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Alexandru Lavric, PhD, is an Associate Professor at Faculty of Electrical Engineering and Computer Science at Ștefan cel Mare University of Suceava, Romania, where he leads research on intelligent radio spectrum management and coordinates the Wireless Lab - Complex Wireless Communications Research Group.
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His work is at the intersection of machine learning, AI, and wireless communications. Current research directions include deep learning models for real-time spectrum sensing, signal presence detection, radio transmission classification, bandwidth and SNR directly from IQ samples, as well as multi-protocol detection across LoRa, Sigfox, LTE and emerging 5G to 6G standards, jamming and interference detection with adaptive fallback strategies, and AI-native orchestration for dense IoT deployments. More recent work addresses 6G enablers: numerology inference from IQ samples, dynamic OFDM/OTFS waveform switching for high mobility scenarios, and integrated sensing and communications. This line of research started with fundamental spectrum coexistence studies in 2016 and has evolved into an adaptive AI-based spectrum sensing orchestrator.
He has authored more than 125 peer-reviewed journal and conference publications, across wireless sensor networks, LPWAN and IoT architectures, spectrum coexistence, and applied machine learning for advanced wireless communications.
Also, he is the founder of Spectrum Hive (spectrumhive.com), a startup translating this research into deployable products for advanced radio spectrum analytics and drone RF detection. The company serves telecommunications operators (e.g. Orange), IoT network operators, smart-city programmers and defense applications, providing real-time spectrum monitoring, interference mitigation and resilience against jamming. Spectrum Hive treats drone detection as a dual-use security problem in a radio environment that is not just congested but actively contested. The designed system fuses three layers: RF spectrum analysis, computer vision and acoustic sensing with AI correlating the streams to detect, classify and validate aerial targets in real time, improving both accuracy and range.
Title of the talk:
Spectrum Hive: Artificial Intelligence Radio Spectrum Sensing Algorithms for Contested Networks