About Me

I am currently a first-year PhD student in Computer Science at Texas A&M University, advised by Prof. Zhiyuan Yu. My research interests include Trustworthy ML, AI Safety and Applied Cryptography.

Previously, I earned my Master’s degree in Computer Engineering at University of Illinois Urbana-Champaign, advised by Prof. Varun Chandrasekaran, whose mentorship has been invaluable in shaping my early academic journey. I also had the privilege of working closely with Prof. Yupeng Zhang and Prof. David Heath, whose guidance introduced me to the fascinating world of cryptography.

Before joining UIUC in 2023, I earned my Bachelor’s degree in Computer Engineering through a joint program between the University of Illinois Urbana-Champaign and Zhejiang University. During my undergraduate studies, I had the privilege of working with Prof. Wee-Liat Ong, Prof. Gaoang Wang, and Prof. Thomas Honold.

I’m open to collaborating on interesting research ideas. If you are interested in Trustworthy ML/AI Safety and seek collaboration, please feel free to contact me at taoranl2 [at] illinois [dot] edu.

“Stay hungry, stay foolish.”
— Steve Jobs, Stanford Commencement Address, 2005

Education

Texas A&M University, 2025 - Present
Doctor of Philosophy in Computer Science

University of Illinois, Urbana-Champaign, 2023 - 2025
Master of Science in Computer Engineering

Zhejiang University, 2018 - 2023
Bachelor of Engineering in Computer Engineering

University of Illinois, Urbana-Champaign, 2018 - 2023
Bachelor of Science in Computer Engineering

“纸上得来终觉浅，绝知此事要躬行。”
— 陆游《冬夜读书示子聿》

Research Interests

My research broadly covers computer security and privacy, focusing on robust, scalable, and practical solutions in the following domains:

• Trustworthy Machine Learning
  • Adversarial robustness and privacy-preserving AI
  • Machine unlearning
  • AI for secure code generation and vulnerability detection
  • LLM agent security
  • Integrating cryptographic protocols (MPC, ZKP) with ML
• Security and Privacy of IoT and Cyber-Physical Systems
  • Secure AI integration in robotics and autonomous systems
  • Resilience of interconnected smart infrastructures
• Cryptography
  • Secure multi-party computation (MPC)
  • Zero-knowledge proofs (zk-SNARKs)
  • Privacy-preserving data analytics