3 papers
eess.SY2026
VIBES -- A Two-Stage Scalable Bayesian Uncertainty Quantification Framework: Application to a Biomass Valorization Process
Poulomi Das, Angan Mukherjee, Debangsu Bhattacharyya
This paper proposes Variational Inference-based Bayesian Estimation with Sobol screening (VIBES), a two-stage scalable framework for Bayesian uncertainty quantification (UQ). The p…
eess.SY2026
Topological Data Analysis for High-Dimensional Dynamic Process Monitoring
Angan Mukherjee, Tyler A. Soderstrom, Michael J. Kurtz +1
Real-time process monitoring requires methods that extract actionable information from high-dimensional time-series data. In this work, we present a new approach for process monito…
cs.LG2025
Physics-Constrained Machine Learning for Chemical Engineering
Angan Mukherjee, Victor M. Zavala
Physics-constrained machine learning (PCML) combines physical models with data-driven approaches to improve reliability, generalizability, and interpretability. Although PCML has s…