John Shawe-Taylor was awarded a scholarship to study mathematics at Trinity College Cambridge in 1970. He completed an undergraduate degree in mathematics at the University of Ljubljana in Slovenia, then part of Yugoslavia. He obtained a PhD in mathematics at the University of London in 1986 after which he moved into computer science taking a lectureship initially at Royal Holloway, but later becoming a professor at the University of Southampton where he lead the ISIS research group. In 2006 he moved to UCL to become the founder director of the Centre for Computational Statistics and Machine Learning.
John Shawe-Taylor has contributed to a number of fields ranging from graph theory through cryptography to statistical learning theory and its applications. However, his main contributions have been in the development of the analysis and subsequent algorithmic definition of principled machine learning algorithms founded in statistical learning theory. This work has helped to drive a fundamental rebirth in the field of machine learning with the introduction of kernel methods and support vector machines, driving the mapping of these approaches onto novel domains including work in computer vision, document classification, and applications in biology and medicine focussed on brain scan, immunity and proteome analysis. He has published over 300 papers and two books that have attracted over 42000 citations.
He has also been instrumental in assembling a series of influential European Networks of Excellence. The scientific coordination of these projects has influenced a generation of researchers and promoted the widespread uptake of machine learning in both science and industry that we are currently witnessing.
He is Head of the Computer Science Department at UCL where he has overseen a significant expansion and witnessed its emergence as the highest ranked Computer Science Department in the UK in the recent 2014 UK Research Evaluation Framework (REF). Under his leadership the department has developed an innovative education programme at both undergraduate, masters and research level that engages students directly with industrial projects and has led to UCL Computer Science playing a leading role in the growth of London as a hub for start-up tech companies.
Davor Orlic completed his MA in Digital Humanities at University College London, is a researcher at the Center for knowledge transfer in information technologies, Jožef Stefan Institute and works as COO of the Knowledge 4 All Foundation Ltd. Part of his portfolio is also the VideoLectures.Net website which has allowed him to work closely with the OER movement, especially MIT OpenCourseWare, OpenCast Foundation (creating the Matterhorn software) and OpenCourseWare Consortium. Davor was also the main organizer of the “OCWC Global Conference 2014”. He has created and developed OpeningupSlovenia and acts as its project lead and is the contact person for the UNESCO Chair on Open Technologies for OER and Open Learning.
Delmiro Fernandez-Reyes is Reader in Digital Health and Intelligent Systems at the Department of Computer Science, Faculty of Engineering University College London, UK. He is also Adjunct Reader in Pediatrics at the College of Medicine of the University of Ibadan (COMUI), Nigeria. His unique interdisciplinary expertise in pediatrics, molecular experimental medicine, and machine learning has translated in large clinical biomedical-science studies where state-of-the-art computational methods are at unison with novel molecular and cellular high-throughput technologies to underpin the discovery & validation of disease biomarkers, their mechanisms and their interventional use for improving childhood global health in low-to-middle income sub-Saharan West Africa.
His research focuses on pediatric infectious diseases and biomedical data-science with extensive work on Global Health Grand Challenges such malaria and tuberculosis. As a Medical Research Council Principal Investigator, he created and lead a multi-site research group to study the pathogenesis of childhood life-threatening severe malaria. In close partnership with COMUI, he founded and currently directs the Childhood Malaria Research Group, a world-leading clinical malaria and research unit, based at the University College Hospital Ibadan where he has been carrying-out large studies of childhood severe malaria. He has deployed effective study designs to acquire large multidimensional data [clinical, epidemiological and experimental: (immunological, proteomic, genomic)] from pediatric cohorts. He pioneered the use of machine learning approaches on plasma proteomics to understand the complex spectrum of disease of childhood severe malaria. His team has discovered and validated protein and genetic biomarkers of severe malaria that currently underpin his research and development of scalable computational clinical decision-support systems for the sub-Saharan region.
He has recently received a prestigious £1.5 million UK Engineering and Physical Sciences Council Global Challenges Award for research, development and deployment of an AI-driven robotic malaria diagnosis platform in sub-Saharan West Africa. He has also integrated and co-leads interdisciplinary research teams that exploit advances in the computational sciences to tackle global challenges in the African region. The impact of his over a decade research in the African region has recently crystalized in the creation of a joint University College London and University of Ibadan African interdisciplinary center of excellence to develop state-of-the-art computational approaches to address global challenges to propel improvements in Global Health and Wellbeing.
Dr. Emine Yilmaz is a reader (associate professor) at University College London, Department of Computer Science and a faculty fellow of the Alan Turing Institute on Data Science. She also works as a research consultant for Microsoft Research, Cambridge and serve as one of the organisers of the Centre for Computational Statistics and Machine Learning (CSML) at UCL. Her research interests lie in the areas of information retrieval, data mining, and applications of machine learning, probability and statistics. She am also a co-founder of the company, UserContext.AI, where we focus on user engagement, personalisation, inferring users interests and recommendation based on users histories and contents they have visited in the Web.
She is a recipient of the Early Career Fellowship from the Engineering and Physical Sciences Research Council (EPSRC). To this date, I have received approximately 1.4 million GBP external funding from funding agencies including European Union, EPSRC, Google and Elsevier. She is an elected member of the executive committee for ACM SIGIR and serve as a co-editor-in-chief for the Information Retrieval Journal. I am the recipient of Karen Sparck Jones 2015 Award for the contributions of my work to the information retrieval research in 2015 and am one of the recipients of the Google Faculty Research Award in 2014/2015.