Dr Muhammad Salman Haleem
Dr Muhammad Salman Haleem
Assistant Professor (Research Focussed)
Applied Biomedical Signal Processing and Intelligent eHealth Lab
School of Engineering
Salman dot Haleem at warwick dot ac dot uk
Dr. Muhammad Salman Haleem is currently Assistant Professor based in Applied Biomedical Signal Processing and Intelligent eHealth Lab, School of Engineering at University of Warwick since August 2020.
Previously, he finished his B.Engg. in Electronics from NED University of Engineering and Technology, Karachi, Pakistan in 2008. He served as a lecturer in the same university from 2008-2009. He then pursued for his M.S. in Electrical Engineering in Illinois Institute of Technology, Chicago, USA from 2009-2011. He was also involved in Masters research based on ‘A task based approach to parametric imaging with Dynamic Contrast-Enhanced MRI’. In 2012, he pursued for his 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 been involved in several collaborative research projects such as GATEKEEPER H2020, Holistic Well-being monitoring with British Telecom, Greater Manchester Police Operational Analytics for improved well-being 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.
- Fundamental AI design and development of mathematical foundations of AI to address personalized risk assessment models. It require 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.
- 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
Courses may include artificial intelligence, machine learning, Big data management, programming in python/java etc. Besides, any course fed by research interests are highly welcome. Also undergraduate, MSc and PhD student supervision is highly welcome
For full list, please check google scholar (link)
- M.S. Haleem, A. Ekuban, A Antonini, S Pagliara, L Pecchia, C. Allocca., Novel Deep Learning-Driven Techniques for Real-Time Multimodal Physical and Electronic Health Data Synthesis, Electronics (IF=2.7), 12, 2023
- Cisuelo, K. Stokes, I. B. Oronti, M.S. Haleem, T. Barber, M. Weickert, L. Pecchia, J. Hattersley Prospective data collection for the development and validation of artificial intelligence models for non-invasive glycaemic event detection using ECG in type 1 diabetics: study protocol, BMJ Open (IF=3.006): 2023
- Andellini, M.S. Haleem, M. Angelini, M. Ritrovato, R. Schiaffini, E. Iadanza, L. Pecchia, “A study protocol for an experimental study for detecting the associations between hypoglycemic events and cardiac conduction disorders through non-invasive monitoring using wearable devices in a pediatric population” Health and Technology (IF=2.2): 2023
- Maccaro, S. Pagliara, F. Abdulsalami, M. Zarro, W. Su, M. S. Haleem, D. Piaggio, L. Pecchia., Ethics and Biomedical Engineering for Wellbeing: a cocreation study for informing the design of a remote service of monitoring and support (preprint), 2022
- R. Jossou, Z. Tahori, G. Houdji, D. Medenou, A. Lasfar, F. Sanya, M. H. Ahouandjinou, S. M. Pagliara, M.S.Haleem and A. Tahir,” N-Beats as an EHG signal forecasting method for labour prediction in full term pregnancy” Electronics (11) (IF=2.7), 2022
- Allocca, S. Jilali, R. Ail, J. Lee, B. Kim, A. Antonini, E. Motta, J. Schellong, L. Stieler, M.S. Haleem, E. Georga, L. Pecchia, E. Gaeta, G. Fico, “Towards a Symbolic AI Approach to the WHO/ACSM Physical Activity & Sedentary Behaviour Guidelines” Applied Sciences (IF=2.7): 2022
- M.S.Haleem and L. Pecchia, “A Deep Learning Based ECG Segmentation Tool for Detection of ECG Beat Parameters”,2nd IEEE Conference on ICT solutions for ehealth 2022.
- M.S.Haleem, R. Castaldo, M. Andellini, O. Cisuelo, J. Hattersley and L. Pecchia, “Estimation of ECG Parameters via Deep Learning based ECG Segmentation Tool for Non-invasive Detection of Glycaemic Events” IUPESM World Congress On Medical Physics And Biomedical Engineering IUPESM-WC2022 2022.
- R. Castaldo, M.S. Haleem, Katy Stokes, B. Oronti, M. Franzese, L. Pecchia “Artificial intelligence for reliable medical technologies in low resources settings” Biomedical Engineering for Sustainable Development (pp.139-154)
- M.S.Haleem, R. Castaldo, S.M. Pagliara, M. Petretta, M. Salvatore, M. Franzese, L. Pecchia, “Time Adaptive ECG Driven Cardiovascular Disease Detector” Biomedical Signal Processing and Control (IF=5.076): 2021
- S.Langton, S., Bannister, J., Ellison, M., Haleem, M. S., & Krzemieniewska-Nandwani, K. (2021). Policing and mental ill-health: Using big data to assess the scale and severity of, and the frontline resources committed to, mental ill-health related calls-for-service’ Policing (IF=1.36): 2021
- M. Ellison, J.Bannister, W.D.Lee & M.S.Haleem,’ Understanding policing demand and deployment through the lens of the city and with the application of big data’ Urban Studies (IF=4.663): 2021
- GATEKEEPER: Smart living homes – whole interventions demonstrator for people at health and social risks, Horizon2020 (08/2020-Present)
- Hypoglycaemia detection via ECG and AI in diabetic patients -- EPSRC IAA (08/2020-12/2021)
- Nocturnal Hypoglycaemia detection via ECG and Artificial Intelligence in diabetic patients -- Wellcome Trust Translational Partnership (08/2020-03/2022)
- Air quality and oxygen availability in hospitals in low resource settings -- EPSRC IAA (04/2023-06/2023)
- Operational Analytics, Greater Manchester Police (01/2017-12/2019)
- The Extent and Nature of Knife Crime in Greater Manchester, Greater Manchester Police (05/2019)
- Automatic Extraction of Retinal Features to Assist Retinal Disease Diagnosis, EPSRC-DHPA (01/2012-12/2014)
Academic Services and Invited Talks
- Guest Editor, Advances in Artificial Intelligence, Machine Learning and Deep Learning Applications, MDPI, Electronics, 2022
- Review Editor, Frontier in Medical Technology for MedTech Data Analytics, since 2020
- Technical Programme Committee, IEEE International Conference on Scalable Computing and Communications, 2023
- Technical Programme Committee, IEEE International Conference on Biomedical and Health Informatics, 2023
- Organizing Committee, Warwick Engineering Postgraduate Research Symposiums, 2022
- Organizing Committee, International Biomedical and Digital Health Sciences Conference, 2022
- Organizing Committee, IEEE International Conferences on IoT, GreenCom, CPSCom, SmartData, 2017
- Review Committee of grant proposals of NIHR
- Finalist in UK ICT Pioneer 2015 competition for most exceptional thesis.
- 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.
- Recipient of Dorothy Hodgkin Postgraduate Award (DHPA) by Engineering and Physical Sciences Research Council (EPSRC), UK for pursuing PhD.