Research

The United Nations estimates that by 2050 more than half of world's population will be residing in urban areas. Consequently, sustainable, and efficient operation of these urban areas has necessitated the emergence of ``SMART CITY". However, to meet the needs of the stakeholders of such smart cities, namely the urban citizens, human-centric urbanization must be a priority. The key features of such a ``humanist smart city" are (i) safety, security, and resilience, (ii) sustainability, (iii) efficiency, (iv) accessibility as well as quality of life, and lastly, (v) citizen autonomy. Motivated by these goals, my research objective is to unify systems and control theory with machine learning to tighten safety and security, improve system resilience and provide autonomy to citizens.

Resilient Transportation Systems 

Human-centric mobility is an integral part of a smart city. With increasing connectivity between smart infrastructures in a smart city, the human-centric transportation can be regarded as a Cyber-Physical-Social System (CPSS) or a Socio-Technical System (STS). It is, however, such connectivity and inter-dependencies make smart cities increasingly vulnerable to cyberattacks and physical faults. This has motivated my research in safety and security for smart mobility with an added focus on merging human-centric sensing and actuation with standard traffic measurements and management techniques. Thus, my research goal is to ensure resilient operation of transportation systems in smart cities against cyberattacks using human-centric strategies. There are several challenges in this area such as:  fusing social data with technical (or physical) data; availability, uncertainty and integrity of social data; preprocessing of social data; vehicle-level analysis vs traffic-level analysis; and impact of human behavior on traffic flow model.

Safeguarding Battery Energy Storage Systems

License: CC BY 3.0

My second research interest deals with challenges in ensuring safety to Battery Energy Storage Systems (BESS). These systems can facilitate greater adoption of sustainable energy technologies through penetration of reliable electric vehicles into the market or large-scale grid integration of renewables. Thus, designing intelligent management for these devices using both physics-based and data-driven approaches can potentially lead to a safer and more reliable BESS. My research goal is to improve safe and efficient operation of energy storage systems.

Anomaly Characterization

The anomalies in dynamical systems can be categorized into the following three types. (i) Faults are defined as system malfunction or defects that lead to system failures (e.g., CAV controller failure). (ii) Cyberattacks are intelligently crafted and inflicted actions by an adversary such that it can passively and actively drive the system to operate undesirably (e.g., hijacking CAVs). (iii) Outliers or rare events are anomalous data or events presented to the dynamical system (e.g., camera jitters). It is extremely critical to detect as well as characterize and classify these anomalies, since they can disrupt normal operations of dynamical systems such as transportation or energy systems. Thus, my research goal is to characterize and classify anomalies in dynamical system in order to dispense appropriate mitigation strategies.