734-882-9084

Applications:
Behavioral Science, Business Analytics, Cyber Security, Economics, Finance Research, Human Subjects Trials and Intervention Studies, Management Science, Mobile Devices, Networks, Policy Research, Sensors and Sensor Networks, Social Sciences, Survey Research
Methodologies:
Data Collection Design, Data Management, Data Quality, Data Security and Privacy, Decision Science, Econometrics, Machine Learning, Missing Data and Imputation, Predictive Modeling, Sparse Data Analysis, Statistical Inference, Statistics, Time Series Analysis
Relevant Projects:

NSF, ARO


Ranjan Pal

Assistant Research Scientist

Electrical and Computer Engineering

Cyber-security is a complex and multi-dimensional research field. My research style comprises an inter-disciplinary (primarily rooted in economics, econometrics, data science (AI/ML/Bayesian and Frequentist Statistics), game theory, and network science) investigation of major socially pressing issues impacting the quality of cyber-risk management in modern networked and distributed engineering systems such as IoT-driven critical infrastructures, cloud-based service networks, and app-based systems (e.g., mobile commerce, smart homes) to name a few. I take delight in proposing data-driven, rigorous, and interdisciplinary solutions to both, existing fundamental challenges that pose a practical bottleneck to (cost) effective cyber-risk management, and futuristic cyber-security and privacy issues that might plague modern (networked) engineering systems. I strongly strive for originality, practical significance, and mathematical rigor in my solutions. One of my primary end goals is to conceptually get arms around complex, multi-dimensional information security and privacy problems in a way that helps, informs, and empowers practitioners and policy makers to take the right steps in making the cyber-space more secure.