Digital health researcher and project contributor with a PhD in Health Informatics and extensive experience in clinical data analysis, stakeholder collaboration, and program coordination. Proven record of impactful research on physical examination and telehealth translatability, with a strong presence in academic publishing and national health informatics conferences. Seeking to contribute to EMPHN’s Audit and Feedback Program by driving evidence-based care improvements through collaborative leadership and practical insight.
Overview
8
8
years of professional experience
1
1
Certification
Work History
PhD Researcher – Health Informatics
Macquarie University
01.2021 - Current
Led a multi-modal research project on physical examinations in GP consultations to inform telehealth transition
Developed a clinical data extraction system using deep learning, NLP and regular expressions, achieving high accuracy across annotated datasets
Supervised teams of clinical students; trained them on keyword mapping, artefact recognition, and data logging
Engaged with GPs and clinical collaborators to review and validate interpretations of in-person consultation activities
Gathered and organized information for research purposes.
Conducted thorough literature reviews to identify gaps in knowledge and inform future research directions.
Collaborated with interdisciplinary teams to conduct comprehensive studies and generate valuable insights.
Applied ethical considerations throughout all stages of the research process, safeguarding participant welfare and data integrity.
Data Scientist – Clinical Analytics
Metabolic Health Solutions
09.2023 - 12.2023
Developed AI models integrated with sensor data to predict real-time breathing patterns for an indirect calorimetry device aimed at measuring Resting Metabolic Rate (RMR).
Analyzed clinical patterns and supported visualization/reporting for practitioner feedback.
Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
Created and implemented new forecasting models to increase company productivity.
Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.
Automated repetitive tasks using scripting languages such as Python or R, saving time during the analytical process significantly.
Optimized machine learning pipelines and computational resources deployment strategies resulting in reduced processing times.
Set up SQL database on cloud servers to store client data for query analysis.
Translated business requirements into data-driven solutions, providing value-added insights that directly contributed to the organization''s strategic goals.
Worked with stakeholders to develop quarterly roadmaps based on impact, effort and test coordinations.
Assistant Supervisor – PACE Program
Macquarie University
08.2022 - 10.2022
Monitored PACE student progress across video annotation projects
Marked deliverables, logged supervision, and contributed to training resource creation
Managed records and documentation for payroll, inventory control and workflow.
Played an integral role in the hiring process by conducting interviews, evaluating candidates'' qualifications, and making informed recommendations based on organizational fit.
Managed daily tasks, delegating responsibilities effectively to optimize team resources and meet deadlines.
Led by example, demonstrating strong work ethic and commitment to excellence.
Submitted documentation and reports to upper management.
Worked closely with other supervisors to create a cohesive, high-performing team that consistently met or exceeded work objectives.
Machine Learning Developer – Computer Vision
COMSATS University
01.2018 - 12.2019
Built video annotation systems using CNN-LSTM and clustering models to detect human healthcare tasks
Developed healthcare-specific datasets for action recognition and classification
Conducted rigorous testing and validation of machine learning models, identifying areas for improvement and optimization.
Developed custom evaluation metrics tailored to specific project requirements, ensuring accurate assessment of model performance.
Developed a robust data storage strategy, managing large volumes of structured and unstructured data efficiently for use in machine learning projects.
Presented findings from research projects at industry conferences, showcasing company expertise and thought leadership in the field of machine learning.
Research Assistant – ComSens Lab
COMSATS University
01.2017 - 12.2017
Contributed to published papers on cloud-fog optimization and smart grid load balancing
Participated actively in regular meetings with fellow researchers to discuss project updates, challenges faced, and lessons learned during ongoing activities.
Collaborated with multidisciplinary teams to develop innovative research methodologies and strategies.
Contributed to the publication of research articles in peer-reviewed journals, showcasing expertise in various topics.
Organized research materials, maintaining a well-ordered workspace conducive to productivity.
Education
PhD - Health Informatics
Macquarie University
12.2025
Masters of Science - Computer Science
COMSATS University
12.2020
Bachelor of Science - Computer Science
NUML University
12.2016
Skills
Clinical Data Analysis Primary Care Research Telehealth Readiness
Behavioural Analysis Data Collection & Quality Assurance Cross-functional Teamwork
Strong Work Ethic Works Well Under Pressure Presentation Delivery
Accomplishments
Participated, presented, and published research work at multiple conferences.
Published multiple Journal articles in peer-reviewed journals
Become a part of the patent writing team at metabolic health solutions
Winner of multiple software development competitions.
Selected Research Projects
Recognition of Physical Examination Tasks (Clinical Tasks) in GP Consultations, Developed a rule-based NLP system to automatically detect clinical physical exams from text transcripts. Validated approach with manually annotated data from 8 clinical reviewers.
Multi-Modal Analysis of GP-Patient Physical Interactions, Combined CNN-RNN architecture with transfer learning to extract visual patterns of Human-Human and Human-Object Activities. Delivered actionable insights into examination practices adaptable to telehealth.
Audit & Feedback Contribution (Ongoing), Working on models to benchmark primary care activity against best-practice standards. Collaborating on behavior change through feedback loops and clinical data interpretation.
Selected Publications
Waheed, M., Xiong, H., Lau, A. (2024). What physical examinations are observed during an in-person GP consultation? IJMI.
Waheed, M., Xiong, H., Lau, A. (2024). Automated Extraction of Physical Examination Interactions in General Practice Consultations: A Multi-Modal Using Images and Text Based Approaches. HIC 2024. DOI: 10.3233/SHTI240922
Lane, J., David, K., Ramarao, J., Ward, K., Raghuraman, S., Waheed, M., & Lau, A.Y.S. (2023). Translating Primary Care to Telehealth: Analysis of In-Person Consultations on Diabetes and Cardiovascular Disease. BJGP Open, 7(1). https://doi.org/10.3399/BJGPO.2022.0123
Waheed, M., Lau, A.Y.S. (2025). Translatability of Physical Examination to Teleconsultation in Primary Care. J Telemed Telecare. (Accepted)
Waheed, M., Hussain, S., Khan, A.A. et al. (2020). A methodology for image annotation of human actions in videos. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-020-09091-2
Conference Presentations
HIC 2024, Oral presentation, Peer-reviewed research paper on multi-modal extraction of physical examinations.