K. Foysal Haque

Foysal Haque is a Ph.D. candidate in the Department of Electrical and Computer Engineering and a member of the Institute for the Wireless Internet of Things (WIoT) at Northeastern University, USA. He received his M.S. in Computer Engineering in 2021 from Central Michigan University, USA, and his B.S. in Electrical and Electronic Engineering in 2016 from the Islamic University of Technology (IUT), Bangladesh. His research interest is in the intersection of wireless networking, embedded systems, and machine learning with a focus on integrated sensing and communication for next-generation wireless networks. He was the recipient of the best paper award in IEEE iSES 2020.

Milin Zhang

Milin Zhang is a Ph.D candidate in computer engineering in the Department of Electrical and Computer Engineering and a member of the Institute for the Wireless Internet of Things at Northeastern University. He received his M.S. in electrical engineering at Syracuse University in 2021. He received B.S. at the University of Electronic Science and Technology of China in 2018. His area of study is the integration of deep learning with cutting-edge wireless technologies, including spectrum sensing and split computing.

Shahriar Rifat

Shahriar Rifat received his B.S. degree in Electrical & Electronic Engineering with a concentration on Communication and Signal Processing in 2019. In 2019, he joined Huawei Technologies Co. Ltd. as Core System Engineer where he worked on integration of VoLTE capabilities in 4G core. From 2020 to 2022, he served as a lecturer in the Department of Electrical Engineering in Sonargaon University and Department of Computer Science & Engineering in the University of Information Technology and Sciences while persuing his M.S. degree in Department of Electrical & Electronics Engineering. His master’s thesis was focused on ultrasound image super resolution. He started his Ph.D. in 2022 under the guidance of Professor Francesco Restuccia at Northeastern University, Boston, MA, USA. His Ph.D. research focuses on inference time dynamic Adaptation of Neural Networks in resource-constrained edge computing systems.

Andrew Ashdown

Andrew Ashdown is a graduate student at Northeastern University. He holds an A.S. in Engineering Science from Hudson Valley Community College and a B.S. in Electrical Engineering from Stony Brook University. His graduate research is focused primarily on 5G cellular technologies, including TCP congestion control, spectral measurement and analysis studies, etc. and his research interests largely fall in these areas. He is currently in collaboration with the AFRL (Air Force Research Labs) and other researchers from Northeastern, and is pursuing graduate coursework as well on topics such as Edge Computing, THz Communications, and the Internet of Things. He is a recipient of the 2024 NDSEG PhD fellowship by the Department of Defense.

Mohammad Abdi

Mohammad Abdi received his B.S. degree from Shiraz University (Pahlavi) in Electrical and Computer Engineering with the highest honors, and his concentration was in Control, Optimization, and Signal Processing. In 2016, he started his M.S. program in Telecommunications Engineering under the supervision of Prof. Abbas Sheikhi and Prof. Mahmoud Farhang, working on the analysis, design, and development of Doppler-shifted interference signal cancellation algorithms using adaptive filters. His master’s thesis investigates novel solutions for dynamic and moving clutter rejection in passive radar systems. He is currently pursuing his Ph.D. under the guidance of Prof. Francesco Restuccia at Northeastern University, Boston, USA. His research interests include Embedded Systems, Wireless Communication Systems, and Artificial Intelligence. His research in the lab focuses on Efficient AI enabling the deployment of ML models to resource-constrained IoT devices.

Tanzil Bin Hassan

Tanzil Bin Hassan earned his Bachelor’s degree in Electrical and Electronic Engineering from the Islamic University of Technology, Bangladesh. With a background in the telco industry, he is currently engaged in pursuing his Ph.D. in the ECE department at Northeastern University. His research focuses on Open Radio Access Network and the application of AI/ML in the context of 5G and Beyond.

Sazzad Sayyed

A. Q. M Sazzad Sayyed received his B.Sc.(Engg.) degree from Bangladesh University of Engineering and Technology, Bangladesh, in 2018. He is pursuing a Ph.D. in electrical engineering with the Institute for Wireless IoT, Northeastern University. He is under direct supervision of Dr. Francesco Restuccia. His research interests include machine learning, dynamic neural network design and embedded deep learning for wireless networks.

K.M. Rumman

K M Rumman is a Ph.D. student in the Department of Electrical and Computer Engineering and a member of the Institute for the Wireless Internet of Things (WIoT) at Northeastern University, USA. He completed his M.S. in Applied Statistics and Data Science in 2023 from Jahangirnagar University (JU), Bangladesh and his B.S. in Electrical and Electronic Engineering in 2016 from Islamic University of Technology (IUT), Bangladesh. His focus is on performing research at the convergence of wireless networking, embedded systems and machine learning.

Francesco Pessia

Francesco Pessia is a Ph.D. student in the Department of Electrical and Computer Engineering and a member of the Institute for the Wireless Internet of Things (WIoT) at Northeastern University, USA. He received his M.S. and B.S. in Computer Engineering from Politecnico di Torino, Italy. His research interest is in embedded systems and FPGA design.

Arman Elyasi

Arman has completed his B.Sc. in Electrical Engineering at Amirkabir University of Technology with a research focus in IoT, Embedded Systems, FPGA Developing, AI/ML, Image Processing and Biomedical Signal Processing. His current research interest lies in embedded AI/ML for next-generation mobile systems.