I’m currently a research scholar in the AIM program housed at Mass General Brigham and Harvard Medical School focusing on generalizable and scalable deep learning to develop biomarkers for precision care in oncology. I’m also in the 3rd year of my PhD program at the GROW School for Oncology and Reproduction @ Maastricht University advised by Prof. Hugo Aerts.

Amidst the pandemic, I graduated cum laude with a MSc in Artificial Intelligence from the Department of Advanced Computing Sciences at Maastricht University and worked on AI-assisted radiotherapy at MAASTRO Clinic. I come from an engineering background (Bachelors in Electronics and Comms Engg.) with skills honed through freelancing and roles at several startups.

With my experiences, I hope to build AI and engineering systems that can benefit medical care.

Whenever I get a chance, I enjoy spending time in nature (New England is a birders paradise) and digging deeper into topics in metaphysics, ethics, epistemology and world history.

 

🔥 News

  • 2024.05:  🎖️ Our challenge won ‘Best in Physics’ award at ESTRO2024
  • 2024.03:  🎉📝 Our paper on foundation models for cancer imaging biomarkers was published in Nature Machine Intelligence
  • 2022.02:  🎉📊 Our paper on design choices for CycleGANs in CBCT to CT translation will be presented at SPIE in San Diego by Ibrahim

 

📝 Publications

Representation Learning in Oncology

  • Nature Machine Intelligence Foundation Model for Cancer Imaging Biomarkers Suraj Pai, Dennis Bontempi, Ibrahim Hadzic, Vasco Prudente, Mateo Sokač, Tafadzwa L. Chaunzwa, Simon Bernatz, Ahmed Hosny, Raymond H. Mak, Nicolai J. Birkbak & Hugo J. W. L. Aerts

Image-to-Image translation for Medical Imaging

3D Segmentation for Radiology applications

Open-science through datasets, challenges and tools.

 

💬 Invited Talks

 

👍🏼 Miscellaneous

  • Reviewer for npj Breast Cancer, Nature Scientific Reports, JOSS.
  • Awarded Brigham Research Institute Microgrant