I am a physician (MBBS) turned AI researcher working at the intersection of clinical medicine, machine learning, and generative AI — from radiology-report NLP to medical-imaging model audits.
I am currently an AI Research Scientist at the Language Technologies Research Centre (LTRC), IIIT Hyderabad, where I lead an NLP pipeline that extracts 54 standardised fields from free-text rectal-cancer MRI radiology reports.
Before AI, I practised as a physician for over a decade across inpatient, outpatient, and family-medicine settings. That clinical grounding is the through-line of my research: I care about whether medical AI is not just accurate, but faithful, validated, and safe to put in front of a clinician.
I hold a Master's in Professional Studies in Data Analytics & Applied Machine Intelligence from Northeastern University (GPA 4.0/4.0), building on an MBBS from Rajiv Gandhi University of Health Sciences, Mysore Medical College.
Research-grade engineering across the medical-AI stack, from data to deployment.
Clinical NLP, structured extraction from radiology reports, medical imaging, AI-driven clinical decision support.
Transformer fine-tuning, low-rank adaptation, retrieval, and ensemble methods with domain-constrained post-processing.
LLM pretraining and fine-tuning, instruction tuning, prompt engineering, and mechanistic analysis of VLMs.
Python-first, with the PyTorch / TensorFlow ecosystem and high-performance and cloud GPU training.
A selection of open-source projects. More on my GitHub.
Cross-model audit of whether chest-X-ray vision-language-model attention overlays match radiologist boxes, with a radiologist reader study. Accepted at MICCAI iMIMIC 2026.
View repository → Medical ImagingUNet-based liver and tumour segmentation from 3D CT volumes, validated via visual and loss analysis.
View repository → Medical ImagingU-Net segmentation on cardiac MRI reaching a Dice similarity coefficient of 0.95.
View repository → Generative AIA transformer LLM built from scratch, pretrained and instruction-tuned with LoRA, cosine-decay scheduling, and gradient clipping.
View repository → Clinical NLPBERT fine-tuned on 50k sentences for mental-health classification; deployed on Hugging Face Spaces.
View repository → RAG · HealthA RAG + FAISS assistant that generates personalised Type-2 diabetes meal plans from medical literature.
View repository →Peer-reviewed work in medical AI and clinical research.
Coverage of my research with the Language Technologies Research Centre at IIIT Hyderabad on the reliability of medical AI explanations.
Our study audits four chest X-ray vision-language models across three datasets and includes a two-radiologist reader study. It examines the distinction between a plausible attention overlay and faithful grounding in the image.
Reporting and commentary on the chest X-ray vision-language model study.
Newspaper clippings preserved by IIIT Hyderabad.
The research feature and official media archive from IIIT Hyderabad.
Additional summaries, syndicated mentions, and curated news listings.
Coverage collected through 11 October 2026. Press reports, print clippings, and news digests are listed separately from the research paper. Some publishers restrict access; the original links and IIITH clipping archive are provided.
Open to research collaborations and PhD opportunities in medical AI, computational pathology, and clinical NLP.