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Dr. Sari Saba-Sadiya

Dr. Sari Saba-Sadiya

Principal Investigator

Dr. Sari Sadiya is a machine learning researcher working at the intersection of computer vision, bioinformatics, and cognitive neuroscience. His research focuses on biological signal processing, model–brain alignment, and robustness. He holds a dual PhD in Computer Science and Cognitive Neuroscience from Michigan State University and has published extensively in leading AI and neuroscience venues.

Awards: Fulbright Scholarship, Dissertation Completion Fellowship, Michigan State University

Key achievements: Lead-PI of the 2025 Hessian.AI Research Grant “Cognitive Neural Systems Architecture Search”, Author of 30+ publications in AI, computer vision, and computational neuroscience.

Industry collaborations and partnerships: Consulted for various AI startups (most recently Deriva.ai), Former Engineer at Apple.

Email: Sari.Sadiya@constructor.org
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Research Portfolio

Dr. Sari Saba-Sadiya’s work leverages state-of-the-art machine learning techniques for biological signal analysis. His toolbox includes model–brain alignment, neural architecture search, transfer-learning (such as feature imitating and prior fitted networks), and interpretability techniques.

At Goethe University Frankfurt, Dr. Sari Saba-Sadiya lead the Hessian.AI-funded project Cognitive Neural Architecture Search, exploring how principles of brain organization can improve the design of artificial neural networks. His work has resulted in 20+ publications across AI, neuroscience, and biomedical applications, alongside collaborations with various industry partners including Honda and Deriva.ai.

Dr. Sari Saba-Sadiya is also committed to education and outreach through teaching, student mentorship, and online learning. He is a project director at the Refugee Outreach Collective’s Global Classroom initiative, which expands access to accredited online education for learners in displacement settings. These experiences inform his interest in educational technologies and the broader societal impact of AI.

Applied AI & Software Engineering:

  • L. Kuhn*, S. Sadiya*, J. Schlotterer, F. Buttner, C. Seifert, G. Roig. Efficient unsupervised shortcut learning detection and mitigation in transformers. In Proceedings of the 2025 International Conference on Computer Vision (ICCV 2025)
  • S. Sadiya, T. Alhanai, M. Ghassemi; Feature Imitating Networks. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022).


Neuroscience & Neuropsychology:

  • M. Menceloglu*, S. Sadiya*, E. Chantland, M. Ghassemi, S. Revizza, T. Liu; Limits of attention to multiple colors revealed by EEG decoding. In Imaging Neuroscience (2025)
  • D. Bersch, M. Vilas, S. Sadiya, T. Schaumloffel, K. Dwivedi, C. Sartzetaki, R. Cichy, G. Roig. Net2Brain: A Toolbox to Compare Artificial Vision Models with Human Brain Responses. In Frontiers in Neuroinformatics Volume 19 (2025)
  • T. Ettling*, S. Sadiya*, G. Roig; Different Algorithms (Might) Uncover Different Patterns: A Brain-Age Prediction Case Study. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (Oral BIBM 2023)
  • T. Liu, M. Fang, S. Sadiya; Adaptive visual selection in feature space. Psychonomic Bulletin & Review (2022)
  • S. Sadiya, T. Alhanai, T. Liu, M. Ghassemi; EEG Channel Interpolation Using Deep Encoder-decoder Networks. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2020).


Learning Sciences & Cognitive Psychology:

  • A. Burgoyne, S. Sadiya, L. Harris, M. Becker, J. Brascamp, D. Hambrick; Revisiting the Self-Generation Effect in Proofreading. In Psychological Research: Journal of Perception, Attention, Memory, and Action (2023)