Radiation Therapy | Data Science | AI & ML
Bridging clinical insights and intelligent healthcare solutions through data science, artificial intelligence, and digital innovation.
Clinical Expertise. Data Intelligence. Healthcare Innovation.
I am a Radiation Therapist with over five years of clinical experience in radiation oncology, working with state of the art advanced treatment machines. My clinical expertise spans SBRT, IMRT, IGRT, and SRS, with a focus on precision treatment delivery, patient safety, and oncology workflows.
Building on this clinical foundation, I am expanding into Data Science, Machine Learning, and Artificial Intelligence, pursuing advanced training through the E&ICT Academy at IIT Guwahati. My focus includes medical image analysis, deep learning, computer vision, and AI-driven healthcare applications.
What distinguishes my approach is the ability to connect clinical context with computational intelligence. From understanding treatment plans and dose-volume histograms (DVHs) to working with DICOM medical imaging data, I bring practical oncology knowledge to the development of clinically relevant data and AI solutions.
My goal is to contribute to Healthcare AI, Medical Imaging AI, and Clinical Data Science, helping translate complex clinical data into meaningful insights and intelligent healthcare technologies.
Connecting clinical oncology expertise with AI, medical imaging, and clinical data science, building intelligent tools that stay grounded in real clinical workflows, not just trained on data.
My interest in Healthcare AI didn't start in a classroom - it started on the treatment couch, watching how much of clinical decision-making still depends on manual review, repeated measurements, and institutional memory that lives in a few experienced heads rather than in the data itself.
That's the gap I want to help close. Not by replacing clinical judgement, but by building tools that make it faster, more consistent, and easier to scale across centres that don't have the luxury of a large physics or data team.
Over the next few years, my focus is on shipping real, working systems as the Founder of VINE Clinical Intelligence™, starting with the VINE ecosystem: auto-contouring, DICOM-native viewers, and decision-support tools built by someone who has actually stood in the bunker.
Five years at the frontline of precision radiotherapy, building AI alongside clinical practice.
Delivered precision radiotherapy across CyberKnife M6, Radixact X9 Tomotherapy, Elekta Versa HD and 4DCT workflows. Specialised in SBRT, SRS, IMRT and IGRT, with a focus on patient safety and treatment accuracy, plus collected the longitudinal intrafraction motion data behind my ML thesis.
Building a suite of clinical AI tools under VINE.Ci™ - including a DICOM viewer, auto-segmentation for medical imaging, and an education app for RTTs, combining clinical insight with Python, MONAI, FastAPI and React.
Foundation in medical science, accelerated by AI/ML engineering.
The undergraduate thesis that shaped a clinical eye for motion and margins, plus hands-on data science and agentic-AI builds from the IIT Guwahati program.
Founder, VINE Clinical Intelligence - VINE.Ci ™
Clinical and professional body registrations held in the UK and India.
Peer-reviewed research at the intersection of radiotherapy physics and medical imaging, from undergraduate thesis to conference presentation.
📊 PTV reduction chart
🎤 Presenting at MVR CANCON
Perspectives from the treatment room and the terminal, organised by discipline.
My CVs are tailored to different career paths, from Radiation Therapy and Clinical Oncology to Data Analytics, Data Science, and Healthcare AI.
For data and AI-focused roles, my CV highlights technical skills, portfolio projects, and applied AI/ML capabilities, supported by over five years of hands-on clinical experience. For clinical roles, it emphasizes radiotherapy expertise, advanced treatment technologies, and precision treatment delivery.
I am interested in opportunities across Healthcare AI, Medical Image Analysis, Clinical & Healthcare Data Analytics, Data Science, ML Engineering, and Clinical AI Implementation.
Open to opportunities, collaborations, and meaningful conversations in Healthcare AI, Data Science, and Clinical Oncology.
