Associate Professor · School of Computer Science and Engineering
Bilal Khan, Ph.D
Machine learning for water treatment, behavioral analysis, and nanomaterial safety.
Focus areas
Intelligent Water Treatment
Machine-learning and deep-learning methods for membrane fouling prediction, real-time scaling detection on reverse-osmosis membranes, and data-driven control of seawater RO feedwater treatment. Work also includes cyber-infrastructure for regional water districts and predictive models for water-consumption forecasting.
Computer Vision for Human Behavior
Computer-vision and pattern-recognition systems for human behavioral analysis — spanning deception detection, facial emotion recognition, and assistive perception for visually impaired users. Includes lightweight transfer-learning models designed for deployment on constrained hardware.
Nanotoxicology & Nanomaterial Safety
Predictive frameworks and curated databases for the environmental and toxicological impact of engineered nanomaterials. Includes Bayesian networks for quantum-dot cellular toxicity, QSAR models for nanoparticle uptake, and simulation tools for environmental release and multimedia distribution.
Embedded Systems & Applied Data Science
Embedded systems for real-time resource management, hardware-accelerated clustering for image pipelines, and applied ML across domains including aviation safety, Arabic-language NLP, and agricultural sensing.
Selected publications
- Kernel-based machine learning intrusion detection systems for ICMPv6 DDoS detection
- Techno-economic assessment of distributed wellhead RO water treatment for nitrate removal and salinity reduction: A field study in small disadvantaged communities
- A comprehensive analysis of deception detection techniques leveraging machine learning
- From Prompts to Performance: Leveraging LLMs for Enhanced Educational AI Interactions