Mona Alinejad

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 and upskilling AI scientists by organising educational events such as Oxford ML Summer schools.

She has a DPhil in Biomedical Engineering from the University of Oxford, and has years of experience in the medical devices industry, and deep tech venture capital.

Reza Khorshidi
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 Rahimi
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.
Thomas Nichols

Dr. Nichols 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, having earned his his PhD in Statistics at Carnegie Mellon University with cross-training in Cognitive Neuroscience.  After joining the faculty at the Department Biostatistics at the University of Michigan, 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. In 2009 he received the Wiley Young Investigator Award by the Organization for Human Brain Mapping in recognition for his contributions to statistical modelling & inference of neuroimaging data.  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.

Moez Draief

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.

Yaodong Yang

Yaodong is a research scientist at Huawei UK where he heads the multi-agent reinforcement learning research team. 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. 



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