Research Interests & Technical Skills
My research focuses on addressing the statistical challenges associated with highly structured data from diverse applications, including imaging and wearable technologies. These data are often discrete samples of complex underlying functional processes, which present dependencies that are difficult to model using traditional statistical approaches. My work aims to develop computationally efficient methods that preserve information across all dimensions of these data while ensuring the results are interpretable and actionable. Additionally, I apply advanced statistical and machine learning techniques, such as mixed effects models, gradient boosting, and tree-based methods, to support research in epidemiology, neurology, and oncology.
Education
2020 Sep – 2023 Jan
MSc in Data Analysis for Business Intelligence with Industry
University of Leicester, Leicester, United Kingdom
Relevant modules: Mathematical Modelling, Data Mining and Neural Networks, Financial Services Information Systems, and Data Analytics for Esports.
2019 Jan – 2020 July
Masters in International MBA
Birmingham City University, Birmingham, United Kingdom
Relevant modules: Global Marketing Management, Managing Financial Performance, International Operations and Project Management.
Professional Development
AI in Healthcare: Applications and Concepts, Harvard T.H. Chan School of Public Health, Harvard University, Fellowship (On campus)
AI and Digital Transformation in Health Care, Critical Thinking, University of Cambridge (On campus - summer program)
ML in Health and Bio, Application of ML in Medicine and Biomedical Sciences, Oxford Mathematical Institute, University of Oxford (On campus - summer program)
Mediterranean Machine Learning Summer School, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia.
(Funded, On-campus, Sep. 2025) (On-campus summer program)
Focus areas: Computer Vision, Generative and Diffusion Models, Ethics in Machine Learning
Poster Presentation Title: CardioFlowFormer
Focus areas: Computer Vision, Generative and Diffusion Models, Ethics in Machine Learning
Poster Presentation Title: CardioFlowFormer
Research Experience
November 2024 - Present
Researcher
University of East London, London, E16 2RD
- Computational Precision Cardiomyocyte Ageing
January 2023 - Present
Researcher, Part-Time, Remote
IVR Low Carbon Research Institute, Chang'an University, Xi'an, China
- Conducting research in machine learning, deep learning, and AI applications in health
December 2023 - June 2024
Researcher, Part-Time, Hybrid
University of Birmingham, Birmingham, UK
- Utilizing ElectroMap for quantitative cardiac electrophysiology data analysis, advancing cardiac research through optical mapping of heart tissue
Relevant Work Experience
February 2023 - June 2024
Data Analyst
Midland Heart Ltd, United Kingdom
June 2022 – October 2022
MSc Data Analysis Project
HSBC Financial Services Company, London, UK
Project: Machine Learning and Sustainability Metrics: Optimising Risk Assessment and Default Prediction
August 2021 – June 2022
M.Sc. Internship
ASAP Data Solution Ltd., Hatfield, United Kingdom
January 2021 – May 2021
Data Analytics for Esports Project
Leicester, United Kingdom
Project: Optimizing E-Sports Revenue: A Novel Data Driven Approach to Predicting Merchandise Sales Through Data Analytics and Machine Learning
February 2021 – April 2021
Fundamental Data Science Module Project
Leicester, United Kingdom
Project: Enhancing Prediction and Analysis of UK Road Traffic Accident Severity Using AI: Integration of Machine Learning, Econometric Techniques, and Time Series Forecasting in Public Health Research
Awards & Achievements
Conference Scholarship - Stanford University
Conference Scholarship - The Royal Society
Bootcamp Scholarship - WMCA
Travel Grant - British Cardiovascular Research Society
Professional Membership
Royal Statistical Society (Fellow) - Ref. 224591
IEEE Young Professional - Ref. 98514633
British Computer Society - Ref. 995126302
London Mathematical Society
British Society for Cardiovascular Research
Peer Review Activities
Soft Computing Journal, Springer 2023
Reviewed manuscript: "Transforming Psychotic Disorder Diagnosis with Deep Learning Model on Timeseries Motor Activity Signals"
Reference: Ms. No. SOCO-D-23-05517
Reference: Ms. No. SOCO-D-23-05517
IEEE Journal of Biomedical and Health Informatics, 2024
Reference: JBHI-02923-2024
Peer Review Verified:
Verified Link
References
Available on request