collaborators

5 papers

eess.SP2026

Information-Theoretic Causal Modelling of Semiconductor Process Dynamics

Daniel Sørensen, Giorgio Melchiorre, Sudip Bandyopadhyay +3

With the progress of the semiconductor industry toward increasingly complex compute devices and tighter process tolerances, advanced process control has become crucial. This work e…

cs.CV2026

High-Fidelity Synthetic Transmission Electron Microscopy Image Generation Using Diffusion Probabilistic Models for Data-Limited Semiconductor Metrology

Johannes Boehm, Bappaditya Dey

Advanced semiconductor nodes drastically increased demand for Transmission Electron Microscopy (TEM), yet destructive sample preparation, slow imaging and high costs severely limit…

cs.LG2025

Unsupervised Anomaly Prediction with N-BEATS and Graph Neural Network in Multi-variate Semiconductor Process Time Series

Daniel Sorensen, Bappaditya Dey, Minjin Hwang +1

Semiconductor manufacturing is an extremely complex and precision-driven process, characterized by thousands of interdependent parameters collected across diverse tools and process…

cs.LG2025

Continuous Wavelet Transform and Siamese Network-Based Anomaly Detection in Multi-variate Semiconductor Process Time Series

Bappaditya Dey, Daniel Sorensen, Minjin Hwang +1

Semiconductor manufacturing is an extremely complex process, characterized by thousands of interdependent parameters collected across diverse tools and process steps. Multi-variate…

eess.IV2025

Scanning Electron Microscopy-based Automatic Defect Inspection for Semiconductor Manufacturing: A Systematic Review

Enrique Dehaerne, Bappaditya Dey, Victor Blanco +1

In this review, automatic defect inspection algorithms that analyze Scanning Electron Microscopy (SEM) images for Semiconductor Manufacturing (SM) are identified, categorized, and…