MSc Artificial Intelligence · Heriot-Watt University (3.6 GPA)
PhD applicant in medical AI for oncology, with interests in cancer imaging, breast cancer screening, radiomics, radiogenomics, and responsible clinical AI evaluation.
Based in Kerala, India
I'm building toward research in medical AI for oncology, especially where medical imaging, clinical data, and responsible model evaluation can support better diagnosis, risk assessment, treatment planning, and follow-up decisions.
My MSc dissertation on medical image concept detection gave me a foundation in radiology image pipelines, multi-label deep learning, and evaluation beyond accuracy. I am now developing a focused portfolio around oncology imaging, breast cancer AI, radiomics/radiogenomics, reproducible deep learning workflows, and clinically meaningful model evaluation.
Current interests:
- Medical image analysis and deep learning for oncology
- Breast cancer screening and imaging-based risk assessment
- Radiomics and quantitative imaging biomarkers
- Radiogenomics and multimodal oncology AI
- Explainable and responsible clinical AI
- Reproducible model evaluation using clinically meaningful metrics
| Repository | What it is |
|---|---|
| oncology-imaging-concept-detection | Reproducible deep learning workspace for oncology imaging and medical image concept detection, extending my MSc dissertation toward clinically oriented evaluation and future radiomics workflows |
| monai-mednist-baseline | Medical image classification baseline using MONAI and PyTorch on MedNIST, with preprocessing, validation metrics, confusion matrix analysis, precision, recall, and F1-score |
| breast-cancer-classification | Machine learning pipeline for diagnostic breast cancer classification, focused on structured preprocessing, baseline modelling, metric comparison, and clear documentation of model limitations |
-
🎓 MSc Artificial Intelligence — Heriot-Watt University, Edinburgh (2022–2023)
Dissertation: Investigating Concept Detection Techniques in Medical Images -
🔬 Research Engineer — Machine Learning, Invesdwin GmbH (Dec 2025–present)
Research-oriented computational validation, reproducible experimentation, structured data workflows, debugging, and technical documentation -
🧪 Machine Learning Research Intern — Heriot-Watt University / 123 Invest Group (2023)
Optimisation algorithms, Java/Python workflows, research documentation, and supervisor-led progress reviews -
👩🏫 Teaching Assistant — Java and Machine Learning, Heriot-Watt University (2023–2024)
Supported programming and machine learning learning activities through tutorials, debugging support, and model workflow explanations -
🎓 B.Tech Computer Science and Engineering — College of Engineering, Munnar (2016–2020)
Stack: Python · PyTorch · PyTorch Lightning · MONAI · TorchVision · scikit-learn · Pandas · NumPy · Java · SQL · Git/GitHub
Actively building my research portfolio in medical AI for oncology. Always happy to discuss cancer imaging, breast cancer AI, radiomics/radiogenomics, responsible clinical AI evaluation, or potential PhD and research opportunities.