Dr Ali Gooya
I joined the University of Leeds as a Lecturer in the September 2018. I obtained an MSc in Bioelectric Engineering from Tehran University and a PhD in Information Science from the University of Tokyo, supported by a Japanese Monbusho scholarship. In 2008, I was awarded a post-doctoral fellowship by Japan Society of Promotion of Science and shortly after, I moved to the University of Pennsylvania, USA, and worked on tumor image analysis till 2011. Subsequently, I served as an Assistant Professor at Tarbiat Modares University, Tehran. In 2014, I was awarded an IIF Marie-Curie Fellowship for statistical modeling of morphology and function of the heart in the University of Sheffield, where I was promoted to a Lecturer in the department of EEE prior to joining Leeds.
Positions - I have funded positions for one PDRA and three international PhD students. If you have got the stamina to work within a world leading image computational group, and have the track record to innovate useful tools or contribute to the state-of-the-art, please contact me.
My research interest includes probabilistic machine and deep learning, variational Bayesian inference, graphical models, and medical image computing. I have a particular expertise in population imaging studies, generative models for shape and motion atlases, and computational tumor image analysis.
Software and Tools - I have developed multiple tools that are available for free academic use. If you use them, please cite the corresponding references. I would be very thankful!
- GLISTR: Glioma Image Segmentation and Registration, Model Personalization (IEEE TMI, 2012)
- Variational Bayesian Mixture of Probabilistic PCA for Shapes from Point Sets (IEEE TPAMI, 2018)
- Group Wise Point Set Registration and Statistical Shape Modeling (SIAM, 2015)
- BSc (University of Science and Technology, Iran)
- MSc (University of Tehran, Iran)
- PhD (University of Tokyo, Japan)
- PGCert (University of Sheffield, UK)
- Member, IEEE
- Marie-Curie IIF Research Fellow (Alumni)
- Fellow, Higher Education Academy
- Member, MICCAI Society
I will be focusing on Machine Learning and Artifical Intelligence.
Postgraduate research opportunities
We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study.
Projects currently available:
- Bayesian Deep Atlases for Cardiac Motion Abnormality Detection from Imaging and Metadata
- Deep learning for early detection of cancer recurrence in patients with glioblastoma through imaging
- Deep learning for outcome prediction after pelvic radiotherapy