Agentic AI Frontier Online Seminar: Towards AI Security – An Interplay of Stress-Testing and Alignment
Shangding Gu
Dear colleagues,
On Friday (5th of September 2025), we are hosting a talk in the scope of the AI Agent Frontier Online Seminar. The details for the talk are given below. We invite you to join via Zoom if you are interested and feel free to share this invitation with colleagues or students who might find the talk relevant.
Talk Title: Towards AI Security – An Interplay of Stress-Testing and Alignment
Speaker: Prof. Furong Huang (University of Maryland)
Talk Time: 5th September 2025, 09:00h California time / 12:00h Eastern Time / 18:00h CEST Time (Amsterdam, Berlin, Rome, Stockholm, Vienna) / +1 00:00h Beijing time.
Join Zoom Meeting:
https://virginiatech.zoom.us/j/87872134251?pwd=d8ycf9bbWVBK87EbII7nQPIy5YX0Qf.1
Passcode: 309194
Talk Abstract: As large language models (LLMs) become increasingly integrated into critical applications, ensuring their robustness and alignment with human values is paramount. This talk explores the interplay between stress-testing LLMs and alignment strategies to secure AI systems against emerging threats. We begin by motivating the need for rigorous stress-testing approaches that expose vulnerabilities, focusing on three key challenges: hallucinations, jailbreaking, and poisoning attacks. Hallucinations—where models generate incorrect or misleading content—compromise reliability. Jailbreaking methods that bypass safety filters can be exploited to elicit harmful outputs, while data poisoning undermines model integrity and security. After identifying these challenges, we propose alignment methods that embed ethical and security constraints directly into model behavior. By systematically combining stress-testing methodologies with alignment interventions, we aim to advance AI security and foster the development of resilient, trustworthy LLMs.
Bio: Furong Huang is an Associate Professor of the Department of Computer Science at the University of Maryland. Specializing in trustworthy machine learning, Security in AI, AI for sequential decision-making, and generative AI, Dr. Huang focuses on applying principles to solve practical challenges in contemporary computing to develop efficient, robust, scalable, sustainable, ethical, and responsible machine learning algorithms. She is recognized for her contributions with awards including best paper awards, the MIT Technology Review Innovators Under 35 Asia Pacific, the MLconf Industry Impact Research Award, the NSF CRII Award, the Microsoft Accelerate Foundation Models Research award, the Adobe Faculty Research Award, three JP Morgan Faculty Research Awards and Finalist of AI in Research - AI researcher of the year for Women in AI Awards North America.
AI Agent Frontier Online Seminar Homepage: https://agentic-ai-frontier-seminar.github.io/index.html We welcome researchers and students who are interested in AI agents to join us! To receive relevant seminar information in time, please click the link to register.
Best regards,
The Agentic Frontier Online Seminar organizers