My research focus is in improving resilience of smart electricity networks. The power grids are undergoing rapid transformation due to large-scale integration of new physical components such as distributed energy resources (DERs) and electric vehicles (EVs) as well as new cyber functionalities such as load control, advanced metering infrastructure, etc. which make the grids "smart". Although these smart features generally improve the health of the grids due to better monitoring and control capabilities, they also increase the susceptibility of electricity networks to both reliability failures such as faults and security failures such as cyber-physical attacks. Recent cyber-physical security (CPS) events around the world highlight the need to seriously tackle the issue of resilience of power systems. The Ukraine attack in December 2015 was the first ever successful cyber attack on the power grids. More recently, Hurricane Maria, in Puerto Rico, destroyed the power networks to such an extent that complete power restoration is estimated to take 6 months! Such events are an obvious motivation for my research. 

My current research effort has been to understand and model cyberphysical failure scenarios in power systems as attacker-defender games, where the defender is the power system operator whose goal is to maintain safe, reliable, economical and uninterrupted service to customers, while the attacker is an adversary or nature trying to disrupt the cyber/physical components. The attacker's objective is to maximize the defender's loss or cause maximum damage to the network. I formulate these games as multi-level optimization problems to determine optimal attacker and defender strategies. Me and my collaborators have demonstrated how with even limited access and modification to real-world energy management processes one such attack could be realistically implemented. We also developed and analyzed effective decentralized defender strategies with lesser communication requirements. 

I am particularly interested in the optimal deployment and utilization of the DERs to improve the operator's ability to anticipate, plan for, and optimally respond to CPS events. I am interested in developing algorithms to shortlist critical CPS attack scenarios, implementing machine learning algorithms to smartly detect such failures, use the knowledge of computed optimal defender strategies to quickly dispatch the DERs in a decentralized manner. My dream is to design and implement effective management strategies for natural or man-made disasters in power systems on a national level.

During the summer of 2018, I interned at Los Alamos National Lab (New Mexico) in T-5 group. I worked on Online Learning of Power Transmission Dynamics under partial observability. 

I am in the latter stages of my PhD program and plan to defend my thesis in April of 2019.