Research interests: principled approximation methods, reliability of complex networks, critical infrastructure, deep learning

Jayant Patil's research focuses on developing principled approximation methods for reliability and resilience of infrastructure systems such as electric power networks. In his work, he uses machine learning, deep learning, dynamic programming, network science, and principled Monte Carlo simulations to assess the risk and reliability of power networks. 

Jayant graduated with a BTech and MTech in Civil Engineering from the Indian Institute of Technology, Bombay in 2014. He designed buildings as a Graduate Engineer at Walter P Moore (India) and developed open-source steel design software as a Project Research Associate at IIT Bombay before joining Rice University.

When he is not doing research, he enjoys cooking, playing Ultimate Frisbee or board games, and biking.