Dr Tempest Van Schaik
Tempest is passionate about improving lives using sensors, data, and AI. Some of the ways she's driven impact have been through her startup, SoilCards, which aims to make mobile soil testing accessible to the world’s poorest farmers in order to improve their livelihood and protect the environment. She has also developed novel ways to measure cognitive function and mood in people with depression using wearables (CognitionKit). She has used data science to improve physiotherapy for children with cystic fibrosis (Project Fizzyo), and has put principles of responsible AI into practice to build predictive ICU models which treat different patient groups fairly.
She is currently a Senior Machine Learning Engineer in Microsoft’s Commercial Software Engineering (CSE) team, where she is a ML Lead for collaborations with some of Microsoft’s biggest healthcare customers (NHS, Philips etc). She is a member of CSE’s Responsible AI board and a CSE ambassador for Diversity & Inclusion, because she believes in promoting positive change as a leader in the industry.
She has a PhD in Bioengineering from Imperial College London, with an internship at MIT, and an Imperial College Rector's Award. She is a Technical Advisory Board member of Ultromics Ltd as well as a TEDx and SXSW speaker. Her research has received awards from Innovate UK, the Royal Society, and the US National Academies of Science Engineering and Medicine.
Dr Malet?abisa Molapo
Dr Malet?abisa (T?abi) Molapo is a Research Manager at IBM Research (Johannesburg). She leads teams working in AI Science, Quantum Computing, and Natural Language Processing. Her research has ranged from Speech & Voice technologies to Human-Computer Interaction and Natural Language Processing, to the application of AI in education and healthcare. She holds Ph.D. and M.Sc degrees in Computer Science from the University of Cape Town and a B.Eng in Computer Systems and Networks from the National University of Lesotho. Before joining IBM, she worked in user research, experience design, and product strategy at Praekelt.org, after spending several years as a Computer Science lecturer and researcher at NUL. She has over 10 years of experience leading technology projects in emerging and low-resource markets - designing, developing, deploying, and evaluating data-driven technology solutions for varying rural and urban contexts in Africa.
Dr Michèle Ramsay
Michèle Ramsay (PhD) is director of the Wits Sydney Brenner Institute for Molecular Bioscience (SBIMB), Professor in Human Genetics and South African Research Chair in Genomics and Bioinformatics of African Populations. Her current research aims to shed light on the role of African population genomic variation in susceptibility to complex diseases including hypertension, obesity, diabetes and stroke, in the context of the ethnic and environmental diversity across the continent. She has expertise in genetic and genomic research for monogenic and complex traits, as well as biobanking and data governance pertaining to research in Africa.
Michèle is the Principal Investigator (PI) of an African longitudinal cohort of about 12,000 individuals as part of the H3Africa Consortium, is on the Scientific Advisory Committee of the H3Africa Bioinformatics Network (H3ABioNet), External Advisory Board of EU-Africa PerMed Consortium, and member of the International Hundred-thousand+ Cohorts Consortium (IHCC). She is President of the International Federation of Human Genetics Societies. Her recent awards include: DSI Distinguished Woman Researcher (August 2019); NSTF-South32 Lifetime Achievement Award (July 2020); and Gold Medal from the South African Medical Research Council (March 2021).
Jessica Breakey
Jessica Breakey is a sociologist working as an associate lecturer in the School of Electrical and Information Engineering at University of the Witwatersrand, where she co-ordinates a multidisciplinary course called Engineers in Society, teaching final-year electrical and information engineers. The course is aimed at connecting social and critical theory to the rapid emergence of new technologies, and challenges students to use a sociological lens to examine the roles of race, gender, power and prejudice in datasets, algorithms, and Artificial Intelligence.