Jacquelyn A. Shelton, Dr. rer. nat., Computer Science: Machine Learning
Hong Kong Polytechnic University
Department of Land Surveying and Geo-Informatics
3D Geospatial Vision Group: Dr. Wei Yao
181 Chatham Road South, Hung Hom, Kowloon
Hong Kong

Email: jacquelyn.ann.shelton ät gmail


My interests in Machine Learning were nurtured in the Department of Empirical Inference at the Max Planck Institute for Intelligence Systems in Tuebingen (formerly MPI for Biological Cybernetics) where I worked on kernel methods and have since ventured to the probabilistic side using Bayesian modelling, and now sometimes even combine them. My primary applications have included neuroscience, image processing, and now climate science. I completed my doctorate in Machine Learning / AI in 2018 at the TU Berlin about large-scale approximate inference in probabilistic models.

My passion and focus now is on developing and applying machine learning / AI, including kernel methods and probabilistic / Bayesian approaches, to critical problems in climate science, ecology, and other environmental domains. I am determined to dedicate my 15 years of ML experience to these domains such that we can interdisciplinarily tackle the core challenges threatening the planet we all share.

I completed my M.S. in Computer Science (Informatik) at the Max Planck Institute for Intelligent Systems in the Department of Empirical Inference headed by Bernhardt Schölkopf with the Universität Tübingen, on semi-supervised Kernel CCA applied to fMRI data with supervision from Andreas Bartels, Matthew Blaschko, Arthur Gretton, and Christoph Lampert. Here is my old homepage at the MPI.

I completed my Dr. rer. nat. (Doctor of Natural Sciences, PhD equivalent) in Computer Science (Machine Learning) from the Technische Universität Berlin (Technical University of Berlin) in the dept. of Software Engineering and Theoretical Computer Science within the Group of Klaus-Robert Mueller, Intelligent Data Analysis. My thesis was entitled Large-scale Approximate EM-style Learning and Inference in Generative Graphical Models for Sparse Coding. I received supervision from Jörg Lücke, Arthur Gretton, and Klaus-Robert Mueller, together composing my doctoral committee with Matthew Blaschko and Manfred Opper.


Publications  [Google scholar]


Conference papers:

Technical reports: