School of Computing and Digital Media staff profiles content store_hidden Jonathan Iworiso Our staff

Dr Jonathan Iworiso is a Senior Lecturer in Mathematics and Statistics for the School of Computing and Digital Media at London Met. He holds a BSc (Hons) in Mathematics/Statistics at University of Calabar, MSc in Statistics & Data Analysis, and PhD in Statistics with specialisation in Machine Learning and Deep Learning Techniques at University of Essex. He has over 12 years of teaching and research experience in the higher education sector. Jonathan academic knowledge and teaching experience were gained at University of Calabar, Federal University Otuoke and University of Essex. He is passionate about the use of modern pedagogical approaches to facilitate teaching and learning support with sustainability in the higher education sector. He has recently developed a framework for decolonising the curriculum in science and computing with sustained evidence of effectiveness, focusing on students’ success. The framework could be extended to the science, technology, engineering and mathematics (STEM) via interdisciplinary and multidisciplinary research collaboration with learned colleagues across the globe. Dr Iworiso is a recipient of an Exceptional Talent Endorsement with Exceptional Talent (Visa) Leave-to-Remain in the United Kingdom, following his demonstrable track records with laudable potentials, innovative research and effective contributions in the field of Machine Learning. He is highly committed to recruiting and supervising degree projects, MSc dissertations and PhD thesis in his field of expertise. He is highly experienced in the use of software and programming language (Excel, SAS, Stata, SPSS, R, RStudio, MATLAB, Python) for Computational Statistics and Data Analysis with applications in Finance, Economics, Environment, Biotechnology, Public Health, Medicine, Politics and Government Decision Making. Dr Iworiso is currently accepting PhD applications for supervision, in relevant disciplines with programming experience or expertise in the use of sophisticated statistical and data analysis software (R, RStudio, Python). He is a seasoned editor and/or reviewer of articles in many international journals including American Journal of Applied Mathematics and Statistics, International Journal of Econometrics and Financial Management, Journal of Statistics Applications and Probability, International Journal of Data Science and Analysis, International Journal of Business and Risk Management, Journal of Forecasting.

Dr Iworiso is currently accepting PhD applications for supervision, in relevant disciplines with programming experience or expertise in the use of sophisticated statistical and data analysis software (R, RStudio, Python). He is keen to develop new research areas in Machine Learning for Predictive Analytics with applications in Finance, Economics, Environment, Biotechnology, Public Health, Medicine (Clinical Trials), Politics and Government Decision Making. He is happy to collaborate with colleagues in industries and academia across the globe, and to embark on knowledge exchange or transfer partnership and commercialisation. Dr Iworiso’s research output could be considered as world leading or internationally excellent, with strong impact to research excellence framework (REF) and beyond academics. 

He is mainly interested but not limited to Machine Learning and Data Science research, spanning the following key areas: 

• Computational Statistics 
• Applied Statistics 
• Exploratory Data Analysis 
• Machine Learning 
• Data Mining 
• Scientific Computing 
• Data Science 
• Big Data 

Should you have any questions or concerns regarding PhD application or seeking potential collaboration, please feel free to contact him by email j.iworiso@londonmet.ac.uk or telephone +44 (0) 2071334554. 

• Data Analysis 
• Statistical Modelling and Forecasting 
• Computational Statistics 
• Financial Mathematics 
• Discrete Mathematics (Logic and Problem Solving) 
• Statistical Methods and Modelling Markets 
• Financial Modelling and Forecasting 

Dr Iworiso's duties include development of new modules, designing instructional materials, module leadership, lecture delivery, innovative teaching, pedagogic research, scholarship, tutoring of courses, marking, evaluation, assessment and feedback, students’ mentoring, pastoral care and in-depth support, work-related projects coordination, project supervision, active participation in course area committees as well as University open days. He is passionate about the use of modern teaching technologies and pedagogical approaches to facilitate teaching and learning support with sustained evidence of effectiveness in the higher education sector. He is highly committed to promoting equality, diversity and inclusion among diverse learners and making the learning environment welcoming to all categories of learners, while upholding professional standards and values in accordance with the UK professional standards framework. The use of Panopto with Livestreaming (Webcast), Blackboard Collaborate via Weblearn, MEDIAL App, MS Teams, Zoom, Google Meet and Adobe Connect for Video Conferencing have contributed immensely to promote the teaching excellence framework (TEF), thereby enhancing students’ experience and satisfaction. 

Ocharive, A., & Iworiso, J. (2024). The Impact of Digital Financial Services on Financial Inclusion: A Panel Data Regression Method. International Journal of Data Science and Analysis, 10(2), 20-32. Available online at https://www.sciencepublishinggroup.com/article/10.11648/j.ijdsa.20241002.11 

Olawale, I. O., Iworiso, J., & Amaunam, I. A. (2023). Predicting Stock Investments Based on Sentiment and Historical Price Data. International Journal of Data Envelopment Analysis and* Operations Research*, 4(1), 1-32. 

Iworiso, J., Temerigha, R. T., & Idiko, B. (2023). Investigating the Impact of Taxation Revenue Management and its Implications on the Sustainability of Nigerian Economic Growth. International Journal of Business and Risk Management, 4(1), 2

Iworiso, J. (2023). Forecasting Stock Market Out-of-Sample with Regularised Regression Training Techniques. International Journal of Econometrics and Financial Management, 11(1), 1-12. 

Iworiso, J. & Vrontos, S. (2019). On the Directional Predictability of Equity Premium Using Machine Learning Techniques. Journal of Forecasting, 39(3), 449-469

Iworiso, J.  (2020). Multivariate Time Series Analysis to Impact Assessment of Nominal Economic Indicators on Federal Government Revenue and Economic Growth in Nigeria. American Journal of Applied Mathematics and Statistics, 8(3), 69-89.

Iworiso, J. & Vrontos, S. (2021). On the Predictability of the Equity Premium Using Deep Learning Techniques. The Journal of Financial Data Science, 3(1), 74-92.

Iworiso, J. (2021). Post Hoc Analysis of Life Expectancy in West Africa. American Journal of Applied Mathematics and Statistics, 9(2), 57-65.

Adekunle, I. M., Roberts, E. M., Offoha, M. U., Alawode, T. T., Adekunle, A. A., Ilesanmi, B., Adeleke, J.A., Udo, I.I. & Iworiso, J. (2013). Green Energy Solutions in Nigeria: Merits, Challenges and Way forward. Regional Conference of the International Network of Women Scientists and Engineers, Nairobi, Kenya.

Conference Proceedings, Workshops and Seminars

A Framework for Decolonising the Curriculum in Science and Computing. A Presentation in the Learning & Teaching Conference organised by the Centre for Professional and Educational Development, held June 2023 at London Metropolitan University.

Practical Data Analysis in Excel, SPSS and RStudio. A Workshop for Postgraduate Research (PhD) Students and Postdoctoral Research Fellows in Quantitative Research involving Data Analysis at London Metropolitan University, February 2023.

Model Complexity and its Applications in Finance and Emerging Markets. School of Computing and Digital Media (SCDM) Lunchtime Seminar Presentation, held May 2022.

Quantitative Research, Statistics and Data Analysis. A Workshop for Postgraduate Research (PhD) Students and Postdoctoral Research Fellows in Quantitative Research involving Data Collection, Statistics and Data Analysis at London Metropolitan University, held June 2022.

Forecasting the Equity Premium Out-of-Sample with Sophisticated Regressing Training Techniques. 7^th Brazilian Conference on Statistical Modelling, Insurance and Finance; held March 2020 in Maresias, Brazil.

Return Sign Predictability with Economic Significance Using Sophisticated Machine Learning Techniques. 18^th European Economics and Finance Society Annual Conference (EEFS 2019), held June 2019 at University of Genoa, Italy.

On the Directional Predictability of U.S Stock Market Using Machine Learning Techniques. 23^rd International Congress on Insurance: Mathematics and Economics (IME 2019), held July 2019 in collaboration with Technical University of Munich, in Munich, Germany.

Directional Predictability of Stock Market Using Machine Learning Techniques. 2^nd Queen Mary University of London Economics and Finance Workshop for PhD Students & Post-doctoral Research Fellows, held May 2019.

Green Energy Solutions: The Empirical Evidence. Regional Conference of the International Network of Women Scientists and Engineers; held November 2013 in Nairobi, Kenya.

Following Dr Iworiso's intellectual strength and valuable contributions in academia and industries, he has received several awards and grants from various funding bodies. He is collaborating with colleagues in writing applications for external funding by reputable funding bodies such as the Engineering and Physical Science Research Council (EPSRC), Natural Environment Research Council among others.

• 2023/24 – External Project Grant awarded by the National Institute of Health Research (NIHR), to undertake a multidisciplinary research project titled Cancer Screening Uptake in Women in Argentina, in collaboration with the Centre for Primary Health & Social Care - £155,724
• 2023 – Internal Project Grant from Rescaling Fund, granted by London Met to undertake a research project titled Advanced Machine Learning Algorithms for Blood Pressure Classification: Early detection or prevention could save lives - £1,500
• 2021 – Rescaling and Transformation Fund, granted for development of short courses in R and RStudio to promote students' employability skills and increase student recruitment for postgraduate research (PhD) - £4,200
• 2021 – Rescaling award for Statistics, Operational Research and Mathematics (STORM) project with the Fetal Medicine Research Institute in King's College London - £4,000
• 2019 – Department of Mathematical Sciences Funding granted to facilitate publication of articles in peer-reviewed journals - £1,000.00
• 2016 – Proficio Funding granted by University of Essex, to facilitate research and active participation in international conferences - £2,000.00
• 2016 – Tertiary Education Trust Fund (TETFUND) sponsorship awarded by the Federal Government of Nigeria to study PhD degree in Statistics at the University of Essex, UK.
• 2014 – Presidential Scholarship awarded by the Presidency Federal Republic of Nigeria to study MSc degree in Statistics and Data Analysis at the University of Essex, UK – £28,900.00

Dr Iworiso is highly dedicated to professional development and progression in his career. As part of continuing professional development (CPD) to promote best practices in the academia and contribute to sustainable development in the wider society, he is an active fellow of many professional bodies. His professional engagements have enhanced his job role, taking on appropriate leadership, administrative and management responsibilities. 

• Senior Fellow of the Higher Education Academy (SFHEA) 
• Fellow, Royal Statistical Society (RSS) London 
• Member, International Statistical Institute (ISI) 
• Member, International Association of Statistical Computing (IASC) 
• Member, Education for Sustainable Development (ESD) Specialist Group 
• Member, Education for Social Justice Forum (ESJF) 

Dr Jonathan Iworiso
Senior Lecturer in Mathematics and Statistics
j.iworiso@londonmet.ac.uk