Publications (16)
Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks
Nishant Yadav, Samrat Chatterjee, Auroop R. Ganguly
Natural hazards including floods can trigger catastrophic failures in interdependent urban transport network-of-networks (NoNs). Population growth has enhanced transportation deman…
Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains
Buddhika Nettasinghe, Samrat Chatterjee, Ramakrishna Tipireddy +1
Conformal prediction is a widely used method to quantify the uncertainty of a classifier under the assumption of exchangeability (e.g., IID data). We generalize conformal predictio…
Identifying early-warning indicators of tipping points in networked systems against sequential attacks
Utkarsh Gangwal, Udit Bhatia, Mayank Singh +3
Network structures in a wide array of systems such as social networks, transportation, power and water distribution infrastructures, and biological and ecological systems can exhib…
Hypergames and Cyber-Physical Security for Control Systems
Craig Bakker, Arnab Bhattacharya, Samrat Chatterjee +1
The identification of the Stuxnet worm in 2010 provided a highly publicized example of a cyber attack used to damage an industrial control system physically. This raised public awa…
AdverSAR: Adversarial Search and Rescue via Multi-Agent Reinforcement Learning
Aowabin Rahman, Arnab Bhattacharya, Thiagarajan Ramachandran +4
Search and Rescue (SAR) missions in remote environments often employ autonomous multi-robot systems that learn, plan, and execute a combination of local single-robot control action…
HistoSPACE: Histology-Inspired Spatial Transcriptome Prediction And Characterization Engine
Shivam Kumar, Samrat Chatterjee
Spatial transcriptomics (ST) enables the visualization of gene expression within the context of tissue morphology. This emerging discipline has the potential to serve as a foundati…
Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties
Ashutosh Dutta, Samrat Chatterjee, Arnab Bhattacharya +1
Development of autonomous cyber system defense strategies and action recommendations in the real-world is challenging, and includes characterizing system state uncertainties and at…
Constraints Satisfiability Driven Reinforcement Learning for Autonomous Cyber Defense
Ashutosh Dutta, Ehab Al-Shaer, Samrat Chatterjee
With the increasing system complexity and attack sophistication, the necessity of autonomous cyber defense becomes vivid for cyber and cyber-physical systems (CPSs). Many existing…
Learning Koopman Representations for Hybrid Systems
Craig Bakker, Arnab Bhattacharya, Samrat Chatterjee +2
The Koopman operator lifts nonlinear dynamical systems into a functional space of observables, where the dynamics are linear. In this paper, we provide three different Koopman repr…
Ad Hoc Teamwork in the Presence of Adversaries
Ted Fujimoto, Samrat Chatterjee, Auroop Ganguly
Advances in ad hoc teamwork have the potential to create agents that collaborate robustly in real-world applications. Agents deployed in the real world, however, are vulnerable to…
Large Language Model-Based Reward Design for Deep Reinforcement Learning-Driven Autonomous Cyber Defense
Sayak Mukherjee, Samrat Chatterjee, Emilie Purvine +2
Designing rewards for autonomous cyber attack and defense learning agents in a complex, dynamic environment is a challenging task for subject matter experts. We propose a large lan…
A Tri-Level Optimization Model for Interdependent Infrastructure Network Resilience Against Compound Hazard Events
Matthew R. Oster, Ilya Amburg, Samrat Chatterjee +4
Resilient operation of interdependent infrastructures against compound hazard events is essential for maintaining societal well-being. To address consequence assessment challenges…
Assessing the Impact of Distribution Shift on Reinforcement Learning Performance
Ted Fujimoto, Joshua Suetterlein, Samrat Chatterjee +1
Research in machine learning is making progress in fixing its own reproducibility crisis. Reinforcement learning (RL), in particular, faces its own set of unique challenges. Compar…
Parallel Algorithms for Median Consensus Clustering in Complex Networks
Md Taufique Hussain, Mahantesh Halappanavar, Samrat Chatterjee +3
We develop an algorithm that finds the consensus of many different clustering solutions of a graph. We formulate the problem as a median set partitioning problem and propose a gree…
Lorenz System State Stability Identification using Neural Networks
Megha Subramanian, Ramakrishna Tipireddy, Samrat Chatterjee
Nonlinear dynamical systems such as Lorenz63 equations are known to be chaotic in nature and sensitive to initial conditions. As a result, a small perturbation in the initial condi…
Unmasking unlearnable models: a classification challenge for biomedical images without visible cues
Shivam Kumar, Samrat Chatterjee
Predicting traits from images lacking visual cues is challenging, as algorithms are designed to capture visually correlated ground truth. This problem is critical in biomedical sci…