Teaching

Application of Data Science to Medical Imaging (2024, 2025)

MPhil Data intesive Science (DiS), University of Cambridge

I co-created and co-lead this medical imaging course with focus on machine learning. The course focuses on Physics of the most common medical scanners (CT, PET, MRI), reconstruction of images on those scanners, medical image formats, medical image preprocessing and medical image analisys.

Image Analisys (2024, 2025)

MPhil Data intesive Science (DiS), University of Cambridge

I co-created and co-lead the Image Analysis course. This course is a foundational mathematics of imaging course, where we teach classical image processing algorithms and applications, inverse problems, sparse representations, data driven image restoration, image quality assesment and pitfalls of ML methods in imaging.

Other

During my research career I have served as teaching assistant to various courses, including Fundamentals of Computer Graphics, Intro to Machine Learning, Robotics, Python for Civil Engineers, among others.

PhD Thesis co-supervised

Christina Runkel (University of Cambridge, ongoing)
S M Ragib Shahriar Islam (Austrian Center for Medical Innovation and Technology, ongoing)
Poorya Mohammadi Nasab (Danube Private University, ongoing)

Masters Thesis Supervised

List of Masters students final projects/thesis that I have supervised. If you are interesed in doing a MSc/MPhil thesis with me, do get in contact.

MPhil Data intensive Science (DiS), University of Cambridge

2025:

Andrea Sainz Bear, “Deep Filtered Back Projection for CT Reconstruction”
Joshua Roberts, “Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction”
Sanjula Hettiarachchige, “A Neural-Network-Based Convex Regularizer for Inverse Problems”
Thanh Trung (Troy) Vu, “End-to-end reconstruction meets data-driven regularization for inverse problems”

2024:

Minwei Wang, “Deep Convolutional Neural Network for Inverse Problems in Imaging”
Alexander Lenders, “Deep Convolutional Neural Network for Inverse Problems in Imaging”
Kaixuan Xu, “Deep Convolutional Neural Network for Inverse Problems in Imaging”
Dai Wang, “Learned Primal-dual Reconstruction”
Xinyu Xinyu, “Learned Primal-dual Reconstruction”

MPhil in Computational Biology, University of Cambridge

2023:

Oliver B Coughlan, “Implementing State-of-the-Art Data-Driven Approaches to CT Image Reconstruction”

MSc Machine Learning, University of Siegen, Germany (Visiting Cambridge)