Engineering Department of Cambridge University (UK). During my first two years in Cambridge I worked in a collaboration project with the Indian multinational company Infosys Technologies. I also spent two weeks giving lectures on Bayesian Machine Learning at Charles University in Prague (Czech Republic). From December 2010 to June 2011, I was a teaching assistant at the Computer Science Department in Universidad Autónoma de Madrid (Spain), where I completed my Ph.D. and M.Phil. in Computer Science in December 2010 and June 2007, respectively. I also obtained a B.Sc. in Computer Science from this institution in June 2004, with a special prize to the best academic record on graduation. My research revolves around model based machine learning with a focus on probabilistic learning techniques and with a particular interest on matrix factorization methods, copulas, Gaussian processes and sparse linear models. A general feature of my work is also an emphasis on fast methods for approximate Bayesian inference that scale to large datasets.

Contact Information

Department of Engineering, University of Cambridge
Trumpington Street, Cambridge CB2 1PZ, UK
Tel. +44 12223 748512
Email: jmh233-at-cam.ac.uk

Curriculum Vitae

My CV can be downloaded from this link [pdf].