Area of research
Artificial Intelligence · Computer Vision and Pattern Recognition
Research interest
Research interests include Computer science, Anomaly detection, Artificial intelligence, Series (stratigraphy), Geology, and Paleontology.
Interpretable Anomaly Detection with DIFFI: Depth-based feature importance of Isolation Forest
A Random Forest-based Approach for Hand Gesture Recognition with Wireless Wearable Motion Capture Sensors
Data-Driven Anomaly Recognition for Unsupervised Model-Free Fault Detection in Artificial Pancreas
A Computer Vision-Inspired Deep Learning Architecture for Virtual Metrology Modeling With 2-Dimensional Data
Time-Series Classification Methods: Review and Applications to Power Systems Data
Anomaly Detection Approaches for Semiconductor Manufacturing