Area of research
Artificial Intelligence · Industrial and Manufacturing Engineering
Research interest
Research interests include Computer science, Artificial intelligence, Machine learning, Interpretability, Anomaly detection, and Predictive maintenance.
AcME—Accelerated model-agnostic explanations: Fast whitening of the machine-learning black box
FORMULA: A Deep Learning Approach for Rare Alarms Predictions in Industrial Equipment
Explainable Machine Learning in Industry 4.0: Evaluating Feature Importance in Anomaly Detection to Enable Root Cause Analysis
A deep learning approach for anomaly detection with industrial time series data: a refrigerators manufacturing case study
Deep Learning-based Production Forecasting in Manufacturing: a Packaging Equipment Case Study
A Convolutional Autoencoder Approach for Feature Extraction in Virtual Metrology
A Computer Vision-Inspired Deep Learning Architecture for Virtual Metrology Modeling With 2-Dimensional Data
On the Error Region for Channel Estimation-Based Physical Layer Authentication Over Rayleigh Fading
Time and Spectral Domain Relative Entropy: A New Approach to Multivariate Spectral Estimation