Dr Mohammad Dehshibi
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Role:
Department staff:
Collaborations:
- Fungal Architectures (FUNGAR) EU H2020 FET-Open Project
- Unconventional Computing Laboratory
- BODYinTRANSIT ERC Project
- Universidad Carlos III de Madrid
- i_mBODY Laboratory
- Universitat Oberta Catalunya
- European Laboratory for Learning and Intelligent Systems (ELLIS)
- COgITOR EU H2020 FET-Open Project
- Bellvitge University Hospital
- Radboud University
- UCL Interaction Centre
- International Journal of Parallel, Emergent and Distributed Systems
Research staff:
- Deep Learning
- Affective Computing
- AI in Medicine
- Unconventional Computing
- Explainable AI (XAI)
- Observational AI
- Machine Learning
- Computer Vision
- Medical Data Analysis
- Biological Signal Processing
Teaching staff:
- Qualifications:
- PhD in Systems Software Engineering / AI, 2017
- Position:
- Research Fellow
- Department:
- FET - Computer Science and Creative Technologies
- Social media:
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About me
Established (R3) multidisciplinary AI researcher, IEEE Senior Member, and ELLIS Member. My research focuses on two areas: (1) developing robust, explainable, and human-centered AI systems, and (2) unconventional computing and bio-inspired computation.
Research topics:
§ Deep Learning
§ Computer vision
§ Explainable AI (XAI)
§ AI in Medicine
§ Unconventional Computing
§ Affective Computing
Supervision:
PhD and master’s theses in medical data analysis, affective computing, and explainable AI, with support for students to address real-world, data-driven problems and to engage in interdisciplinary collaborations.
Publication’s note:
Updated publications and citation metrics are available on Google Scholar. More details are accessible in my ORCID and ResearcherID profiles.
Area of expertise
My expertise spans deep learning, machine learning, computer vision, and the analysis of complex medical and biological data. I have a particular interest in affective computing, observational AI, and explainable AI (XAI), with applications in healthcare, human-computer interaction (HCI), and adaptive intelligent systems. I also contribute to emerging research at the boundary of AI and unconventional computing, exploring novel substrates and architectures for computation.
Publications
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