Michael Cecil

Michael Cecil is a part-time instructor in the Department of Sustainability and Social Justice at Clark University. His academic focus revolves around climate resilience, agricultural sustainability, and the application of geospatial artificial intelligence in environmental monitoring. Cecil's work integrates machine learning techniques with satellite data to address challenges in smallholder agriculture, climate-smart farming practices, and policy-driven agricultural programs.

His research interests include leveraging remote sensing technologies for scalable agricultural monitoring, developing cloud gap imputation methods using foundation models, and assessing the efficacy of USDA programs in supporting climate-resilient agriculture. Cecil also explores the intersection of farmer decision-making, yield variability, and risk management in agricultural systems, particularly in data-sparse environments.

Notable contributions include advancing vision transformer and generative adversarial network (GAN) models for satellite image analysis, evaluating foundation models in geospatial tasks, and analyzing producer strategies within evolving climate baselines. His work emphasizes interdisciplinary collaboration to bridge gaps between environmental science, policy, and technological innovation.