Ahmad Bazzi
Research Scientist
Affiliation: NYU Abu Dhabi
Education: PhD, EURECOM, France
Research Websites: NYUAD Wireless Research Lab
Research Areas: Integrated Sensing and Communications; Wireless Communications; Signal Processing; Optimization; Statistics; Artificial Intelligence
Ahmad Bazzi was born in Abu Dhabi, United Arab Emirates. He received his PhD degree in electrical engineering from EURECOM, Sophia Antipolis, France, in 2017. and the MSc degree (summa cum laude) in wireless communication systems (SAR) from the Centrale Supélec, in 2014. Bazzi is currently a research scientist in the Wireless Research Lab, and NYU WIRELESS, NYU Tandon School of Engineering, contributing to integrated sensing and communications (ISAC). Prior to that, he was the Algorithm and Signal Processing Team Leader at CEVA-DSP, Sophia Antipolis, leading the work on Wi-Fi (802.11ax) and Bluetooth (5.xx BR/BLE/BTDM/LR) high-performant (HP) PHY modems, OFDMA MAC schedulers, and RF-related issues. He is an inventor with several patents involving intellectual property of Wi-Fi and Bluetooth products, all of which have been implemented and sold to key clients.
Since 2018, he has published YouTube lectures under his name "Ahmad Bazzi," where his channel contains mathematical, algorithmic, and programming topics, with over 270,000 subscribers and more than 17 million views, as of November 2024. He was awarded a CIFRE Scholarship from the Association Nationale Recherche Technologies (ANRT) France, in 2014, in collaboration with RivieraWaves (now CEVA-DSP). He was nominated for Best Student Paper Award at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2016. He received the Silver Plate Creator Award from YouTube in 2022 for his 100,000-subscriber milestone.
Bazzi was awarded an exemplary reviewer for the IEEE Transactions on Communications in 2022 and an exemplary reviewer for the IEEE Wireless Communications Letters in 2022. He served as technical program committee (TPC) member and a reviewer for many leading international conferences. He was selected among the 200 Top Arab Creators for 2023. He serves as an editor of the IEEE Communications Letters, 2025-2026, and the IEEE Open Journal of the Communications Society (OJ-COMS), 2025-2026. He also serves as a guest editor for the IEEE Open Journal of the Communications Society (OJ-COMS) special issue on “Resilient and Trustworthy Communications for 6G Wireless Environments: Integrating Sensing, AI, and Security in Smart Wireless Systems”, 2026. His research interests include signal processing, wireless communications, artificial intelligence, statistics, and optimization.
Current Research
Waveform Design for Integrated Sensing and Communications (ISAC) 6G Systems
6G is intended to foster a wide scope of services, spanning haptic telemedicine to VR/AR remote services and holographic teleportation with massive eXtended reality (XR) capabilities, as well as Blockchain, just to name a few. Therefore, 6G will go beyond communications, thanks to a key feature that is ISAC. Indeed, ISAC cooperation and convergence is an utmost topic that will serve as a door-opener for innovative applications in several domains such as the automotive sector, UAV sector, and robotics. Spectrum efficiency is one of the major virtues of ISAC, as the dynamics of sensing and communication can be “buckled up” within the same resource. An additional advantage is hardware resource sharing between radar and communication tasks, thus having both sensing and communication on a single platform will lead to reduced PHY-layer modem size and cost. All these merits give rise to a serious number of challenges and research questions that need to be addressed, such as efficient resource reuse and spectrum sharing, trade-offs between high communication rates and high-resolution sensing performances, privacy and security, and shared waveform design from a practical standpoint. In this project, we focus on practical waveform design, which puts forward dual-functional radar and communication base stations at the forefront of future 6G cellular networks. The main essence lies in providing efficient algorithms and designs through suitable optimization frameworks, enabling fruitful trade-offs, given the conflicting natures of the sensing and communication objectives. Even more, these methods should adapt to model uncertainties, such as situations with imperfect channel state information, and hardware imperfections, such as high power amplifier considerations.