Tao Li

Tao Li's research focuses on security and privacy for wireless sensing and Internet-of-Things (IoT) devices, including attacks and defenses for systems that use radar (mmWave), motion sensors, and machine learning models. Recent work examines how deep learning systems (including federated learning, where multiple devices jointly train a model without sharing raw data) can be attacked with hidden 'backdoor' triggers, and how to authenticate users on wearables and IoT devices using signals like hand-tapping or magnetic sensors. The work sits at the intersection of mobile computing, machine learning security, and human activity recognition using wireless signals.

Publication output has fluctuated over the last decade with a peak around 2019, a dip in 2024, and a recent resurgence in 2025, suggesting an active but variable publishing pace rather than steady linear growth.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026