معرفی
Mohsen Moradi is a Postdoctoral Research Associate in the Department of Electrical and Computer Engineering at Northeastern University. His research focuses on advanced coding theory, particularly in the development of Polarization-Adjusted Convolutional (PAC) codes, forward error correction, and decoding algorithms. He explores intersections between reinforcement learning and signal processing to enhance code performance.
His work emphasizes practical applications such as bounded-complexity sequential decoding, tree pruning techniques, and Monte-Carlo-based code construction. Key contributions include optimizing PAC codes through search-constrained algorithms and analyzing their performance alongside Reed-Solomon and Reed-Muller codes.
Recent publications (2020–2025) highlight trends in PAC/SC/Polar code design, with a focus on computational efficiency, metric optimization, and algorithmic innovation. His research bridges theoretical insights with real-world implementation challenges in communication systems.
Moradi’s explorations extend to hybrid coding systems (e.g., concatenated codes) and stochastic methods like guessing-based decoding. He collaborates with academic and industry partners to advance next-generation communication protocols requiring robust error correction at high data rates.
