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Welcome to AIS2 (Artificial Intelligence and Systems Security) Lab! AIS2Lab is an AI-oriented security research team established by Asst Prof. Daoyuan Wu in the Division of Industrial Data Science, School of Data Science at Lingnan University (LU), one of the eight UGC-funded universities in Hong Kong.
We adopt a systems security mindset to advance the security and trustworthiness of artificial intelligence in the era of Large Language Models (LLMs). At AIS2Lab, we are committed to conducting inter-disciplinary research that integrates knowledge and methodologies from computer science, artificial intelligence, law, healthcare, and other related fields. Our work aims to address emerging security challenges and promote responsible innovation across both technical and societal domains.
Specifically, our research focuses on the following key areas:
Large Language Model and AI Security: LLMs for Cybersecurity; Security of LLMs; AI Safety; LLM + Law.
Blockchain and Smart Contract Security: Chain & DeFi Security; Consensus Security; Transaction Compliance.
GPU Software and Medical System Security: AI Infrastructure Security; Healthcare and Medical System Security.
Novel Program Analysis and Mobile Security: Novel Program Analysis & Fuzzing; LLM for Mobile; EdgeAI Security.
Through close collaboration with experts from diverse disciplines, AIS2Lab aims to build secure and responsible AI systems that benefit both technology and society.
To realize this vision, we are always seeking passionate and persistent students (PhD/RA/Postdoc/Interns) with backgrounds or strong interests in AI/LLMs, blockchain, GPU and medical software, programming languages, and fuzzing to join AIS2Lab. We value persistence and a commitment to research excellence.
Currently, we have the following priority openings:
For full-time RA applicants, you are required to pursue a PhD in our group after completing the RA. Otherwise, we will not consider your application. For remote interns, there is no such restriction. We always welcome excellent UG students.