Paromita Banerjee

Paromita Banerjee is a Visiting Assistant Professor in the Department of Mathematics and Computer Science at John Carroll University. She holds a Ph.D. in Applied Mathematics from Case Western Reserve University, an MS in Statistics from the University of Houston-Clear Lake, and prior degrees from the University of Kalyani and the University of Calcutta. Her research focuses on numerical methods for stochastic differential equations (SDEs), causal inference frameworks, and machine learning applications in epidemiology, finance, and social sciences. She previously worked as a business analyst at Tata Consultancy Services in Bangalore, India.

• Education:
  • B.S. in Statistics, University of Calcutta
  • M.S. in Statistics, University of Kalyani, India
  • M.S. in Statistics, University of Houston-Clear Lake
  • Ph.D. in Applied Mathematics, Case Western Reserve University

Her current teaching interests span data science, statistics, machine learning, database systems, probability, regression analysis, time series analysis, and statistical computing. She also teaches foundational courses like linear algebra and calculus.

Her research explores structural equation models based on post-intervention SDEs and robust clustering/classification methods in machine learning. Her recent work includes Bayesian inference models for pandemic dynamics and numerical methodologies for multivariate SDEs using the Milstein scheme.

Awards:

• SCE Dean's Scholarship (University of Houston-Clear Lake)
• Graduate Fellowship & Teaching Assistantship (Case Western Reserve University)

Her advising and grants section remains unspecified in the provided text, but her academic trajectory reflects sustained engagement with interdisciplinary research at the intersection of mathematics and applied sciences.