Dr Muhammad Salman Haleem

Profile

Dr. Muhammad Salman Haleem is currently Lecturer (Assistant Professor) in School of Electronic Engineering and Computer Science. He is involved in teaching Joint Programme in collaboration with Beijing University of Posts and Telecommunications. Previously, he served as Assistant Professor-Research Focused in Applied Biomedical Signal Processing and Intelligent eHealth Lab, School of Engineering at University of Warwick since August 2020. Dr. Haleem finished his PhD PhD in Computing from Manchester Metropolitan University where he received the prestigious scholarship on EPSRC-DHPA. The title of his research was ‘Automatic Extraction of Retinal Features to Assist Glaucoma Disease Diagnosis’. After completion of his PhD in 2015, he served as a Research Associate – Data Science in the same university till 2020 where he designed and developed novel computer aided methods to advance operational analytics and policing methods for improved well-being. 

Dr. Haleem research interests lie in artificial intelligence, data science and deep learning solutions with special focus on medical and healthcare data analytics. His research works focus on design and development of novel Artificial Intelligence based solutions for improved chronic disease monitoring (such as Diabetes, cardiovascular diseases); physical activity and stress monitoring; retinal image and MRI analysis etc. He has authored/co-authored more than 40 peer-reviewed papers including systematic literature reviews, study protocols, scientific articles, book chapters in top academic journals and conference proceedings. He has also been regular reviewer of top scientific journals such as Biomedical Signal Processing and Control, Computerized Medical Imaging and Graphics, IEEE transactions in Biomedical Engineering, IEEE journal of Biomedical and Health Informatics, etc. 

Teaching

Advanced Network Programming 

This module builds on the students' Java programming skills to equip them with a conceptual understanding of a selection of advanced topics in network programming including threads, sockets, RMI, JavaScript and server-side topics (servlets, JSPs and JavaBeans). HTML and the HTTP protocol are also covered. The course contains a coursework component requiring each student to understand how to develop a distributed application such as an e-commerce platform, implemented using the technologies introduced in the lectures. 

Introduction to AI 

This course builds on theoretical concepts of Artificial Intelligence to equip them fundamental design and development of modern Artificial Intelligence architectures. This course contains coursework involving mathematical foundations of Artificial Intelligence architectures 

Research

Research Interests:

• Fundamental AI design and development of mathematical foundations of AI to address personalized risk assessment models. It require time series data acquisition, processing and modelling from multiple sources such as modern assistive technologies, health questionnaires, electronic health records etc. Pivotal for modern chronic disease management 
• Text mining for extracting contextual insights from unstructured text logs. With the advent of modern technologies, we are acquiring Big Data from various multiple sources under clinical, health and policing domain and Big data analytics would be pivotal to extract information from unstructured text records. 
• Image processing and computer Vision including Adaptive ML models for extracting personalized anatomical structures and assistive robotics for effective healthcare and hospitalization management. 
• Trustworthy AI for more explainable, fair, robust, private, and transparent modelling 

Supervision

I am always looking for self-motivated students who want to pursue a PhD degree in Electronic Engineering and Computer science. If you are with a solid background in artificial intelligence/computer science and a strong grounding in mathematical and programming skills, please drop me an email with your CV and draft research proposals. Also find the PhD funding opportunities at http://www.eecs.qmul.ac.uk/phd/phd-opportunities/ 

Scholarly Contributions

Honours, awards, and keynote lectures:

• Keynote lecture on “Generative AI in Medical and Healthcare Applications, Sustainable Global Health & Wellbeing Bootcamp 2023, Jesus College of University of Cambridge, UK, 2023.
• Won the first prize in IFMBE Scientific Challenge 2023 for research paper "Spectrogram-based approach with Convolutional Neural Network for human activity classification” at 16th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)
• Won the second prize in IFMBE Scientific Challenge 2023 for research paper " Spectrogram-driven Convolutional Neural Network for Real-Time Non-invasive Hyperglycaemia Detection in Paediatric Type-1 Diabetes via Wearable Sensors” at 16th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)
• Finalist à UK ICT Pioneer 2015 competition for most exceptional thesis, 2015 à https://www.youtube.com/watch?v=vJYka5KYN9w
• Paper entitled "Retinal Area Detector from Scanning Laser Ophthalmoscope (SLO) Images for Diagnosing Retinal Diseases" selected as a featured article in IEEE Journal of Biomedical and Health Informatics, 2014
• Recipient of Dorothy Hodgkin Postgraduate Award (DHPA) by Engineering and Physical Sciences Research Council (EPSRC), UK for pursuing PhD-£90,000, 2012