Computational biology, smart agriculture, machine learning, complex systems
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Research focuses on modeling and control of complex biological and engineered systems: mechanistic simulations of population and disease dynamics, and IoT-based sensing/actuation for indoor agriculture. Combines machine learning with systems modeling to enable energy-efficient, data-driven decision support.
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