My research lies at the interface between computer perception (which builds artificial systems for understanding images, sounds and videos), neuroscience (which tries to understand the brain) and machine-learning (which provides a theoretical framework for learning from data). The goal is to develop systems that solve important problems, drawing inspiration from the brain. For example, figuring […]
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I have very broad interests in probabilistic inference in machine learning, covering both unsupervised, supervised and reinforcement learning. I’m particularly interested in design and evaluation of non-parametric methods such as Gaussian processes and Dirichlet processes. Exact inference in these models is often intractable, so one needs to resort to approximation methods, such as variational techniques […]
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I studied Computer Science and Cognitive Science at the University of Pennsylvania and obtained my PhD from MIT in 1995. From 1995 to 1998, I was a Postdoctoral Fellow at the University of Toronto, working with Geoff Hinton. I was one of the founding faculty members of the Gatsby Computational Neuroscience Unit at UCL (1998-2005) […]
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Since Sep 2016, I am a University Lecturer (equivalent to US Assistant Professor) in Machine Learning at the Department of Engineering in the University of Cambridge, UK. I was before a postdoctoral fellow in the Harvard Intelligent Probabilistic Systems group at the School of Engineering and Applied Sciencies of Harvard University, working with the group […]
Read more →I am a postdoctoral fellow working with José Miguel Hernández-Lobato on Bayesian optimization to accelerate the discovery of novel materials and chemical reactions. My research is supported by an Early Postdoc.Mobility fellowship of the Swiss National Science Foundation. From 2015 to 2018, I was pursuing my Ph.D. in theoretical chemistry under the supervision of Markus […]
Read more →John Bronskill is a postdoc in the Machine Learning Group at the University of Cambridge supervised by Richard Turner . He received a Bachelor’s degree and a Master’s degree in Electrical Engineering from the University of Toronto and a PhD in Engineering from the University of Cambridge.
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Christian Steinruecken is a post-doctoral researcher in machine learning, working on the Automatic Statistician Project with Prof Zoubin Ghahramani.
Read more →I’m a PhD student studying machine learning at the University of Cambridge in the Computational and Biological Learning Lab. My advisor is Dr. Richard Turner. I’m interested in meta-learning, neural processes, approximate inference methods and Bayesian optimization. I was recently a visiting student at MILA under the supervision of Yoshua Bengio. Previously, I completed a […]
Read more →I am a first year PhD student supervised by Prof Carl Rasmussen. I completed my undergraduate degree (MEng, BA) here at Cambridge University Engineering Department in 2017, and am affiliated with Churchill college. My research interests are in Bayesian inference in non-linear time series models.
Read more →I’m a PhD student supervised by Adrian Weller and advised by José Miguel Hernández-Lobato (started in October 2019, Sidney Sussex College). I am funded by the Department of Engineering and Trust Scholarship. Before entering a PhD program I’ve received a Bachelor’s degree in Computer Science from Ural Federal University (2017, Yekaterinburg, Russia) and Master’s degree […]
Read more →Elre joined the PhD program in October 2018. She is supervised by Richard Turner and advised by Adrian Weller. She previously studied at the University of Pretoria, South Africa, where she completed her BSc, BSc(Hons) and MSc in Computer Science, as well as a BSc (Hons) degree in Mathematics. She is a member of Churchill […]
Read more →Jonathan is a PhD student in the machine learning group under the supervision of Richard Turner, and is funded by the Harding Distinguished Scholarship Programme. After graduating from the University of Kent with a BSc in Computer Science, Jonathan spent several years working in finance as both a systems programmer and trader. He later studied […]
Read more →I am a PhD student in the Machine Learning Group at the University of Cambridge, supervised by José Miguel Hernández-Lobato, and a member of Darwin College. Before starting the PhD, I was a consultant for Wolfram Research where I helped develop the deep learning library for Mathematica. I hold an MPhil in Advanced Machine Learning […]
Read more →Originally from Zaragoza, Spain, Javier graduated from the University of Zaragoza in Telecommunications Engineering (EE/CS) in 2018. Javier went on to receive an MPhil in Machine Learning and Machine Intelligence from the University of Cambridge in 2019. Following this, he joined the group as a PhD student in 2019, under the supervision of Dr. José […]
Read more →Umang is a PhD student in University of Cambridge’s Machine Learning Group supervised by Adrian Weller. He completed a joint bachelors-masters in Electrical and Computer Engineering at Carnegie Mellon University, where he was advised by José Moura and worked with Pradeep Ravikumar and Zico Kolter. He is funded by the Trust and Transparency Initiative at […]
Read more →Austin is a PhD student in the Cambridge Machine Learning group, researching machine learning with a focus on scientific applications (especially chemistry and materials). He is supervised by José Miguel Hernández-Lobato and advised by Adrian Weller. Before coming to Cambridge, he received a BASc in nanotechnology engineering from the University of Waterloo in Canada. He […]
Read more →Yen-Chen is a PhD student in the Machine Learning Group at the University of Cambridge, supervised by Prof. Carl Edward Rasmussen. He received an BSc and MSc in Electrical Engineering from National Taiwan University. He is funded by Cambridge Trust. His work is about model-based reinforcement learning for spoken dialogue systems.
Read more →I’m a PhD student, supervised by José Miguel Hernández-Lobato and Zoubin Ghahramani. I did my undergraduate degree at the University of Oxford, supervised by Frank Wood and Jan-Willem van de Meent. My core interests are: exploration in reinforcement learning, Bayesian optimisation and bandits.
Read more →Hi there, I am Erik, a PhD student in the Machine Learning Group at the University of Cambridge, supervised by José Miguel Hernández-Lobato. As a Cambridge-Tübingen fellow, I will also spend a year of my PhD at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, at the department led by Bernhard Schölkopf. My […]
Read more →I am a Marie Sklodowska-Curie Early Stage Researcher in the MAGISTER consortium which seeks to utilize machine learning to understand and predict thermoacoustic oscillations in aircraft engines or gas turbines. My job, as I see it, is to serve as a liasion between the probabilistic machine learning group led by my PhD supervisor Professor Carl […]
Read more →Jiri Hron joined the PhD programme in October 2017 as a member of Trinity College with financial support of Nokia and EPSRC. He is supervised by Zoubin Ghahramani and advised by Adrian Weller. Google Scholar
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Originally from Hamburg, Germany, Julius studied Mathematics (MSci) at Imperial College London and Artificial Intelligence (MSc) at UPC Barcelona and TU Delft. He joined the Cambridge-Tübingen programme in October 2018 where he is supervised by Adrian Weller in Cambridge and Bernhard Schölkopf at the Max Planck Institute for Intelligent Systems in Tübingen. He is funded […]
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Hey! I am a PhD student at the Machine Learning Group at the University of Cambridge, supervised by Dr Richard Turner, and a member of Christ’s College. Previously, I was a machine learning researcher for Invenia Labs; they solve problems in the fields of machine learning, finance, electricity systems and markets, and complex systems. […]
Read more →Andrew is a PhD student in the Machine Learning Group supervised by Dr Richard Turner, starting in October 2018. He received his BA and MEng in Information and Computer Engineering from the Cambridge University Engineering Department in 2018. He is funded by the Trinity Hall Research Studentship and the George and Lilian Schiff Studentship. His […]
Read more →I am a PhD student in the Machine Learning Group at the University of Cambridge since 2018. I have a broad interest in the field of probabilistic machine learning, especially Bayesian approximate inference methods, Bayesian deep learning, and Gaussian processes. Previously I received BSc in mathematics and a MRes in machine learning and computational statistics […]
Read more →Ross received the BA and MEng degrees in Engineering from the University of Cambridge, specialising in Information and Computer Engineering. His Part IIB Project, Parallelising Sequential Monte Carlo, was completed under the supervision of Dr Sumeetpal Singh in the Signal Processing and Communications Lab. He joined the Machine Learning Group as a PhD student in […]
Read more →David received an MPhil in Machine Learning, Speech and Language Technology from Cambridge University in 2018. Prior to this, David received a BA in Mathematics from Williams College. David began his PhD in 2018 and is supervised by Prof. Carl Rasmussen. David is funded by a Dr. Herchel Smith Fellowship. David is interested in Bayesian […]
Read more →Sebastian is a PhD student in the Machine Learning Group supervised by Prof. Carl Rasmussen. He joined in October 2018, after completing his BA and MEng in Information and Computer Engineering at the Cambridge University Engineering Department. He is funded by a Gates Cambridge Scholarship, and his research interests include approximate inference, Bayesian deep learning, […]
Read more →Chaochao Lu is a PhD student of Machine Learning Group at the University of Cambridge, where he is co-supervised by Prof. Zoubin Ghahramani and Prof. José Miguel Hernández-Lobato, advised by Prof. Carl Edward Rasmussen, and also jointly supervised by Prof. Bernhard Schölkopf and Dr. Michael Hirsch at the Max Planck Institute for Intelligent Systems under […]
Read more →I am a PhD student in the Machine Learning Group at the University of Cambridge, supervised by Prof. Carl Edward Rasmussen. I received an MSc in Computer Science from the University of Oxford, and a BSc in Computer Science from Universitat Pompeu Fabra, Barcelona. I am funded by the Department of Engineering. My work is […]
Read more →Wenbo obtained his MPhil degree in Machine Learning, Speech and Language Technology from University of Cambridge in 2017. Before that, he graduated with a BA and MEng in Information and Computing Engineering from University of Cambridge. He joined the MLG as a PhD Candidate in Oct. 2017 supervised by Dr. José Miguel Hernández-Lobato. He is […]
Read more →Jonathan graduated from Cambridge University with a MPhil in Machine Learning, Speech and Language Technology in 2017. Before that he graduated with a BSc and MSc in engineering and applied statistics from the Ben-Gurion University of Israel. He is funded by a Samsung doctoral studies grant and supervised by Dr. José Miguel Hernández-Lobato. His research […]
Read more →Siddharth graduated with a Master’s in Engineering from the University of Cambridge in 2017. He joined the Machine Learning Group, in CBL, in October 2017 as a PhD student, supervised by Dr Richard Turner. He is funded by EPSRC. His research focusses on approximate Bayesian inference techniques, usually variational inference, applied to a variety of […]
Read more →Robert received his M.Sc. in Computer Science in 2017 from the Technical University of Darmstadt, where he worked with Prof. Gerhard Neumann, Prof. Jan Peters and Prof. Stefan Roth. He joined the group as a Ph.D. student in October 2017. He is supervised by Prof. Carl Rasmussen. His research interests include reinforcement learning and Bayesian […]
Read more →Marton has received his BA in Computer Science in 2016 and his MPhil in Machine Learning, Speech and Language Technology in 2017 from Cambridge University. He joined the group as a PhD student in October 2017. He is supervised by Dr. José Miguel Hernández-Lobato and he is funded by EPSRC. His interests include Bayesian Optimization […]
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Alessandro completed a BA in Philosophy before moving on to a Master’s degree in Machine Learning at UCL. Continuing the work of his Master’s thesis, he spent one year at the Gatsby Computational Neuroscience Unit working with Professor Sahani on latent variable dynamical systems. Prior to joining the Cambridge-Tübingen Machine Learning group in October 2016, […]
Read more →John Bradshaw graduated with a Master’s of Engineering from the University of Cambridge in 2015. After working for a year in a startup that applied deep learning to industrial problems he joined the group as a PhD student in 2016. He is funded by the EPSRC. His email address is jab255 -at- cam.ac.uk
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