Maria Lomeli Garcia
About me
I am a Research Associate, working with Zoubin Ghahramani at the Machine Learning group, CBL, University of Cambridge and I am a member of Trinity Hall college.
I studied my PhD at the Gatsby Unit, UCL, my supervisor was Yee Whye Teh. Before coming to the UK, I did an MSc in Mathematical Sciences at IIMAS,
Universidad Nacional Autónoma de México, advised by Ramsés Mena.
Research interests
 Statistical Machine Learning
 Bayesian Nonparametrics
 Reproducing kernel Hilbert spaces
 Exact inference methods (MCMC, SMC)
News
 I am attending the DALI workshop in Lanzarote, Spain, April, 2018.
 I am invited to give a talk at Amazon, Cambridge in February, 2018.
 I am invited to give a talk at the University of Warwick, Statistics Algorithms seminar in April, 2018.
 I am invited to give a talk at the UCL, CSML lunchtime seminar in February, 2018.
 I am invited to give a talk at the University of Glasgow in February, 2018.
Journal publications
 Lomeli, M., Favaro, S., Teh, Y. W.,'' A marginal sampler for Stable PoissonKingman mixture models'', Journal of Computational and Graphical Statistics, 2017, Vol 26, 4453 JCGS.

Favaro, S., Lomeli, M., Nipoti, B., Teh, Y.W., ''Stickbreaking representations of stable PoissonKingman models'' , Electronic Journal of Statistics, 2014, Vol. 8, pp 10631085 EJS.

Favaro, S., Lomeli, M., Teh, Y.W.,''On a class of stable PoissonKingman models and an effective marginalized sampler'', Statistics and Computing, 2014, Vol 25, pp 6778
StCo.
Proceedings
 Lomeli, M., Favaro, S.,Teh, Y.W., 2015, ''A hybrid sampler for PoissonKingman mixture models'', Neural information Processing Systems NIPS
 Sejdinovic, D., Strathmann, H., Lomeli Garcia, M., Andrieu, C., Gretton, A., 2014,''Kernel Adaptive MetropolisHastings'', International Conference in Machine Learning ICML

Favaro, S., Lomeli, M., Nipoti, B., Teh, Y.W., 2013, ''Stickbreaking representations of stable PoissonKingman models'', Complex Data Modelling and Computationally Intensive Methods for Estimation and Prediction conference.
Workshops
 BloemReddy, B., Mathieu, E., Foster, A., Rainforth, T., Ge, H., Lomeli, M., Ghahramani, Z., Teh, Y.W., 2017, ''Sampling and inference for discrete random probability measures in probabilistic programs'', Approximate Inference workshop, NIPS
Theses and projects
 General Bayesian inference schemes in infinite mixture models
PhD thesis, University College London
Arxiv version: arXiv:1702.08781
 Consistencia Posterior de Modelos Bayesianos No Paramétricos
(Posterior Consistency of Bayesian Nonparametric Models)
MSc project, UNAM
Available upon request (In Spanish)
 Qué tan "expertos" son los Expertos: Un Modelo de Evaluación y Pronóstico
Undergraduate thesis, ITAM
Available upon request (In Spanish)
Talks
 August 30, 2017. Talk at the 2017 SMC workshop
 June 7, 2017. Talk at the ''Congreso Bayesiano de América Latina''
 June 14, 2016. Talk at the ''Bayes Legacy'' sesssion, 13th ISBA Wold meeting in Sardinia, Italy
 June 2, 2016. Talk at the Machine Learning group, CBL, University of Cambridge
 May 5, 2016. Talk at Machine Learning reading group, CBL, University of Cambridge
 July 16, 2015. Talk at CBL, University of Cambridge
 June 22, 2015. Talk at the 10th
Bayesian Nonparametrics conference
 June 15, 2015. Talk at the 9th
Bayesian Inference for Stochastic Processes conference
 January 26, 2014. Talk
at the Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas,
Universidad Nacional Autónoma de México
 October 24, 2014. Talk
at the Computational Statistics seminar, University of Oxford
 September 24, 2014. Talk
at CBL, University of Cambridge
 March 3, 2014. Talk at the workshop
Advances in Scalable Bayesian Computation, available
online here
Teaching
 Teaching assistant, Part II Statistical modelling course, Statslab, University of Cambridge (Lent, 2018)
 Coding lab demonstrator, APTS, Statistical computing module for Statistics PhD students, University of Cambridge (December, 2017)
 Coding lab demonstrator, MLSALT1 graduate course, University of Cambridge (Michaelmas, 2017)
 Coding lab demonstrator, 3F8 undergraduate course, University of Cambridge (Lent, 2017)

Teaching assistant, Statistical Data Mining and Machine Learning MSc in Applied Statistics course, University of Oxford (Hilary term 2014 and 2015)
 Teaching assistant, Probabilistic and Unsupervised Learning graduate course, University College London (Autumn, 2012)
 Lecturer, Stochastic Processes, undergraduate course, Instituto Tecnológico Autónomo de México (Summer, 2011)
Reviewing
 Biometrika
 Scandinavian Journal of Statistics
 Computational Statistics and Data Analysis
 Statistics and Computing
 International Conference in Machine Learning

Neural Information Processing Systems

AISTATS
Miscellaneous
I was one of the organisers of our CSML Lunch Talk Series.
Contact
maria.lomeli@eng.cam.ac.uk
Computational and Biological Lab
Department of Engineering
University of Cambridge