Mona is the founder and CEO of AI for Global Goals, which aspires to connect AI talents to the industries and companies whose missions are aligned with the UN's Sustainable Development Goals (SDGs). Her main interest is in training, up-skilling and re-skilling AI scientists by organising academic/educational events such as Oxford ML Summer schools, workshops and hackathons.
She has a D.Phil. in Biomedical Engineering from the University of Oxford, and has years of experience in the biomedical industry, and deep tech venture capital.
Area Chair - Statistical ML
Thomas is the Professor of Neuroimaging Statistics at the Oxford Big Data Institute. He is a statistician with a solitary focus on modelling and inference methods for brain imaging research. He has a unique background, with both industrial and academic experience, and diverse training. He was the Director of Modelling and Genetics at GlaxoSmithKline's Clinical Imaging Centre, London, where he developed methods for fMRI clinical trials and imaging genetics studies.
He is a developer of both the Statistical Parametric Mapping (SPM) and FMRIB Software Library (FSL) tools, and is well known for bringing advanced statistical methodology to brain imaging and making it accessible to non-statisticians.
Reza is currently the Chief Scientist at AIG, and Investigator (in machine learning and medicine) at Deep Medicine program of The University of Oxford. Reza's current research at Oxford is focused on probabilistic machine learning, deep sequence models, biomedical informatics, and population health.
Reza’s team at AIG (i.e., Investments AI) is a group of scientists, engineers, designers, product managers, and digital strategy experts, focused on building AI-first products in FinTech.
Kazem is a cardiologist, epidemiologist and health services researcher with interest in prevention and management of chronic diseases. He has led the design, coordination and reporting of multi-centre randomized trials, collaborative meta-analyses and large-scale observational studies that have investigated the burden, causes and management of cardiovascular diseases. He is the Director of the Oxford Martin programme on Deep Medicine which is using some of the largest and most complex biomedical datasets that have ever been collected to generate insights into complex disease patterns, risk trajectories and treatment effects.
Area Chair - AI for Good
Yu Yu is currently the director of data science at BNY Mellon. She joined the Advanced Digital Solutions team at BNY Mellon in 2019, bringing over 10 years of statistical modeling expertise to the firm. She is responsible for researching and validating AI and ML solutions that can help improve business outcomes for the bank as well as for its clients by driving automation, reducing risk and delivering actionable insights. Yu Yu previously held data science positions at both Point72 and AIG Science, where she leveraged cutting-edge statistical modeling and ML techniques to solve a wide range of investment and business problems. Before her industrial career, she was a tenure-track professor of marketing at Georgia State University for nearly five years.
Area Chair - AI for Good
Moez Draief is currently the Global Chief Scientist and VP of Data Science and Engineering at Capgemini. Previously, he was the Chief Scientist for Artificial Intelligence at Noah’s Ark Lab of Huawei Technologies.
Before moving to industry in 2016, he worked as an academic for a number of years, including a position at Cambridge University as a Marie Curie Research Fellow and a faculty position at Imperial College London.
He recently joined the London School of Economics as a visiting professor in the statistics department.
His research focuses on graph representations, online learning and game theory.
Area Chair - NLP
Karo is the Global Head of NLP and a Science Director at AIG where his NLP team develop advanced NLP technologies and AI-first products for the asset management arm of AIG. Before starting a specialist NLP practice at AIG, Karo was the Founder CTO of a zero-to-exit technology spin-out commercialising his academic research at the Department of Computer Science, University of Oxford where he completed a DPhil in Computer Science in 2011. Karo's current research interests center around linguistic substrata of explainable AI and efficient, precision-oriented NLP methods for demanding financial and legal NLP application areas.
Area Chair - ML Fundamentals
Yaodong is a research scientist at Huawei UK where he heads the multi-agent reinforcement learning research team. He is also Assistant Professor at King's College London. He has published more than 30 research papers including NIPS, ICML, ICLR, AAAI, IJCAI. Before joining Huawei, he was a senior science manger at AIG, working on machine learning applications on finance. He holds a PhD degree from UCL and MSc degree from Imperial College London, and was awarded UK Exceptional Talent in Machine learning by the Home Office in 2018.