Song Fang

Dr. Song Fang is an Associate Professor in the School of Computer Science at the University of Oklahoma. She holds a Ph.D. from the University of South Florida (2018), M.S. from Beijing University of Posts and Telecommunications, and B.S. from South China University of Technology. Her research focuses on wireless/mobile system security, cyber-physical systems, IoT security, and machine learning applications in cybersecurity. She has been promoted to Associate Professor with tenure since July 2024 and serves as an Associate Editor for IEEE TDSC and TPC member for multiple top conferences.

Education:

• Ph.D., Computer Science, University of South Florida (2018)
• M.S., Computer Science, Beijing University of Posts and Telecommunications, China
• B.S., Computer Science, South China University of Technology, China

Research Interests: Dr. Fang's work emphasizes adversarial wireless attacks, defense mechanisms, and leveraging machine learning for system security. Her projects include keystroke inference countermeasures, camera localization, and vehicular network security. Recent trends show her focus on proactive defenses and exploiting signal characteristics for privacy preservation.

Awards: She received the EAI MobiQuitous 2022 Best Paper Award for 'HoneyBreath'.

Advising & Grants: Advised students include Yan Zhou, Qiuye He, and Edwin Yang. Secured NSF grants for projects like 'Exploiting Stimulus-response Correlation for Wireless Hidden Device Localization' and the OVPRP Faculty Investment Award (2022).

Labs/Teams: Leads a research group active in automotive security, wireless attacks, and IoT vulnerability analysis, evidenced by collaborations with industry and academic partners.