He obtained his PhD in mathematics under the supervision of Prof Andrew Stuart and Prof Martin Hairer at the University of Warwick in 2013. Rebecca Silver, Turing University Liaison Manager (ULM) at the University of Warwick Dr. Sebastian Vollmer , Director of Data Study Groups at the Turing Prof. Colm Connaughton , Director of the Warwick Centre for Complexity Science and deputy-director of the … Sebastian Vollmer Associate Programme Director at Alan Turing Institute Greater Oxford Area. for selecting, tuning, evaluating, composing and comparing machine model implementations written in Julia and other previously disconnected, machine learning algorithms and tools of high quality, written in Julia. 2017 – 2020. How the data is encoded will be referred to as the machine type whereas how the data should be interpreted will be referred to as the scientific type (or scitype). He was a postdoctoral fellow of Arnaud Doucet and Yee Whye Teh at the University of Oxford, working on Bayesian Inference for Big Data with Stochastic Gradient Markov … This paper describes work carried …, During the coronavirus disease (COVID-19) crisis, digital technologies have become a major route for accessing remote care. Sebastian Vollmer. You can update your cookie preferences at any time. Associate Programme Director at Alan Turing Institute. Research Interests: Monte Carlo Methods, Stochastic Gradient Methods, Stochastic Processes, Applications of Data Science. 6:20 - 6:50 PM [Data for Good as Research] Daniela Paolotti - ISI Foundation. This website offers tutorials for MLJ.jl and related packages. MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing machine learning models written in Julia and other languages. I am also the 2019 recipient of the Feuer International Scholarship in Artificial Intelligence as well as a 2019 Data Science for Social Good Fellow and continue to support the fellowship and foundation as one of the principal organisers, reviewers and mentors for the UK programme. Scalable Methods for Statistical Inference and Machine Learning. 7:20 - 7:50 PM My research and training focusses on the translation and application of causal inference methods to improve analysis of real-world data in health and social science. a class label, a count, ...). goals of the MLJ project have been usability, interoperability, extensibility, code transparency, and reproducibility. There are 50+ professionals named "Vollmer", who use LinkedIn to exchange information, ideas, and opportunities. View Sebastian Vollmer’s profile on LinkedIn, the world’s largest professional community. Martin Hairer. Sebastian Vollmer (Turing / Warwick) 1pm - 2pm, Mon, 21 Jan '19. Another class of approximate inference algorithms is the Stochastic Gradient Langevin Dynamics (SGLD) algorithm, originally proposed for approximating expectations with respect to an unnormalised density. how the data is encoded (e.g. More data processing. Cited by. UCL. Oxford, United Kingdom. Developing efficient Stein-based discrepancies for inference and assessment. PhD Student at UCL & The Alan Turing Institute United Kingdom 182 connections. I completed my PhD in September 2013 in Mathematics at the University of Warwick supervised by This has motivated practitioners to investigate approximate inference methods, where the property of asymptotic unbiasedness is relaxed, thus permitting a small amount of bias at the cost of a huge reduction in variance. Arnaud Doucet (Oxford) and YW Teh, AH Thiery, SJ Vollmer. @Students: Projects in Machine Learning and Computational Statistics are available, Lecture this term: Data Science for Social Good - methods and practices, see https://warwick.ac.uk/fac/sci/statistics/currentstudents/modules/st4/st419/additionalinformation/, Mathematics Institute Sebastian Vollmer. Associate Prof. and UKRI Future Leader Fellow, University of Leeds Turing Fellow, Alan Turing Institute Honorary Prof., Beijing … Email: [email protected]. Office: B0.17. # In this tutorial, we are exploring the application of Ridge and Lasso LassoRegressor( lambda = 1.0, fit_intercept = true, penalize_intercept = false, solver = nothing) @897 More broadly, the MLJ project hopes to bring cohesion and focus to a number of emerging and existing, but 9 others named Sebastian Vollmer are on LinkedIn. department of statistics at the University of Warwick. We use cookies to give you the best online experience. I am an associate professor in statistics and mathematics in the Mathematics Insitute and the department of statistics at the University of Warwick. Realistically, the complex dynamics characterising the data generating process can only be expressed as a high-dimensional stochastic model, rendering exact Bayesian inference and classical Monte Carlo methods insufficient. Rough sleeping is a chronic problem faced by some of the most disadvantaged people in modern society. Coronavirus (Covid-19): Latest updates and information. I am also the director of data study groups at the Alan Turing Institute. Speeding up MCMC for scalable Bayesian Inference. ... Sebastian Vollmer. languages. I am also the director of data study groups at the Location: PS0.17 Physical Sciences Predicting risk of hospital admission and readmission of Scottish population . Reece Ebanks. Project aims. View the profiles of professionals named "Vollmer" on LinkedIn. Please login to This tutorial uses the World Resources Institute Global Power Plants Dataset to explore data pre-processing in Julia. Directions. Alan Turing Institute. of this activity will be increased cohesion and synergy within the talent-rich communities developing these tools. please email me, for an idea of potential projects consider the following list: MLJ (Machine Learning in Julia) is a toolbox written in Julia that provides a common interface and meta-algorithms University of Oxford: Deirdre Hollingsworth MIT: Chris Rackauckas Alan Turing Institute: Andrew Duncan (Imperial College London) Swansea University: Michael Gravenor, and Biagio Lucini University of Cambridge: Ronojoy Adhikari University of Warwick: Sebastian Vollmer(Alan Turing Institute) Royal Society Rapid Assistance in Modelling the Pandemic (RAMP): Graeme Ackland (University of … Coventry CV4 7AL Chris Dent. As well as a theme lead for the health and medical sciences research programme. Year; Consistency and fluctuations for stochastic gradient Langevin dynamics. Please let us know if you agree to functional, advertising and performance cookies. Reece Ebanks Illustrator / Designer London. Sebastian obtained his PhD in mathematics under the supervision of Andrew Stuart and Martin Hairer at the University of Warwick in 2013. I’ve worked in application areas ranging from transport, energy, and in particular health and well-being. When analysing data, it is important to distinguish between. Stein’s method is a probabilistic approach to controlling the distance between probability measures in terms of a differential and difference operators. Sebastian Vollmer - The Alan Turing Institute. A key feature of these methods is that they are asymptotically un-biased, i.e. There has been much recent activity on the use of piecewise deterministic markov processes (PDMP’s) as a method for sampling. BIO / Dr Sebastian Vollmer is Director of Data Study Groups and Theme lead of the Health Programme at the Alan Turing Institute in London as well as Associate Professor at the Departments of Mathematics and Statistics at the University of Warwick. Andrew Stuart and Miguel Morin (Alan Turing Institute) Sebastian Vollmer (University of Warwick, Alan Turing Institute) Franz Kiraly (University College London) Mike Innes (Julia Computing) Avik Sengupta (Julia Computing) Valentin Churavy (Massachusetts Institute of Technology) Aims and Milestones Milestones. This tutorial is loosely adapted from this pandas tutorial as well as the DataFrames.jl documentation.It is by no means meant to be a complete introduction, rather, it focuses on some key functionalities that are particularly useful in a classical machine learning context. For students projects March 2018 The potential of using less accurate tests as means of pandemic surveillance is missed, rather than providing reliable medical information about an individual. See others named Sebastian Vollmer … Sebastian Vollmer Sachverständiger Bautechnik bei TÜV SÜD Industrieservice GmbH Böblingen, Baden-Württemberg, Deutschland 48 Kontakte Director of the Data Study Groups is Turing Fellow and Associate Professor at Warwick, Dr Sebastian Vollmer. Prior to this I undertook postdoctoral research with the posterior distribution can be approximated arbitrarily well, provided sufficient samples are generated. 6:50 - 7:10PM [How to use search data to improve your communications strategy] Stefan Byrd-Krueger - ParsonsTKO. Sebastian Vollmer is Director of the Turing Data Study Groups and Health Programme Theme Lead. health and medical sciences research programme.My research interests lie at the interface of applied probability, computational statistics and machine learning, with a particular focus on industrial applications. Machine type vs Scientific Type Why make a distinction? On each tutorial page, you will find a link to download the raw script and the notebook corresponding to the page. Applications of Stats/ML to health and well being. Office: B0.17 Sebastian Vollmer. Guiding Yee Whye Teh (Oxford). Dr Sebastian Vollmer is Programme Co-Director for Health and Director of the Turing Data Study Groups. Sebastian Vollmer is Director of the Turing Data Study Groups and Health Programme Theme Lead. Sebastian obtained his PhD in mathematics under the supervision of Andrew Stuart and Martin Hairer at the University of Warwick in 2013. UCL. University of Warwick Teams worked together over a 12-week period to attempt to solve a wide variety of social problems, using “data to improve the lives of people” in the words of Sebastian Vollmer, … Zeeman Building Education. In contrast to the discretised Langevin dynamics, the SGLD uses an unbiased estimate of the gradient of the log target based on a small subset of the data, thus mitigating computational cost by requiring a reduced number of data point evaluations per sample generated. University of Warwick/Turing. Data Science for Social Good - methods and practices. The only computationally feasible and accurate way to perform statistical inference is with Markov Chain Monte Carlo (MCMC), typically employing methods based on Metropolis-Hastings schemes. The dataset is created from multiple sources and is under continuous update, which means that there are lots of missing data, non-standard characters, etc Hence plenty of material to work with! While this method was first developed with the aim of obtaining quantitative central limit theorems, it has recently been adopted by the computational statistics and machine learning community for various practical tasks including goodness-of-fit testing, generative modeling, global non-convex optimisation, variational inference, de novo sampling, constructing powerful control variates for Monte Carlo variance reduction, and measuring the quality of Markov chain Monte Carlo algorithms. UCL Doctor of Philosophy - PhD Machine Learning. Bilal Akhter Mateen, Harrison Wilde, John M. Dennis, Andrew Duncan, Nick Thomas, Andrew McGovern, Spiros Denaxas, Matt Keeling, Sebastian Vollmer University of Warwick Alan Turing Institute Phone: +44 7901091342. Cited by. Associate Professor. I am a second year PhD student in Statistics supervised primarily by Sebastian Vollmer at Warwick. Sort. Sebastian has 4 jobs listed on their profile. how the data should be interpreted (e.g. Biography. Sebastian Georg Vollmer (German pronunciation: [zeˈbasti̯an ˈɡeːɔʁk ˈfɔlmɐ]; born July 10, 1984) is a former German American football offensive tackle. Verified email at turing.ac.uk - Homepage. MLJ is released under the MIT licensed and sponsored by the Alan Turing … Sort by citations Sort by year Sort by title. Warwick’s Moodle Platform. Learning by doing. As well as a theme lead for the Paper. Sebastian J. Vollmer. Mike Innes (Julia computing) Optional Modules Include:-Machine Learning CS342, and Data Mining CS909 Aberystwyth University, 22-09-2014 - 30-06-2017 BSc (Hons) Joint Mathematics and Physics: rst class Project: \Information Theory and Statistical Mechanics" Isaac Aryee. Int), and. Sebastian Vollmer Associate Programme Director at Alan Turing Institute Greater Oxford Area. Before joining the University of Warwick, I was a lecturer in Statistics at the University of Oxford. Supervisors: Dr. Sebastian Vollmer (U. Warwick/Alan Turing Inst.) In recent years there has been an explosion of complex data-sets in areas as diverse as Bioinformatics, Epidemiology, Finance as well as from Industrial Monitoring Processes. Sebastian obtained his PhD in mathematics under the supervision of Andrew Stuart and Martin Hairer at the University of Warwick in 2013. In addition to other novelties outlined below, MLJ aims to provide first-in-class model composition capabilities. Mary Broome. Articles Cited by Public access. Sebastian Vollmer Affiliation: Department of Statistics, University of Warwick, Coventry, ... our project managers Joshua Sidgwick and Andrea Sipka, the organizer of the Warwick/Turing program Sebastian Vollmer and to the founder of DSSG Rayid Ghani. Isaac Aryee Project Manager at Interserve London. In a heterogeneous patient population diagnosed with type 2 diabetes, it is of interest to examine how patients may vary in their response to second-line drug therapies and what might influence these differences. 6:10 - 6:20 PM Networking . Health Data Scientist at Leeds Institute for Data Analytics and Fellow of the Turing Institute. While this property is advantageous, this comes at a cost: typically such methods exhibit large variance meaning that many samples must be generated to obtain an approximation to within a given error tolerance. PDMP based methods for sampling demonstrate many highly desirable properties: they are non-reversible but remain asymptotically un-biased, and moreover, for tall-data problems sub-sampling can be introduced while preserving the invariant measure. COVID-19 National Core Studies; COVID-19 Data and Connectivity; Data & Connectivity – Information for the Public; International COVID-19 Data Alliance (ICODA) While still in their infancy, these novel methods appear to be advantageous over state of the art MCMC methodology. Therefore, …, COEXI(S)T - Modelling COVID-19 exit strategies for policy makers in the United Kingdom, University of Warwick & The Alan Turing Institute, Gergo, Gaurav Venkataraman, Harrison Wild, Sebastian J. Vollmer Bohner, health and medical sciences research programme, Modelling COVID-19 exit strategies for policy makers in the United Kingdom, Stein’s method for Statistics and Machine Learning, A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services, Digital Health Management During and Beyond the COVID-19 Pandemic: Opportunities, Barriers, and Recommendations, Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness, A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic. Mathematics Insitute and the We investigate whether the additional information from non-diagnostic-quality mass testing can lead to the implementation of a quicker and lower risk exit strategy from lockdown. 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