Catalogue of Possibilities / Supervisors

Dr Ali Gooya he/him

Frontearing AI driven medical image analysis

Senior Lecturer in Machine Learning

School of Computing Science

Research interests:

Medical image analysis, Generative AI, Deep learning, Population imaging, Biomarker discovery, Vision foundation models, Multi-modal machine learning, Computational anatomy, Variational Bayes

Research fields:

AI for healthcare, Medical vision, Computer-aided diagnosis, Unsupervised/semi-supervised learning

Mission Priority Areas

Why do you want to join the DiveIn community?

I want to join the DiveIn CDT community because I am strongly motivated by its mission to foster interdisciplinary, inclusive research that makes a real-world impact. My research interests align with the CDT’s focus on combining technical innovation with societal benefit, and I am eager to collaborate with peers from diverse backgrounds to tackle complex challenges, particularly on AI applications for healthcare. I believe my background in medical image analysis and my experience in interdisciplinary research with clinicians in UoG and beyond will allow me to make a meaningful contribution to the CDT. At the same time, I am excited about the opportunity to learn, broaden my skills, and grow within a supportive and forward-thinking community.

Personal profile:

My research passion lies at the intersection of medical image analysis and artificial intelligence, where I work to empower clinicians with tools that are both accurate and interpretable. In my group, we develop AI-driven methods for robust 2D and 3D segmentation (e.g., tumour delineation, anatomical structures), uncertainty quantification, and predictive modelling to inform diagnostics and treatment planning—advancing from MRI, CT, and ultrasound data toward clinical impact. We leverage statistical rigour and deep learning innovation to ensure trustworthy outputs for healthcare professionals University of Glasgow.

I’d love to develop collaborations that bridge imaging with computational medicine, such as teaming up with the Imaging Centre of Excellence for clinical translation or the Wolfson Wohl/Precision Oncology Lab to drive oncology-related image-based assays.

I envision interdisciplinary projects that converge AI, medical imaging, statistics, and clinical practice. One such project could explore integrating uncertainty-aware segmentation with physical model-based representations for radiotherapy planning. I aim to supervise projects that balance methodological novelty with clinical utility, ideally in collaboration with engineering or clinical partners.

As a supervisor, I support mentees with intellectual autonomy, rigorous statistical grounding, and holistic professional development—encouraging interdisciplinary curiosity while grounding work in real-world impact. My former students have gone on to roles in academic research, clinical AI development teams, or interdisciplinary startups.

I am deeply committed to fostering an inclusive research environment. Through supervision of both UK and international students from various backgrounds and ethnicities, I’ve cultivated diverse teams where all voices are heard. The DiveIn CDT’s pillars of Connect, Belong and Thrive align closely with my own ethos, and I will actively promote equitable practices in recruitment, collaboration, and student support.

Beyond the lab, I’m an avid cyclist and amateur photographer—sporting long-distance trails and capturing nature through my lens. These pursuits reflect my curiosity, resilience, and appreciation for both detail and the bigger picture—qualities I bring to my research and mentorship.

https://www.gla.ac.uk/schools/computing/staff/aligooya/#