Amin Aminifar, Jonathan Dan, David Atienza. “Federated Learning with Patient-Annotated Data in Epileptic Seizure Detection.” In International Joint Conference on Neural Networks (IJCNN), 2025.
Anahita Baninajjar, Amin Aminifar, Kamran Hosseini, Amir Aminifar, Ahmed Rezine. “Robustness and Privacy Interplay in Patient Membership Inference.” In International Joint Conference on Neural Networks (IJCNN), 2025.
Fatemeh Akbarian, Robbe Vlaeminck, Joran Verheijen, Amin Aminifar, Amir Aminifar. “Federated Learning for Obstacle Detection to Assist the Visually-Impaired Using Augmented Reality.” In 28th Euromicro Conference on Digital System Design (DSD), 2025.
Soheil Khooyooz, Vimala Bauer, Anice Jahanjoo, Mostafa Haghi, Amin Aminifar, Nima TaheriNejad. “IDNoise: Resource-Aware Machine Learning-Based Noise and SNR Detection in Electrocardiogram Signals.” In 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025.
Published
Amin Aminifar, Matin Shokri, Amir Aminifar. “Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems.” In Future Generation Computer Systems (Impact Factor: 6.1), 2024. | Publisher Link
Amin Aminifar, Baichuan Huang, Azra Abtahi, Amir Aminifar. “LightFF: Lightweight Inference for Forward-Forward Algorithm.” In 27th European Conference on Artificial Intelligence (Acceptance Rate: 23%), 2024. | Publisher Link
Amin Aminifar, Khooyooz, Soheil, Jahanjoo, Anice, Shakibhamedan, Salar, TaheriNejad, Nima. “RecogNoise: Machine-Learning-Based Recognition of Noisy Segments in Electrocardiogram Signals.” IEEE International Symposium on Circuits and Systems (ISCAS), 2024. | Publisher Link
Abtahi, Azra, Amin Aminifar, Amir Aminifar. “Privacy-Preserving Federated Interpretability.” In IEEE International Conference on Big Data (BigData), 2024. Publisher Link
Shakibhamedan, Salar, Amin Aminifar and Luke Vassallo and Nima TaheriNejad. “Harnessing Approximate Computing for Machine Learning.” IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2024.
Khooyooz, Soheil, Jahanjoo, Anice, Amin Aminifar, TaheriNejad, Nima. “A Novel Machine-Learning-Based Noise Detection Method for Photoplethysmography Signals.” 2024 46th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2024.
Jahanjoo, Anice, TaheriNejad, Nima, Amin Aminifar. “High-Accuracy Stress Detection Using Wrist-Worn PPG Sensors.” IEEE International Symposium on Circuits and Systems (ISCAS), 2024.
Shakibhamedan, Salar, Anice Jahanjoo, Amin Aminifar, Nima Amirafshar, Nima TaheriNejad, Axel Jantsch. “An Analytical Approach to Enhancing DNN Efficiency and Accuracy Using Approximate Multiplication” Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ICML), 2024.
Amin Aminifar, Shokri, Matin, Rabbi, Fazle, Pun, Violet Ka I, Lamo, Yngve. “Extremely Randomized Trees With Privacy Preservation for Distributed Structured Health Data.” IEEE Access, 2022. | Publisher Link
Amin Aminifar. “Privacy-Preserving Machine Learning and Data Sharing in Healthcare Applications.” Ph.D. Thesis, 2022. | Publisher Link
Lamo, Yngve, et al. “Towards adaptive technology in routine mental health care.” DIGITAL HEALTH, 2022.
Amin Aminifar, Rabbi, Fazle, Pun, Ka I, Lamo, Yngve. “Privacy preserving distributed extremely randomized trees.” Proceedings of the 36th Annual ACM Symposium on Applied Computing (SAC), 2021. | Publisher Link
Amin Aminifar, Rabbi, Fazle, Lamo, Yngve. “Scalable Privacy-Preserving Distributed Extremely Randomized Trees for Structured Data With Multiple Colluding Parties.” ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. | Publisher Link
Amin Aminifar, Rabbi, Fazle, Pun, Violet Ka I, Lamo, Yngve. “Diversity-Aware Anonymization for Structured Health Data.” 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021. | Publisher Link
Amin Aminifar, Rabbi, Fazle, Pun, Violet Ka I, Lamo, Yngve. “Monitoring Motor Activity Data for Detecting Patients’ Depression Using Data Augmentation and Privacy-Preserving Distributed Learning.” 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021. | Publisher Link
Forooghifar, Farnaz, Amin Aminifar, Teijeiro, Tomas, Aminifar, Amir, Jeppesen, Jesper, Beniczky, Sandor, Atienza, David. “Self-Aware Anomaly-Detection for Epilepsy Monitoring on Low-Power Wearable Electrocardiographic Devices.” 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021. Publisher Link
Nordgreen, Tine, et al. “Challenges and possible solutions in cross-disciplinary and cross-sectorial research teams within the domain of e-mental health.” Journal of Enabling Technologies, 2021.
Mukhiya, Suresh Kumar, Amin Aminifar, Rabbi, Fazle, Pun, Violet Ka I, Lamo, Yngve. “Artificial Intelligence in Mental Health.” Artificial Intelligence: Models, Algorithms and Applications, 2021.
Amin Aminifar, Lamo, Yngve, Pun, Ka I, Rabbi, Fazle. “A Practical Methodology for Anonymization of Structured Health Data.” 2019 17th Scandinavian Conference on Health Informatics (SHI), 2019.
Shokri, Matin, Khasteh, Seyed Hossein, Amin Aminifar. “Adaptive Fuzzy Watkins: A New Adaptive Approach for Eligibility Traces in Reinforcement Learning.” International Journal of Fuzzy Systems, 2019. Publisher Link
Sopic, Dionisije, Amin Aminifar, Aminifar, Amir, Atienza, David. “Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems.” IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), 2018. Publisher Link
Sopic, Dionisije, Amin Aminifar, Aminifar, Amir, Atienza, David. “Real-time classification technique for early detection and prevention of myocardial infarction on wearable devices.” 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2017. Publisher Link
Shakibhamedan, Salar, Amin Aminifar, Nima Taherinejad, Axel Jantsch. “EASE: Energy Optimization through Adaptation – A Review of Runtime Energy-Aware Approximate Deep Learning Algorithms.” TechRxiv, 2024. DOI: 10.36227/techrxiv.170723230.09169589/v1
Traunmueller, Peter, Anice Jahanjoo, Soheil Khooyooz, Amin Aminifar, Nima TaheriNejad. “Wearable Healthcare Devices for Monitoring Stress and Concentration Level in Workplace Environments.” arXiv 2406.05813, 2024.
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