Khalil ul Rehman

Conducting advanced AI/ML research focused on novel model architectures, learning paradigms, and AI for Engineering and Control Theory. Designing experiments to investigate deep learning techniques on large-scale real-world datasets, including Hybrid Systems modeling and intelligent control scenarios.

Architected and deployed end-to-end machine learning pipelines for production, covering data ingestion, feature engineering, model training, evaluation, and serving. Developed and fine-tuned NLP models for text classification, named entity recognition, sentiment analysis, and information extraction using Transformers and BERT-based architectures.

Designed and deployed machine learning models for data classification, regression, and anomaly detection using Python-based ML frameworks. Developed NLP solutions for text processing, feature extraction, and predictive analytics across structured and unstructured datasets.

Taught undergraduate courses in Artificial Intelligence, Machine Learning, and Programming (Python, C/C++). Supervised final year projects in AI and data science, mentoring students through research design, implementation, and presentation.

Developed full-stack web applications using Python (Django, Flask) and JavaScript frameworks, including ReactJS, ReduxJS, and AngularJS within MEAN/MERN stack environments. Built cross-platform mobile applications and contributed to Unity-based game development using C#.

Delivered lectures on Python programming, covering fundamentals, data structures, and applied programming for undergraduate students.

Pursuing a Doctor of Philosophy in Artificial Intelligence, with research focused on AI/ML, including novel model architectures and AI for engineering and control theory.

Completed a Master of Science in Computer Science, with coursework and research in advanced computing topics.