Neil Gaikwad

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Web Neil S. Gaikwad 
Twitter  neilsgaikwad 
Arts: Explore the Planet Earth 

RESEARCH

Neil Gaikwad is a doctoral student, specializing in human-centered machine learning and socioeconomic development.  Neil develops computational and design methods to build fair and interpretable machine learning for addressing breakdowns in sociotechnical systems, such as urban systems and markets under weak institutions, whose performance and adoption depend on the complexity of cultures, colonial-histories, and economic contexts in which they function. His research advances the field of societal and urban computing through the lens of machine learning, human-centered design, and evidence-informed policymaking for sustainable development.  He holds a master’s degree from the School of Computer Science at Carnegie Mellon University.

Neil’s research is informed by experiences in academia, quantitative finance on Wall Street, and farming communities in the Western Ghats of India (Sahyadri). His current research invents human-centered machine learning for deco… View full description

Web Neil S. Gaikwad 
Twitter  neilsgaikwad 
Arts: Explore the Planet Earth 

RESEARCH

Neil Gaikwad is a doctoral student, specializing in human-centered machine learning and socioeconomic development.  Neil develops computational and design methods to build fair and interpretable machine learning for addressing breakdowns in sociotechnical systems, such as urban systems and markets under weak institutions, whose performance and adoption depend on the complexity of cultures, colonial-histories, and economic contexts in which they function. His research advances the field of societal and urban computing through the lens of machine learning, human-centered design, and evidence-informed policymaking for sustainable development.  He holds a master’s degree from the School of Computer Science at Carnegie Mellon University.

Neil’s research is informed by experiences in academia, quantitative finance on Wall Street, and farming communities in the Western Ghats of India (Sahyadri). His current research invents human-centered machine learning for decoding the impact of the socioeconomic and Earth’s physical processes on marginalized farmers. Drawing upon this understanding, he is designing more efficient precision agriculture markets to help marginalized farmers mitigate the impact of meteorological disasters and institutional breakdowns. This research is part of the MIT Quest for Intelligence, an institute-wide initiative that aims to unlock the nature of intelligence and harness it to make a better world.

Neil's research has been published in premier artificial intelligence and human-computer interaction conferences (AAAI, ACM UIST, ACM CSCW, ACM CHI) and a scientific journal (PNAS), and featured in the New York Times, Bloomberg, WIRED, and the Wall Street Journal. His honors include the Facebook Fellowship Award, an MIT Arts Scholar, an IJCAI Distinguished Program Committee Member, the ACM UIST Honorable Mention, the MIT Graduate Teaching Award, presented annually to one MIT professor or teaching assistant from each school, for excellence in teaching a graduate level course, and the Karl Taylor Compton Prize, the highest student award presented by MIT in recognition of excellent achievements in citizenship and devotion to the welfare of MIT.

ARTS

Neil is a practicing photographer and an MIT arts scholar. His artwork inspires his scientific endeavors. His exhibition Beyond the Boundaries captures the complexities of our planet, including 3,000 years old glacier landscapes, the Western Ghats (Sahyadri) of India, cultures, and pressing societal challenges such as climate change. Neil's photography work has been published in National Geographic. For more information, please visit `Explore the Planet Earth’ on Facebook and Instagram.