About Me

I’m Ali Rasteh, a Ph.D. candidate in Electrical and Computer Engineering at New York University (NYU), with a specialization in Wireless Communications, Applied Machine Learning, and Hardware Design. Before starting my Ph.D. at NYU, I completed my Bachelor’s and Master’s degrees in Electrical Engineering at Sharif University of Technology (Tehran, Iran), where I specialized in electronics and developed foundational skills in Integrated circuit design and applied research. Through my work at NYU Wireless, I lead and contribute to research that pushes the boundaries of wireless spectrum sensing, FR3 channel modeling, and efficient hardware for spectrum analysis. My role as a Research Assistant has given me the opportunity to engage in advanced projects, developing complex algorithms and hardware systems that enable the next generation of wireless technologies.

With extensive hands-on experience in both academia and industry, I bring a unique blend of research-driven insights and real-world engineering skills. Before joining NYU, I led hardware and software projects at Sina Communication Systems Co., where I oversaw the development of critical telecommunications network infrastructure, including GPON OLT systems, aggregation/access routers, and POTN DWDM systems. My industry background has strengthened my skills in managing cross-functional teams, from hardware and FPGA design to embedded software and full-stack development. Additionally, my time at Sina Co. deepened my knowledge of hardware and FPGA design as well as communication networks. Concurrently, I pursued research in Machine Learning and Spiking Neural Networks as a member of French National Centre for Scientific Research (CNRS).

Alongside my research, I have a deep commitment to advancing technology through innovation. I am proficient in a range of programming languages, AI/ML tools and frameworks, hardware description languages, and FPGA EDA tools, allowing me to develop scalable solutions in telecommunications and beyond. My work has been published in leading conferences and journals, and I continue to explore projects that merge cutting-edge technology with practical applications, including my recent endeavors in FR3 wireless communication systems.

Through this website, I aim to share insights from my research, updates on ongoing projects, and resources for those interested in wireless communications, communication networks, and applied machine learning. Thank you for visiting, and feel free to connect with me on LinkedIn or explore my GitHub for a closer look at my work.