Mohamed Akrout

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For a complete and up-to-date list, please see my Google Scholar profile.

Akrout, M., Cirone, K., Vender, R. Evaluation of vision LLMs GTP-4V and LLaVA for the Recognition of Features Characteristic of Melanoma, accepted to Journal of Cutaneous Medicine and Surgery (to be published soon).
Akrout, M., Gyepesi, B., Holló, P., Poór, A., Kincső, B., Solis, S., Cirone, K., Kawahara, J., Slade, D., Abid, L., Kovács, M., Fazekas, I. Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images, MICCAI Deep Generative Models workshop, 2023.
Akrout, M., Farahmand, A.M., Jarmain, T., Abid, L. Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning. MICCAI, 2019.
Akrout, M., Wilson, C., Humphreys, P., Lillicrap, T., and Tweed, D. B. Deep Learning without Weight Transport. Advances in Neural Information Processing Systems (NeurIPS), 2019.
Akrout, M., Farahmand, A., Jarmain, T. Improving Skin Condition Classification with a Question Answering Model. Medical Imaging meets NeurIPS Workshop, 2018.

Akrout, M., Bellili, F., Mezghani, A., and Nossek, J. A. Physically Consistent Models for Intelligent Reflective Surface-assisted Communications under Mutual Coupling and Element Size Constraint, IEEE Asilomar Conference on Signals, Systems & Computers, 2023.
Akrout, M., Shyianov, V., Bellili, F., Mezghani, A., and Heath., R. W. Bandwidth Gain: the Missing Gain of Massive MIMO. IEEE International Conference on Communications, 2023.
Akrout, M., Shyianov, V., Bellili, F., Mezghani, A., and Heath., R. W. Super-Wideband Massive MIMO. IEEE JSAC special issue on Beyond Shannon Communications: A Paradigm Shift to Catalyze 6G, 2023.
Akrout, M., Shyianov, V., Bellili, F., Mezghani, A., and Heath., R. W. Achievable Rate of Near-Field Communications Based on Physically Consistent Models. IEEE Transactions on Wireless Communications, 2022.
Akrout, M.*, Shyianov, V*., Bellili, F., Mezghani, A., and Heath., R. W. (* for joint first co-authorship) Achievable Rate with Antenna Size Constraint: Shannon meets Chu and Bode. IEEE Transactions on Communications, 2021.

Akrout, M., Feriani, A., Bellili, F., Mezghani, A., Hossain, E. Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues, IEEE Communications Surveys & Tutorials, 2023.
Akrout, M., Feriani, A., Bellili, F., Mezghani, A., Hossain, E. Continual Learning-Based MIMO Channel Estimation: A Benchmarking Study. IEEE International Conference on Communications, 2023.
Fredj, F., Al-Eryani, Y., Maghsudi, S., Akrout, M., and Hossain, E. Distributed Beamforming Techniques for Cell-Free Wireless Networks Using Deep Reinforcement Learning. IEEE Transactions on Cognitive Communications and Networking, 2022.
Al-Eryani, Y., Akrout, M., and Hossain, E. Multiple Access in Cell Free Networks: Outage Performance, Dynamic Clustering, and Deep Reinforcement Learning based Design. IEEE Journal on Selected Areas in Communications, 2021.
Al-Eryani, Y., Akrout, M., and Hossain, E. Antenna Clustering for Simultaneous Wireless Information and Power Transfer in a MIMO Full-duplex System: A Deep Reinforcement Learning-based Design. IEEE Transactions on Communications, 2021.

Akrout, M., Amdouni, H., Feriani, A., Kourda, M., Abid, L. A 35-Year Longitudinal Analysis of Dermatology Patient Behavior across Economic & Cultural Manifestations in Tunisia, and the Impact of Digital Tools. MICCAI Workshop on Ethical and Philosophical Issues in Medical Imaging (EPIMI), 2022.
Akrout, M., Feriani, A., McLeod, B. Dynamic Noises of Multi-agent Environments can Improve Generalization: Agent-based Models Meet Reinforcement Learning. Gamification and Multiagent Solutions Workshop at ICLR 2022.
Akrout, M.. On the Adversarial Robustness of Neural Networks without Weight Transport. Real Neurons & Hidden Units Workshop at NeurIPS 2019.
Zhu, H., Akrout, M., Zheng, B., Pelegris, A., Jayarajan, A., Phanishayee, A., Schroeder, B. and Pekhimenko, G. Benchmarking and Analyzing Deep Neural Network Training. IEEE International Symposium on Workload Characterization (IISWC), 2018.

Abid, L., Sanfiz, A. J., Lopez, A. R., Jarmain, E. T., Akrout, M., Challa, A., Kawahara, J. G., Solis-Reyes, S. A. System to collect and identify medical conditions from images and expert knowledge.