👤 Biography
I am a doctoral researcher in Artificial Intelligence for Healthcare 🧠🏥, currently based in London 🇬🇧. My research is conducted under the supervision of Dr. Nasim Dadashiserej, where I focus on developing Explainable AI (XAI) models for risk stratification in healthcare 📊.
My research aims to build transparent and clinically trustworthy AI systems 🤝 that support early diagnosis and decision-making. I work at the intersection of Explainable AI, machine learning, and deep learning 🤖, integrating advanced clinical feature selection techniques to ensure models are both accurate and medically meaningful. I also explore interpretability frameworks such as SHAP and LIME 🔍, along with multimodal healthcare data integration, to enhance model reliability in real-world clinical settings.
Prior to my PhD, I gained valuable experience working within the NHS in Bristol and London 🏥, where I was exposed to real-world NHS workflows, patient data systems, and operational challenges. This experience played a key role in shaping my motivation to pursue doctoral research in healthcare AI. I worked as an RTT (Referral to Treatment) Data Validator 📑, where I was responsible for ensuring the accuracy and integrity of patient pathway data in line with NHS standards. RTT pathways represent the patient journey from initial referral to the start of treatment, forming a critical component of waiting time management and healthcare delivery performance ⏱️.
Through this role, I developed a deeper understanding of clinical data quality, pathway validation, and healthcare system dynamics, which now directly informs my research approach. It highlighted the importance of reliable, interpretable models that can be trusted by clinicians and aligned with operational healthcare needs.
I hold a Master’s degree in Data Science 🎓 from Cardiff Metropolitan University, where I built a strong foundation in data analytics, statistical modeling, and machine learning. My previous projects include developing predictive models for diseases such as Parkinson’s using speech data, as well as working with modern AI approaches including large language models (LLMs) and efficient fine-tuning techniques like LoRA and QLoRA ⚙️.
My broader research interests lie in AI-driven clinical decision support systems, digital health innovation, and trustworthy AI 🚀. I am particularly passionate about translating advanced AI techniques into practical healthcare solutions that improve patient outcomes and system efficiency ❤️. I actively seek collaboration opportunities in healthcare AI, biomedical data science, and translational research 🤝.
🎓 Qualifications
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MSc in Data Science 📊
Cardiff Metropolitan University, Cardiff, United Kingdom -
B.Tech in Electrical and Electronics Engineering ⚡
VRS Engineering College, India
👨🏫 Supervisors
🔬 Research Interests
- Explainable Artificial Intelligence (XAI) in Healthcare 🧠
- Risk Stratification and Predictive Modeling in Clinical Systems 📊
- Machine Learning and Deep Learning for Medical Data 🤖
- Clinical Decision Support Systems (CDSS) 🏥
- Healthcare Data Analytics and Electronic Health Records (EHR) 📁
- Advanced Feature Selection Techniques for Clinical Data ⚙️
- Generative AI and Large Language Models (LLMs) in Healthcare ✨