Area of research
Building and Construction · Artificial Intelligence
Research interest
Research interests include Computer science, Fuzzy logic, Data mining, HVAC, Anomaly detection, and Energy consumption.
Building Energy Management Systems: The Age of Intelligent and Adaptive Buildings
Multi-use high-technology testbed
Mining Building Energy Management System Data Using Fuzzy Anomaly Detection and Linguistic Descriptions
Vulnerability identification and classification via text mining bug databases
FN-DFE: Fuzzy-Neural Data Fusion Engine for Enhanced Resilient State-Awareness of Hybrid Energy Systems
EEG based brain activity monitoring using Artificial Neural Networks
Data driven fuzzy membership function generation for increased understandability
Next Generation Emergency Communication Systems via Software Defined Networks
Neural Network based downscaling of Building Energy Management System data
Optimal placement of Phasor Measurement Units in power grids using Memetic Algorithms
Driving behavior prompting framework for improving fuel efficiency
Fuzzy logic based force-feedback for obstacle collision avoidance of robot manipulators
Dynamic fuzzy force field based force-feedback for collision avoidance in robot manipulators
Human machine interaction via brain activity monitoring
Shadowed Type-2 Fuzzy Logic Systems
Fuzzy linguistic knowledge based behavior extraction for building energy management systems
Information gain based dimensionality selection for classifying text documents
Mining Bug Databases for Unidentified Software Vulnerabilities
Computational intelligence based anomaly detection for Building Energy Management Systems
Visual, linguistic data mining using Self- Organizing Maps