Neil Gaikwad, a doctoral student at the Space Enabled research group, has been chosen for the 2019 INK Fellowship Program for Emerging Innovators. Every year, INK identifies 20 young achievers who are redefining their fields of work or the world around them. This year INK selected its 20 fellows from over 900 candidates around the world.
Neil's research focuses on the theory, design, and implementation of human-centered machine learning for sustainable development. He seeks to understand and reform broken urban systems and markets through the lens of human-centered machine learning, design, and evidence-informed policymaking. Towards this goal he is developing human-AI collaboration algorithms, experimental methods, and mechanisms to study, model, and (re-) design urban systems and markets under weak institutions, analyzing large-scale datasets emerging from social processes, Earth remote sensing satellites, and socio-economic interactions.
Neil's current research develops human-centered machine learning systems for decoding the impact of the Earth’s physical processes on agricultural markets and food security. Drawing upon this understanding, he is designing more efficient precision agriculture markets to enhance food security through helping marginalized farmers mitigate the impact of meteorological disasters and institutional breakdowns. This work investigates the complexity of cultures, colonial-histories, and economic contexts that impact the design, implementation, and performance of machine learning systems. He works with Professor Danielle Wood, the director of the Space Enabled research group.