Seyedhamidreza Mousavi

PhD student @Mälardalen University.

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I am currently a PhD student at Mälardalen University. My research has focused on the automatic design of high-performance, compact, robust, and reliable deep learning-based systems for autonomous driving.

My research interests lie in trustworthy, tiny, discriminative and generative deep learning models, with a focus on deploying them on resource-constrained devices.

news

Jun 10, 2025 Our paper got accepted to [IJCNN 2025]!(https://2025.ijcnn.org/).
Jun 04, 2025 Our presentation for the Reliability of Deep Neural Networks in TSS. Reliability of DNNs

selected publications

  1. AADAM.png
    Aadam: A fast, accurate, and versatile aging-aware cell library delay model using feed-forward neural network
    Seyed Milad Ebrahimipour, Behnam Ghavami, Hamid Mousavi, and 3 more authors
    In Proceedings of the 39th International Conference on Computer-Aided Design, 2020
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  2. TAS.png
    Tas: ternarized neural architecture search for resource-constrained edge devices
    Mohammad Loni, Hamid Mousavi, Mohammad Riazati, and 2 more authors
    In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2022
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  3. DASS.png
    DASS: differentiable architecture search for sparse neural networks
    Hamid Mousavi, Mohammad Loni, Mina Alibeigi, and 1 more author
    ACM Transactions on Embedded Computing Systems, 2023
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  4. PROACT.png
    ProAct: Progressive Training for Hybrid Clipped Activation Function to Enhance Resilience of DNNs
    Seyedhamidreza Mousavi, Mohammad Hasan Ahmadilivani, Jaan Raik, and 2 more authors
    arXiv preprint arXiv:2406.06313, 2024
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