Research Interests and 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
Relevant modules: Mathematical Modelling, Data Mining and Neural Networks, Financial Services Information Systems, and Data analytics for Esports.
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 (Including Deep Learning, Representation Learning, and Generative AI) in Health and Bio, Application of ML in Medicine and Biomedical Sciences, Oxford Mathematical Institute, University of Oxford (On campus - summer program).
Collaborative Research Experience
- Conducting research in machine learning, deep learning, and AI applications in health.
- Utilizing ElectroMap for quantitative cardiac electrophysiology data analysis, advancing cardiac research through optical mapping of heart tissue.
Relevant Work Experience
Awards and Achievements
- Stanford University
- Center for Continuing Medical Education, Stanford University School of Medicine
- Contact: (650) 497-8554
- Ref.: Available of request
- Organiser: University of Leicester, UKRI Funded (UK Research and Innovation)
- Landscape Decisions Programme 2023 Conference
- Multifunctional Landscapes: From Research to Policy
- Ref.: Available of request
- Host: Birmingham City University, Birmingham, UK
- Digital Skills for Smart Manufacturing
- CPD Bootcamp
- Core Module: Machine Learning and Artificial Intelligence Applications.
- Ref.: Available of request
Professional Membership
- Royal Statistical Society, Ref. 224591 (Fellow)
- IEEE (Institute of Electrical and Electronics Engineers), Young Professional, Ref. 98514633
- BCS (British Computer Society), Ref. 995126302
- LMS (London Mathematical Society), Ref. (membership@lms.ac.uk)
- British Society for Cardiovascular Research (BSCR)
Peer Review Activities
- Reviewed manuscripts for Soft Computing Journal, Springer 2023
- Ref.: Ms. No. SOCO-D-23-05517
- Title: "Transforming Psychotic Disorder Diagnosis with Deep Learning Model on Timeseries Motor Activity Signals Soft Computing"
- For Reference: em@editorialmanager.com, Mauro Gaggero, Associate Editor, Soft Computing
- IEEE Journal of Biomedical and Health Informatics, 2024, Ref.: JBHI-02923-2024, Reviewed manuscripts.
References
Available on request