Fellow Short Talks – Dan Olteanu, Ricardo Silva & Rob Procter

Date: 29 November 2016

Time: 11:00am – 12:30pm

Watch the live stream here: bit.ly/TuringLive

Recordings will also be made available on our YouTube channel following the event. By attending the event you consent to audio and video recording and its/their publication.


Professor Dan Olteanu (OXFORD)

Bio

Dan Olteanu is an associate professor in the Department of Computer Science and Fellow of St Cross College at the University of Oxford. He has also taught at University of California, Berkeley, University of Munich, Saarland University, and Heidelberg University. He received his PhD in Computer Science from University in Munich in 2005.

Research
His research interests are in database systems and theory. Dan contributed to XML query processing, incomplete information and probabilistic databases, and more recently to factorized databases and the industrial-strength LogicBlox database and analytics system. He is a co-author of the book “Probabilistic Databases” (2011). Olteanu has served as associate editor for PVLDB’13 and IEEE TKDE, as track chair for ICDE’15, group leader for SIGMOD’15, and will serve as vice chair for SIGMOD’17. His current research is supported by awards from Amazon, Google, and LogicBlox, and an ERC consolidator grant.
View Professor Dan Olteanu’s personal website at http://www.cs.ox.ac.uk/dan.olteanu/


Professor Ricardo Silva (UCL)

Bio

Ricardo Silva got his PhD at Carnegie Mellon in 2005, in the newly formed Machine Learning Department. He moved to UCL as a Senior Research Fellow in the Gatsby Computational Neuroscience Unit. After a year at the Statistical Laboratory at Cambridge as a postdoc, Ricardo returned to UCL to join the Department of Statistical Science as a Lecturer in 2008.

Research
My research focuses on: 1 Algorithms for probabilistic inference: approximations for likelihoods and posterior distributions based mostly of variational approximations and Markov chain Monte Carlo. 2. Latent variable models: measurement error models and generalisations of probabilistic principal component analysis, as well as the modelling of network data; 3. Machine learning for causal inference: identification and discovery of models with unmeasured confounding and measurement error. I have also recently focused on applied work on human movement modelling, including partners such as TfL (for traffic data), UCL Institute of Behavioural Neuroscience (human navigation strategies) and Stratagem Ltd (sports modelling).
View Dr Ricardo Silva’s personal website at http://www.homepages.ucl.ac.uk/~ucgtrbd/


Professor Rob Procter (WARWICK)

Bio

Rob Procter is Professor of Social Informatics and deputy head (research) in the department of Computer Science, Warwick University. Previously he has held positions at Manchester and Edinburgh universities. His research interests are strongly inter-disciplinary, and include social media analytics and social data science

Research
Rob’s current data science-related research includes the use of machine learning to: predict the veracity of content posted in social media and; analyse factors that influence the propagation of inflammatory postings. He is also interested in a number of other areas related to data science. These include methodological and ethical issues in the use of new forms of data in social research. More generally, he is interested: in applications of big data analytics in domains such as smart cities and healthcare; investigating social and technical issues that may influence the adoption of data science across academic, commercial and public sectors.