Liverpool Skyline

Department of Electronics and Electrical Engineering

Dr Ibrahim Idowu

Biography

Dr Ibrahim Idowu has a BSc degree in Information System, MSc in Computer Forensics and PhD in Computer Science. His research interests include data science, artificial intelligence, machine learning and advanced algorithm development.

Languages

English
Yoruba

Degrees

Liverpool John Moores University, United Kingdom, PhD in Computer Science
Liverpool John Moores University, United Kingdom, MSc in Computer Forensics
Lancaster University, United Kingdom, BSc in Information System

Publications

Conference Publication (journal proceedings)

Khalaf M, Hussain AJ, Al-Jumeily D, Keight R, Keenan R, Al Kafri AS, Chalmers C, Fergus P, Idowu IO. 2017. A performance evaluation of systematic analysis for combining multi-class models for sickle cell disorder data sets Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10362 LNCS :115-121 >DOI

Khalaf M, Hussain AJ, Al-Jumeily D, Keight R, Keenan R, Fergus P, Al-Askar H, Shaw A, Idowu IO. 2016. Training Neural Networks as Experimental Models: Classifying Biomedical Datasets for Sickle Cell Disease Huang DS, Bevilacqua V, Premaratne P. INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2016, PT I, 12th International Conference on Intelligent Computing (ICIC) 9771 :784-795 >DOI >Link

Khalaf M, Hussain AJ, Keight R, Al-Jumeily D, Keenan R, Fergus P, Idowu IO. 2016. The Utilisation of compsiste Machine Learning models for the Classification of Medical Datasets For Sickle Cell Disease 2016 SIXTH INTERNATIONAL CONFERENCE ON DIGITAL INFORMATION PROCESSING AND COMMUNICATIONS (ICDIPC), 6th International Conference on Digital Information Processing and Communications (ICDIPC) :37-41 >Link

Khalaf M, Hussain AJ, Al-Jumeily D, Keenan R, Keight R, Fergus P, Idowu IO. 2015. Applied Difference Techniques of Machine learning Algorithm and Web-based Management System for Sickle Cell Disease Jumelly DA, Hussain A, Tawfik H, MacDermott A, Lempereur B. PROCEEDINGS 2015 INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ESYSTEMS ENGINEERING DESE 2015, International Conference on Developments in eSystems Engineering (DeSE) :231-235 >DOI >Link

Khalaf M, Hussain AJ, Al-Jumeily D, Keenan R, Fergus P, Idowu IO. 2015. Robust Approach for Medical Data Classification and Deploying Self-Care Management System for Sickle Cell Disease Wu YL, Min GY, Georgalas N, Hu J, Atzori L, Jin XL, Jarvis S, Liu L, Calvo RA. CIT/IUCC/DASC/PICOM 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY - UBIQUITOUS COMPUTING AND COMMUNICATIONS - DEPENDABLE, AUTONOMIC AND SECURE COMPUTING - PERVASIVE INTELLIGENCE AND COMPUTING, IEEE International Conference on Computer and Information :575-580 >DOI >Link

Khalaf M, Hussain AJ, Al-Jumeily D, Fergus P, Idowu IO. 2015. Advance Flood Detection and Notification System based on Sensor Technology and Machine Learning Algorithm Liatsis P, Uus A, Miah S. 2015 INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP 2015), 22nd International Conference on Systems, Signals and Image Processing (IWSSIP) :105-108 >Link

Idowu IO, Fergus P, Hussain A, Dobbins C, Khalaf M, Eslava RVC, Keight R. 2015. Artificial Intelligence for Detecting Preterm Uterine Activity in Gynacology and Obstertric Care Wu YL, Min GY, Georgalas N, Hu J, Atzori L, Jin XL, Jarvis S, Liu L, Calvo RA. CIT/IUCC/DASC/PICOM 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY - UBIQUITOUS COMPUTING AND COMMUNICATIONS - DEPENDABLE, AUTONOMIC AND SECURE COMPUTING - PERVASIVE INTELLIGENCE AND COMPUTING, IEEE International Conference on Computer and Information :215-220 >DOI >Link

Idowu IO, Fergus P, Hussain A, Dobbins C, Al-Askar H. 2014. Advance Artificial Neural Network Classification Techniques Using EHG for Detecting Preterm Births 2014 EIGHTH INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT AND SOFTWARE INTENSIVE SYSTEMS (CISIS),, 8th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS) :95-100 >DOI >Link

Journal Articles

Fergus P, Idowu I, Hussain A, Dobbins C. 2016. Advanced artificial neural network classification for detecting preterm births using EHG records NEUROCOMPUTING, 188 :42-49 >DOI >Link

Fergus P, Idowu IO, Hussain AJ, Dobbins C, Al-Askar H. 2014. Evaluation of Advanced Artificial Neural Network Classification and Feature Extraction Techniques for Detecting Preterm Births Using EHG Records Huang DS, Han K, Gromiha M. INTELLIGENT COMPUTING IN BIOINFORMATICS, 8590 :309-314 >Link

Theses / Dissertations

Idowu IO, Fergus , Hussain , Dobbins . Classification Techniques Using EHG Signals for Detecting Preterm Births Fergus PF, Hussain , Dobbins .