The SEES Lab

• Autonomous security monitoring and enforcement -- Design HW/SW agents that can detect security anomaly and mitigate attacks with minimal human intervention.
• Machine learning for design automation
  • Sequential Pattern Mining using Data Mining Techniques
  • Sequential Pattern Mining using Recurrent Neural Network
• Hardware/software design of machine learning under latency and energy constraints
• Testing, verification, and validation of software, hardware, and embedded systems
  • Scalable methods for probabilistic model checking
  • Efficient model checking of parallel and distributed systems

To interested graduate students: dedicated and hardworking students are welcome to join us to work on different projects as outlined above. If you are interested in something that is related but not listed, please do share your thoughts. When you contact us, please explain briefly why you would like to apply, and why you are interested in the area of yoru choice.

Undergraduate students with good academic records and strong self-learning capabilities are also welcome to contact us for research experience opportunities.