H. Daoud and M. Bayoumi, "Deep Learning Approach for Epileptic Focus Localization," in IEEE Transactions on Biomedical Circuits and Systems, vol. 14, no. 2, pp. 209-220, April 2020.

I. K. Dutta, B. Ghosh, A. H. Carlson, and M. Bayoumi, “Lightweight Polymorphic Encryption for the Data Associated with Constrained Internet of Things Devices” 2020 IEEE 6th World Forum on Internet of Things (WF-IoT)

P. Williams, I. K. Dutta, Hisham Daoud, and M. Bayoumi, “Security Aspects in Internet of Things – A Survey” 2020 IEEE 6th World Forum on Internet of Things (WF-IoT)

B. Ghosh, I.K. Dutta, M. Totaro, M. Bayoumi, “A survey on the progression and Performance of Generative Adversarial Networks” 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT)

Omar Eldash, Adam Frost, Kasem Khalil, Ashok Kumar, Magdy Bayoumi. Dynamically Recon-figurable Deep Learning for Efficient Video Processing in Smart IoT Systems In 6th IEEE WorldForum on Internet of Things (WFIoT), IEEE,2020

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”Intelligent Fault-PredictionAssisted Self-Healing for Embryonic Hardware.” IEEE Transactions on Biomedical Circuits andSystems (2020).

Haytham Idriss, Tarek Idriss, Phillip Williams, Magdy A Bayoumi “Memory-based Arbiter PUF: A Novel Highly Reliable and Scalable Strong PUF Design”, 2020 IEEE 6th World Forum on Internet of Things

Pablo Rojas, Haytham Idriss, Magdy Bayoumi, “Comparative Analysis on the Scaling Properties of Arbiter-Based PUFs”, 2020 IEEE 6th World Forum on Internet of Things

H. Idriss, T. Idriss, P. Williams, and M. Bayoumi, Memory-based Arbiter PUF: A Novel Highly Reliable and Scalable Strong PUF Design. 6th IEEE Virtual World Forum on the Internet of Things (WF-IoT), 2020.

H. Daoud, P. Williams, and M. Bayoumi, IoT based Efficient Epileptic Seizure Prediction System Using Deep Learning. 6th IEEE Virtual World Forum on the Internet of Things (WF-IoT), 2020.

A. M. Abdelhameed and M. Bayoumi, “Semi-Supervised EEG Signals Classification System for Epileptic Seizure Detection,” IEEE Signal Processing Letters, vol. 26, no. 12, pp. 1922 1926, 2019.

H. Daoud and M. Bayoumi, "Semi-supervised Learning for Epileptic Focus Localization Using Deep Convolutional Autoencoder," in Proc. of IEEE Biomedical Circuits and Systems Conference (BioCAS), Nara, Japan, 2019.

H. Daoud and M. A. Bayoumi, “Efficient Epileptic Seizure Prediction based on Deep Learning,” in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 5, pp. 804-813, Oct. 2019.

I. K. Dutta, B. Ghosh, and M. Bayoumi, “Lightweight Cryptography for Internet of Insecure Things : A Survey” 2019 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC)

Khalil, Kasem, Omar Eldash, Bappaditya Dey, Ashok Kumar, and Magdy Bayoumi. ”A NovelReconfigurable Hardware Architecture of Neural Network.” In 2019 IEEE 62nd International Mid-west Symposium on Circuits and Systems (MWSCAS), pp. 618-621. IEEE, 2019.

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”N 2 OC: Neural-Network-on-Chip Architecture.” In 2019 32nd IEEE International System-on-Chip Conference (SOCC), pp.272-277. IEEE, 2019.

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”Self-healing hardware sys-tems: A review.” Microelectronics Journal (2019): 104620.

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”Economic LSTM Approachfor Recurrent Neural Networks.” IEEE Transactions on Circuits and Systems II: Express Briefs(2019).

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”A Speed and Energy FocusedFramework for Dynamic Hardware Reconfiguration.” In 2019 32nd IEEE International System-on-Chip Conference (SOCC), pp. 388-393. IEEE, 2019.

P. Williams, P. Rojas, and M. Bayoumi, Security Taxonomy in IoT – A Survey, 62nd IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2019.

A. M. Abdelhameed and M. Bayoumi, “Semi-Supervised Deep Learning System for Epileptic Seizures Onset Prediction,” 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018.

A. M. Abdelhameed, H. G. Daoud, and M. Bayoumi, “Epileptic Seizure Detection using Deep Convolutional Autoencoder,” 2018 IEEE International Workshop on Signal Processing Systems (SiPS), 2018.

H. G. Daoud, A. M. Abdelhameed, and M. Bayoumi, “FPGA Implementation of High Accuracy Automatic Epileptic Seizure Detection System,” 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS), 2018.

A. M. Abdelhameed, H. G. Daoud, and M. Bayoumi, “Deep Convolutional Bidirectional LSTM Recurrent Neural Network for Epileptic Seizure Detection,” 2018 16th IEEE International New Circuits and Systems Conference (NEWCAS), 2018

H. G. Daoud, A. M. Abdelhameed, and M. Bayoumi, “Automatic epileptic seizure detection based on empirical mode decomposition and deep neural network,” 2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA), 2018.

H. Daoud and M. A. Bayoumi, “Deep Learning based Reliable Early Epileptic Seizure Predictor,” in Proc. of IEEE Biomedical Circuits and Systems Conference (BioCAS), Cleveland, OH, USA, 2018.

S. Madani, M. R. Madani, I. K. Dutta, Y. Joshi, and M. Bayoumi, “A Hardware Obfuscation Technique for Manufacturing a Secure 3D IC” 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS)

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”An Efficient Approach forNeural Network Architecture.” In 2018 25th IEEE International Conference on Electronics, Cir-cuits and Systems (ICECS), pp. 745-748. IEEE, 2018.

Khalil, Kasem, Omar Eldash, Ashok Kumar, and Magdy Bayoumi. ”Flexible Self-Healing Routerfor Reliable and High-Performance Network-on-Chips Architecture.” In 2018 31st IEEE Interna-tional System-on-Chip Conference (SOCC), pp. 152-157. IEEE, 2018.

Khalil, Kasem, Omar Eldash, and Magdy Bayoumi. ”A cost-effective self-healing approach forreliable hardware systems.” In 2018 IEEE International Symposium on Circuits and Systems(ISCAS), pp. 1-5. IEEE, 2018.