Akul Kumar is a high school student with a focused interest in applied mathematics, computational modelling, and their intersection with real-world systems, particularly in agriculture and climate resilience. He currently studies at Commonwealth School (Massachusetts), where his academic work spans mathematics, computer science, physics, and economics.

His work is grounded in using quantitative thinking to address complex, real-world challenges. As the founder of Farming Futures, Akul has developed a data-driven approach to understanding crop vulnerability in drought-prone regions of northern India. He designed a Crop Stress Index (CSI) model that integrates variables such as rainfall deviation, temperature variability, irrigation reliability, and crop sensitivity, alongside field survey data and external weather datasets. This work extends into resource optimisation, prioritising support for farmers based on measurable risk and constraints.

Beyond this initiative, Akul’s experience spans research, technology, and education. He has conducted machine learning research at MIT focused on medical imaging, and previously worked on climate modelling and environmental data systems in applied settings. He has also developed computational tools, including a protein modelling platform used by researchers, reflecting his broader interest in data-driven problem-solving across disciplines.

Alongside his technical work, Akul is actively engaged in education and outreach. As Head Math Tutor at Dribble Academy, he teaches mathematics and programming to students from underserved communities, and through his platform, Indian Math Guy, he shares accessible mathematical content with a wider audience.

References:

1. Lowder, S. K., S´anchez, M. V., and Bertini, R. (2021). Which farms feed the world and has farmland become more concentrated? World Development, 142:105455.
https://www.researchgate.net/publication/350524818_Which_farms_feed_the_world_and_has_farmland_become_more_concentrated

2. Kumar, D., & Doan, M. K. (2025). Adoption of agricultural technologies by smallholder farmers: A synthesis of empirical evidence. World Bank.
https://documents1.worldbank.org/curated/en/099092925141086193/pdf/P500443-c5c1ae72-ed75-442e-885c-7ced9e0bb0ea.pdf

3. Gollin, M., de Miranda, C., Muriuki, T., and Commins, S. (2023). Designing and delivering government-led graduation programs for people in extreme poverty. In Practice, 7.
https://www.peiglobal.org/sites/default/files/2025-10/IP7_ExtremePovertyBrief_FINAL.pdf

4. Ritchie, H. (2022). Increasing agricultural productivity across sub-Saharan Africa is one of the most important problems of this century. Our World in Data. https://ourworldindata.org/africa-yields-problem

5. Food and Agriculture Organisation of the United Nations (n.d.). Agricultural Technologies for Enhanced Climate Resilience and Smallholder Farmer Livelihoods. Fao.org. https://www.fao.org/neareast/main-topics/regional-priorities/priority-1-rural-transformation-and-inclusive-value-chains/agricultural-technologies-for-enhanced-climate-resilience-and-smallholder-farmer-livelihoods