Research output per year
Research output per year
Personal profile
Research interests
My work is at the intersection of medical image analysis, machine learning, and computational neuroscience. I focus on developing novel computational methods to extract information from imaging data and delineate patterns in large heterogeneous data sets, towards improving patient-specific diagnosis and advancing our understanding of brain structure and function in health and disease. Current applications include aging and Alzheimer's Disease, as well as development and neuropsychiatric disorders.
Mentoring
Dr. Sotiras is actively looking for motivated students, postdoctoral researchers, and medical trainees interested in medical image analysis, machine learning and their applications in clinical neuroscience and neurooncology. We are dedicated to maintaining a vibrant and diverse working environment and to providing as many opportunities as possible for young trainees to pursue their scientific and professional goals.
Available to Mentor:
- Undergraduate Students
- Post-Baccalaureate Students
- PhD/MSTP Students
- Postdocs
- Residents and Fellows
Fingerprint
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Analyzing heterogeneity in Alzheimer disease using multimodal normative modeling on imaging-based ATN biomarkers
for the Alzheimer's Disease Neuroimaging Initiative, Apr 2025, In: Alzheimer's and Dementia. 21, 4, e70143.Research output: Contribution to journal › Article › peer-review
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Comparing Data-Driven Subtypes of Depression Informed by Clinical and Neuroimaging Data: A Registered Report
Hannon, K., Jarukasemkit, S., Balogh, L., Ahmad, F., Lenzini, P., Sotiras, A. & Bijsterbosch, J. D., May 2025, In: Biological Psychiatry Global Open Science. 5, 3, 100473.Research output: Contribution to journal › Article › peer-review
Open Access -
Developing approaches to incorporate donor-lung computed tomography images into machine learning models to predict severe primary graft dysfunction after lung transplantation
Ma, W., Oh, I., Luo, Y., Kumar, S., Gupta, A., Lai, A. M., Puri, V., Kreisel, D., Gelman, A. E., Nava, R., Witt, C. A., Byers, D. E., Halverson, L., Vazquez-Guillamet, R., Payne, P. R. O., Sotiras, A., Lu, H., Niazi, K., Gurcan, M. N. & Hachem, R. R. & 1 others, , Jun 2025, In: American Journal of Transplantation. 25, 6, p. 1339-1349 11 p.Research output: Contribution to journal › Article › peer-review
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DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification
Zhu, W., Chen, X., Qiu, P., Sotiras, A., Razi, A. & Wang, Y., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 333-351 19 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15096 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
5 Scopus citations -
DMC-Net: Lightweight Dynamic Multi-scale and Multi-resolution convolution network for pancreas segmentation in CT images
Yang, J., Marcus, D. S. & Sotiras, A., Nov 2025, In: Biomedical Signal Processing and Control. 109, 107896.Research output: Contribution to journal › Article › peer-review
1 Scopus citations