Dr. Nsoesie is an Assistant Professor of Global Health at Boston University School of Public Health. She has a PhD in Computational Epidemiology from the Genetics, Bioinformatics and Computational Biology program at Virginia Tech. She also has an MS in Statistics and a BS in Mathematics. Her research is focused on the use of digital data and technology to improve health in communities globally. Her work has also focused on addressing bias in digital data and understanding factors influencing disparities in health outcomes. Her research findings have been reported in major news outlets and science magazines, including Science, Smithsonian Magazine, Scientific American, Washington Post, NPR, and the BBC. She is on the advisory board of Data Science Africa and Data Science Nigeria. She is also the founder of Rethé - an initiative focused on providing scientific writing tools and resources to student communities in Africa in order to increase representation in scientific publications. She has written for NPR, The Conversation, Public Health Post, and Think Global Health. Dr. Nsoesie was born and raised in Cameroon.

Anubha Sinha is a Senior Programme Manager at CIS. She has researched algorithmic transparency, with a view to contribute to the development of an overarching regulatory framework for AI tech, and is currently engaged in research on Digital Identity systems. She is an experienced Public Policy professional and skilled in Intellectual Property, Data Protection, Privacy, Artificial Intelligence and Research. She professionally provides legal services and graduated from Dr. RML National Law University.

Santiago Saavedra is Assistant Professor at the Economics Department in Universidad del Rosario. He holds a PhD in Economics from Stanford University. Last year he was awarded a Google Artificial Intelligence Impact Challenge grant.

His research interests are in Development and Environmental Economics. In particular, he is interested in how economic development affects natural resources, and how this in turn affects the path out of poverty. To overcome data availability limitations, he uses spatial and computational tools. He has studied the response of illegal mining to a change in royalty taxes and health effects of gold mining in Colombia. Deforestation after the peace agreement and of communal land titling. He has also studied the migration of miner networks and the labor supply of bike taxis in Kenya.

Dr. Nakalembe is an Assistant Research Professor at the University of Maryland. She is the NASA Harvest Africa Program Director, a member of the NASA SERVIR Applied Sciences Team and serves as the Agriculture and Food Security Thematic Lead. She is a 2020 Africa Food Prize Laureate for her dedication to improving the lives of smallholder farmers by using satellite technology to harness data to guide agricultural decision-making. Her work in this area has helped prevent potentially disastrous impacts of crop failure. Her relentless efforts have also promoted the formulation of policies and programs that are directly impacting farmers against the impacts of food failure. Dr. Nakalembe was a 2020 UMD Research Excellence Honoree and 2019 was a recipient of the Inaugural GEO Individual Excellence Award. She was featured in the 2020 Women and GIS, Volume 2: Stars of Spatial Science ESRI Press book.

Dr. Nakalembe grew up in Kampala, Uganda where she earned a BSc. at Makerere University in Environmental Science. She earned an MSc. in Geography and Environmental Engineering from Johns Hopkins University and her Ph.D. in Geographical Science at the University of Maryland.

Xiaoxiang Zhu is the Professor for Signal Processing in Earth Observation at the Technical University of Munich, heads the Department "Earth Observation Data Science" at the German Aerospace Center and since May, she is also the Director of the Munich Future AI Lab "AI4EO".

The research of Professor Zhu focuses on signal processing and data science in earth observation. Geo-information derived from Earth observation satellite data is indispensable for many scientific, governmental and planning tasks. Furthermore, Earth observation has arrived in the Big Data era with ESA's Sentinel satellites and NewSpace companies. Professor Zhu develops innovative machine learning methods and big data analytics solutions to extract highly accurate large scale geo-information from big EO data. These show, for example, not only three-dimensional structures of buildings, settlement types, population density, but also their evolutions over time. Her team aims at tackling societal grand challenges, e.g. UN’s SDGs, thus, works on solutions that can scale up for global applications, with a particular focus on the developing world.