most citedPhysics-Constrained Machine Learning for Chemical Engineering

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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…