🎓 M.Tech in Computer Engineering | Aligarh Muslim University, India (CGPA: 8.80/10)
🏥 Clinical Data Scientist @ QIRAIL Lab, CMC Vellore
🧠 Radiomics • Auto-Segmentation • Adaptive Radiotherapy • Cancer AI • Uncertainty Quantification

I am a clinical data scientist and medical imaging researcher working at the Quantitative Imaging Research and Artificial Intelligence Lab (QIRAIL), Department of Radiation Oncology, Christian Medical College, Vellore, India, one of India's leading cancer centers.

My work focuses on building AI pipelines that help oncologists make smarter, faster, and more personalized treatment decisions for head and neck cancer patients.

My research primarily focuses on:

• Radiomics-Based Cancer Outcome Prediction
• Automated Tumor Segmentation (3D CNNs, nnU-Net)
• Adaptive Radiotherapy & Treatment Planning Automation
• Uncertainty Quantification in Clinical AI
• DICOM/PACS Engineering & Clinical Data Pipelines
• Multimodal Deep Learning for Oncology

I have authored and co-authored multiple papers, including a Poster Highlight presented at the European Society for Radiotherapy and Oncology (ESTRO) 2026, Sweden, a Springer LNEE conference paper, a medRxiv preprint, and an Elsevier book chapter. I also organize hands-on radiomics and auto-segmentation workshops for clinicians, Medical Physics, and researchers.

I genuinely enjoy talking with people — researchers, clinicians, or anyone curious about AI in healthcare. Feel free to reach out anytime.

🎯 I am actively looking for PhD positions in medical imaging, radiation oncology AI, uncertainty quantification, adaptive radiotherapy, and cancer research.

• 📄 Anatomy-Guided Skip-connection Recalibration for CT-based Head and Neck Tumor Auto-segmentation
  Asjad Nabeel P, Hannah Mary Thomas T, Hasan Shaikh, Sathya A, Rajendra Benny Kuchipudi, Jino Wilson Victor, Simon P Pavamani, Balu Krishna Sasidharan, Jeny Rajan
  International Journal of Biomedical Imaging, 2026

• 📄 Can reproducibility be achieved? External validation of 'Reproducible' image-based prognostic models for head and neck cancer
  Hasan Shaikh, Sathya A, Praveenraj C, Balu Krishna S, Aparna Irodi, Rajendra Benny Kuchipudi, Jino Wilson Victor, Manu Mathew, Rajesh Isiah, Simon Pavamani, Joy Mammen, Hannah Mary Thomas T
  Scientific Reports, Nature Portfolio, 2026

• 📄 Development and validation of a prospective radiomics-clinical signature for locoregional recurrence in patients with locally advanced head and neck cancer
  Balu Krishna S, Amal Joseph Varghese, Hasan Shaikh et al.
  European Society for Radiotherapy and Oncology (ESTRO), Stockholm, Sweden, 2026 — ✅ Accepted (Abstract, Poster)

• 📄 Metaheuristic-Driven Machine Learning Pipelines for Radiomics-Based Prediction of Locoregional Recurrence in Head and Neck Cancer
  Hasan Shaikh, Balu Krishna S, Amal Joseph Varghese et al.
  Proceedings of the International Conference on Artificial Intelligence for Healthcare (AIHC), Lecture Notes in Electrical Engineering, Springer Nature, 2025 — ✅ Accepted

• 📄 Automated Segmentation of Head and Neck Cancer from CT Images Using 3D Convolutional Neural Networks
  Piyus Prabhanjans, Asjad Nabeel P, Aparna V K, Hannah Mary Thomas T, Balu Krishna Sasidharan, Hasan Shaikh, Amal Joseph Varghese, Rajendra Benny Kuchipudi, Simon Pavamani, Jeny Rajan
  medRxiv, 2026

• 📄 Cancer Survival Prediction Using Artificial Intelligence: Current Status and Future Prospects
  Hasan Shaikh and Rashid Ali
  Data Science in the Medical Field, Academic Press, Elsevier, 2024

• 🪧 "Before We Treat, Can We Tell? A Locoregional Recurrence Signature in Head & Neck"
  Hasan Shaikh, Amal Joseph Varghese, Balu Krishna S et al.
  15th Annual Research Day, Christian Medical College, Vellore, India, 2025

• 🪧 "Can CT Radiomics Predict Recurrence in Head and Neck Cancer? Early Results from a Prospective Imaging Trial"
  Hasan Shaikh, Amal Joseph Varghese, Hannah Mary Thomas T et al.
  14th Annual Research Day, Christian Medical College, Vellore, India, 2024

• 🛠️ 2nd Workshop on Radiomics and Auto-Segmentation - 2nd edition (March 2026)
  Department of Radiation Oncology & QIRAIL Lab, Christian Medical College, Vellore, India, hands-on training for clinicians, Medical Physics, and researchers on radiomics pipelines and auto-segmentation tools.

• 🛠️ 1st Workshop on Radiomics and Auto-Segmentation - 1st edition (November 14-15, 2025)
  Department of Radiation Oncology & QIRAIL Lab, Christian Medical College, Vellore, India, hands-on training for clinicians, Medical Physics, and researchers on radiomics pipelines and auto-segmentation tools. Certificate

I'm actively applying for PhD positions. If your lab works on any of the following, I'd love to connect:

• 🧠 Medical image analysis & segmentation
• 🎯 Radiomics & cancer outcome prediction
• 📐 Uncertainty quantification in clinical AI
• ⚙️ Adaptive radiotherapy & treatment planning automation
• 🔁 Auto-segmentation for radiation oncology workflows
• 🧬 Multimodal learning for cancer research

Medical Imaging: 3D Slicer · ITK-SNAP · Orthanc PACS · XNAT · DICOM · NIfTI
ML/DL: TensorFlow · Keras · scikit-learn · nnU-Net
Infra: Docker · GitHub · PostgreSQL · Bash

• 💬 I love talking with people — researchers, clinicians, engineers, or anyone curious about AI in healthcare. Just message me.
• 🤖 I believe AI will eventually automate radiation oncology end-to-end — radiation therapy delivery, treatment planning, auto-segmentation, adaptive radiotherapy, and a fully paperless AI-driven EMR. We're close.
• 🌍 The biggest impact of medical AI won't be in well-resourced hospitals — it'll be in under-resourced settings where expert clinicians are scarce.
• 📍 Based in Vellore, Tamil Nadu, India

I'm always open to conversations about research, PhD opportunities, or collaborations.

💡 "Making radiotherapy smarter, one pipeline at a time."