My research is along the following themes.

Our focus is on rigorously understanding the dynamics of spreading processes (such as infectious diseases, opinions, etc.) on networks. We borrow tools from network science, dynamical systems, optimization, game theory and signal processing for modeling, estimation and control of such processes.

We are interested in investigating the following problems.

- How to infer the prevalence of infectious diseases from testing data and use it as feedback for deploying optimal non-pharmaceutical interventions (such as lockdown, contact tracing, isolation, etc)?
- How does individual protective behavior evolve and influence the spread of epidemics?
- How do behavioral biases influence individuals while taking protective measures (such as self-quarantine, vaccination, etc)?

**Representative Publications:**

- Impacts of Game-Theoretic Activation on Epidemic Spread over Dynamical Networks, SIAM Journal on Control and Optimization, 2022. (Joint work with: Tanya Sneh and Kavish Gupta)
- A Closed-Loop Framework for Inference, Prediction and Control of SIR Epidemics on Networks, IEEE Transactions on Network Science and Engineering, 2021. (Joint work with: Philip Paré and Jaydeep Godbole)
- Game-Theoretic Vaccination Against Networked SIS Epidemics and Impacts of Human Decision-Makers," IEEE Transactions on Control of Network Systems, 2019. (Joint work with Shreyas Sundaram)

**External Collaborators:** Philip Paré and Shreyas Sundaram (Purdue University), Saverio Bolognani (ETH Zurich), Vaibhav Srivastava (Michigan State University).

**Funding:** Joint DST-NSF Indo-US Research Grant by IDEAS, ISI Kolkata jointly with Prof. Philip Paré from Purdue University, USA.

Optimization problems with uncertainty are at the heart of many engineering disciplines. In particular, stochastic optimal control, model predictive control and estimation heavily rely on solving optimization problems with uncertain objectives and constraints.

We are currently investigating new techniques (and their applications) that do not impose any assumptions on the knowledge or nature of the probability distribution of the uncertainty, but rather relies directly on the available data to compute (approximate) optimal solutions of such problems.

**Representative Publications:**

- Wasserstein Distributionally Robust Look-Ahead Economic Dispatch, IEEE Transactions on Power Systems, 2021. (Joint work with: Bala Kameswar Poolla, Saverio Bolognani, Duncan Callaway and Ashish Cherukuri)
- Consistency of Distributionally Robust Risk- and Chance-Constrained Optimization under Wasserstein Ambiguity Sets, IEEE Control Systems Letters, 2021. (Joint work with: Ashish Cherukuri)
- Data-Driven Chance Constrained Optimization under Wasserstein Ambiguity Sets, Proceedings of the American Control Conference (ACC), Philiadelphia, PA, USA, 2019. (Joint work with: Ashish Cherukuri and John Lygeros)

**Funding:** ISIRD Grant, IIT Kharagpur

**External Collaborators:** Ashish Cherukuri (University of Groningen), Bala Kameswar Poolla (NREL), Saverio Bolognani and John Lygeros (ETH Zurich).

Modern engineered systems are highly interconnected and interdependent. Different types of faults, and targeted attacks exploit the underlying network of interconnections to spread throughout the system. In this context, our research is focused on the following problems.

- What is the impact of decentralized decision making on the security of large-scale networks?
- How do behavioral biases influence the security investment decisions of human users, and what is the network-wide impact of such decisions?
- Are certain classes of networks inherently resilient, and if so, what is the underlying structure of such networks?

**Representative Publications:**

- Equilibrium Strategies for Multiple Interdictors on a Common Network, European Journal of Operational Research, 2021. (Joint work with: Harikrishnan Sreekumaran, Andrew L. Liu, Nelson A. Uhan and Shreyas Sundaram)
- Behavioral and Game-Theoretic Security Investments in Interdependent Systems Modeled by Attack Graphs, IEEE Transactions on Control of Network Systems, 2020. (Joint work with: Mustafa Abdallah, Parinaz Naghizadeh, Timothy Cason, Saurabh Bagchi and Shreyas Sundaram)
- Interdependent Security Games on Networks under Behavioral Probability Weighting, IEEE Transactions on Control of Network Systems, 2018. (Joint work with: Shreyas Sundaram)

**In Press: **Purdue News.

Technology has enabled increasing human interaction with engineered systems in recent years. In particular, humans actively interact with shared infrastructure, and make decisions that influence their operation. For instances, smart phones and Internet-of-Things have led to proactive participation of end-users in transportation and energy systems. Thus understanding and influencing their behavior is essential for controlling the operation of such systems. We investigate the following questions in this context.

- How to quantify the impacts of decentralized and human decision-making on shared systems?
- How to design dynamic incentives to truthfully elicit the preferences and privately-held information from end-users?
- Do psychological biases cause humans to respond to economic incentives in counter-intuitive ways, and if so, how to mitigate them?

**Representative Publications:**

- Controlling Human Utilization of Failure-Prone Shared Resources via Taxes, IEEE Transactions on Automatic Control (To appear). (Joint work with: Shreyas Sundaram)
- Fragility of the Commons under Prospect-Theoretic Risk Attitudes, Games and Economic Behavior, 2016. (Joint work with: Siddharth Garg and Shreyas Sundaram)
- Dynamic Mechanism Design for Human-in-the-Loop Control of Building Energy Consumption, Proceedings of the American Control Conference (ACC), Philiadelphia, PA, USA, 2019. (Joint work with: Maximilian Schuette, Annika Eichler and John Lygeros)

**In Press:** Purdue News.