Research Staff

Professor Sofia Olhede - Director, UCL Big Data Institute (BDI)

Sofia Olhede is since 2007 a professor of statistics, and since 2008 an honorary professor of computer science at UCL. She was awarded her PhD in 2003 at Imperial College London, where she was a lecturer (assistant professor) and senior lecturer (associate professor) between 2002 and 2006. She is director of the Centre for Data Science at UCL and until last year, chair of the Alan Turing Institute science committee. Sofia served on the Royal Society machine learning committee, the British Academy and Royal Society data governance project, and is a member of the personal data individual access control section of the IEEE global initiative for ethical considerations in artificial intelligence and autonomous systems. She currently holds a European Research Council consolidator fellowship, and previously held a five year Engineering and Physical Sciences Research Council leadership fellowship.

Sofia's research interest is the foundations of data science, including stochastic processes such as time series, point processes and random fields and in particular data taking the forms of networks. She is interested in the interface of policy and algorithms, and data science for social good.

Professor Patrick Wolfe - UCL Statistical Science (Director of the BDI from 2014 to 2017)

Patrick J. Wolfe is professor of statistics and honorary professor of computer science at UCL, and a Royal Society and EPSRC established career research fellow in the mathematical sciences.

From 2001-2004 he held a fellowship and college lectureship in engineering and computer science at the University of Cambridge, where he completed his PhD in 2003 following a National Science Foundation graduate fellowship.  Prior to joining UCL he was assistant (2004-2008) and associate (2008-2011) professor at Harvard University, where he received the Presidential Early Career Award for Scientists and Engineers from the White House. 

Professor Wolfe served as executive director of the UCL Big Data Institute from its inception until July 2017. Externally to UCL, he serves on the Research Section Committee of the Royal Statistical Society, on the Program Committee of the 2015 Joint Statistical Meetings, and as an organizer of the 2016 Newton Institute program on Theoretical Foundations for Statistical Network Analysis.

Summary of research interests: The mathematics of big data. Modelling and inference for graphs and networks; statistical imaging and image processing; time series and time-frequency analysis; audio signal processing and acoustic modeling.

Professor David Jones - UCL Computer Science

David is a professor of bioinformatics and head of the Bioinformatics Group in UCL Computer Science. His main research interests are in protein structure prediction and analysis, simulations of protein folding, Hidden Markov Model methods, transmembrane protein analysis, machine learning applications in bioinformatics, de novo protein design methodology, and genome analysis including the application of intelligent software agents. New areas of research include the use of high throughput computing and Grid technology for bioinformatics applications, analysis and prediction of protein disorder, expression array data analysis and the analysis and prediction of protein function and protein-protein interactions.

Dr Sebastian Riedel - UCL Computer Science

Dr. Riedel is a reader in UCL Computer Science at UCL. He is leading the machine reading laboratory and co-directing the London media technology campus, a joint UCL-BBC research lab. He received his MSc and Ph.D. in computer science from the University of Edinburgh. He was a researcher at the University of Tokyo and the University of Massachusetts Amherst. He is an Allen distinguished investigator and received $1M award from the Paul Allen Foundation to 'move the needle' towards answering broad scientific questions in AI. He is a Marie Curie fellow, was a finalist for the Microsoft Research faculty award and received a Google focused research award. Sebastian is generally interested in the intersection of natural language processing and machine learning, and particularly interested in teaching machines to read and to reason with what was read. 

Dr Emine Yilmaz - UCL Computer Science

Emine Yilmaz is a lecturer (assistant professor) in UCL Computer Science. She is also working as a research consultant for Microsoft Research, Cambridge. She obtained her Ph.D. from Northeastern University in 2008. Her main interests are information retrieval and applications of information theory, statistics and machine learning. She has published research papers extensively at major information retrieval venues such as SIGIR, CIKM and WSDM. She has previously given several tutorials on evaluation at the SIGIR 2015, SIGIR 2012 and SIGIR 2010 conferences and at the RuSSIR/EDBT Summer School in 2011. She has also organized several workshops on Crowdsourcing (WSDM2011, SIGIR 2011 and SIGIR 2010) and User Modeling for Retrieval Evaluation (SIGIR 2013). She has served as one of the organizers of the ICTIR in 2009 and as the demo chair for the ECIR in 2013.

Dr Pierre-André Maugis - Senior Research Associate & Head of Technology Transfer, Big Data Institute

Doctor P-A. Maugis (PhD 2012, Sorbonne University, University of Paris) is a Senior Research Associate and Head of Technology Transfer at the Big Data Institute. Pierre-André is a former student of the École Normale Supérieur, whose high entry requirements selects for academic excellence, demonstrating his raw academic ability. He consolidated his strong background in mathematics and statistics by undertaking his Ph.D at the Sorbonne, with a focus on the econometrics of risk in finance, leading to the publication of several articles in econometric journals. After his Ph.D, following his interest in adapting mathematics to practical problems, he spent several years as a consultant in the banking, finance and insurance sectors in Paris (France). His interests in modeling dependent data led him back to academia, and he is now focusing on developing rigorously founded statistical tools for the analysis of networks, especially the roles hubs, triadic closure and community structures play in the structure and function of real world networks. Although his works on high dimensional dependence and networks are technical, he is still able to have in impact on real problems in econometrics, and to make his findings accessible to a large audience. Since joining UCL he has taken responsibilities within the Big Data Institute and the Stochastic Process Group, organizing conferences, and managing the group's relationships with corporate and academic partners, especially in terms of knowledge and expertise transfers. 

Dr Swati Chandna: Research Associate

Swati received her PhD in Statistics from Imperial College London in November 2013. During her PhD, she worked in the area of statistical signal processing focusing on multivariate time series with applications in oceanography. Her thesis, supervised by Professor Andrew Walden, is entitled 'Frequency domain analysis and simulation of multi-channel complex-valued time series'. From May 2013 to November 2014, she was a post-doctoral researcher at the University of Surrey and a member of the university defence research collaboration working on the 'signal processing solutions for a networked battlespace' project, with focus on model-based source separation techniques. Prior to her PhD, she received an MSc. in applied mathematics from the University of Houston, Texas, and has an undergraduate degree in mathematics from the University of Delhi, India. She is currently Research Associate at the UCL Big Data Institute where she works on network data.

Summary of research interests: statistical signal processing, time series analysis with applications in oceanography, multichannel complex-valued time series, blind source separation, time-frequency analysis, bootstrap, network data.

Dr Rui Fa: Research Associate

Dr Rui Fa received his PhD degree in electrical engineering and information systems from University of Newcastle, UK, in 2007. From January 2008 to September 2010, he held research positions in the University of York and the University of Leeds working in radar signal processing and wireless communication projects. From October 2010, Dr Fa extended his research fields to bioinformatics and computational biology, and joined the University of Liverpool involving in a collaborative research project (in 2013, the project was mover to Brunel University London) with the Universities of Oxford, Cambridge, and Bristol, which is funded by National Institute for Health Research (NIHR) . Dr Fa joined the Bioinformatics Group in UCL Computer Science as a senior research fellow in 2015. His current research interests include bioinformatics and computational biology, systems biology, machine learning, Bayesian statistics, statistical signal processing, and network science. Dr Fa has authored and co-authored more than 60 peer reviewed journal and conference papers, and one research monograph with Wiley.

Dr Shangsong Liang: Research Associate

Shangsong Liang received a B.Sc. and M.Sc. degree from the Northwest A&F University, Xi’an, China, in 2008 and 2011, respectively, and a Ph.D. degree from the University of Amsterdam in 2014, all related to computer science. He is currently a postdoc at UCL. His research interest is information retrieval and data mining. Dr. Liang has published SIGIR, KDD, CIKM, ECIR and Information Processing & Management.

Dr Sandipan Roy: Research Associate

I am currently a Research Associate at the Department of Statistical Science at University College London. I completed my PhD in Statistics at University of Michigan in 2015 under the supervision of Professor George Michailidis and Yves Atchade. My thesis was "Statistical inference and computational methods for large high-dimensional data with network structure". My current research is focused on modeling data with complex high dimensional network structure and provide methodology for estimating the corresponding structure using tools from nonparametric statistics, graphical models and high dimensional inference. 

Dr Weichi Wu: Research Associate

Weichi Wu obtained his Ph.D in statistics from the University of Toronto in May 2015. Supervised by Prof. Zhou Zhou, he worked on change point analysis, M-estimation regression, nonparametric modelling, simultaneous quantile inference in the literature of non-stationary time series.

He is currently a research associate in the Department of Statistical Science and Big Data Institute at UCL, working on network data.

Summary of research interests: Network data, nonparametric statistics, time series, regression analysis, change point analysis.