معرفی
Sneha Kasera is a Researcher at the University of Utah's Department of Computer Science, affiliated with the University of Utah. Her work focuses on wireless communications, networking, and signal processing, with an emphasis on spectrum management, machine learning applications in networks, and security. She has contributed extensively to projects like the POWDER platform for wireless experimentation and spectrum analysis.
Her research interests include developing advanced techniques for spectrum monitoring, dynamic radio resource allocation, and leveraging machine learning for network optimization. Key projects include Radio Dynamic Zones (RDZ) for efficient spectrum utilization and Bayesian learning methods for heatmap construction in outdoor wireless environments.
Her recent work explores multi-agent reinforcement learning for mmWave power allocation, adversarial attacks on localization systems, and privacy-preserving exposure notification via hash collision techniques. She has also pioneered methods for crowdsourced spectrum monitoring and calibration-free full-duplex systems.
Collaborations include contributions to the POWDER platform, which enables scalable wireless research. Her technical expertise spans hardware-software integration, network security, and algorithm design for 5G/6G systems.
