Upcoming Events

Past Events

• Backdoor in AI: Algorithms, Attacks, and Defenses

  Speaker: Ruixiang Tang Date: Feb 14, 11:45am–12:45pm Abstract: As deep learning models are increasingly integrated into critical domains, their safety emerges as a critical concern. This talk delves into the emerging threat of backdoor attacks. These attacks involve embedding a…

• Exploring, Counteracting and Harnessing Adversarial Examples

  Speaker: Han Xu Date: Feb 12, 11:45am–12:45pm Abstract: Recently, with the development of AI and ML, their corresponding safety problems, especially their vulnerability to adversarial attacks, have also become increasingly important. In order to enhance the ML safety, it is…

• Structuring Cooperative Teams for Multi-Agent Autonomy

  Speaker: Qi Zhang Date: Feb 9, 11:45am–12:45pm Abstract: Cooperative artificial intelligence (AI) equips a team of autonomous agents with the capability of planning and learning to maximize their joint utility, which finds a wide range of applications. While being a…

• Learning from Imperfect Data: Incremental Learning and Few-shot Learning

  Speaker: Yaoyao Liu Date: Feb 7, 11:45am–12:45pm Abstract: In recent years, artificial intelligence (AI) has achieved great success in many fields. Although impressive advances have been made, AI algorithms still suffer from an important limitation: they rely on static and…

• Data-Centric AI: Taming AI-ready Feature Space From Decision-Making to Generative-AI

  Speaker: Dongjie Wang Date: Feb 5, 11:45am–12:45pm Abstract: Unlike humans, AI systems are brittle and not robust. They often struggle when faced with novel situations, and are highly sensitive to small perturbations, which can lead to catastrophically poor performance. These…

• Empowering Graph Neural Networks for Real-world Tasks

  Speaker: Zhichun Guo Date: Feb 2, 11:45am–12:45pm Abstract: Graph neural networks (GNNs) have been widely used on graph-structured data, but they also face a series of challenges in solving real-world problems, including scarcity of labeled data, scalability issues, and potential…

• Robust Learning with Evolving Data Streams for Personalized Healthcare

  Speaker: Jingchao Ni Date: Jan 31, 11:45am–12:45pm Abstract: The proliferation of data acquisition technologies such as wearable devices, sensors, data logging, imaging, and IoT, has produced vast amounts of data across domains. This influx of data has empowered AI applications…

• Harnessing Mobile Technologies for Healthcare Equity and Fairness

  Speaker: Huining Li Date: Jan 29, 11:45am–12:45pm Abstract: Mobile health technologies are increasingly recognized as a means to bridge health disparities due to their high accessibility, cost-effectiveness, and global connectivity. However, research indicates that if these technologies are not implemented…

• Responsible Graph Machine Learning Under a Fairness Lens

  Speaker: Yushun Dong Date: Jan 24, 11:45am–12:45pm Abstract: Graph learning algorithms have been increasingly deployed in a plethora of real-world applications, such as epidemic analysis, healthcare, and financial analysis. Nevertheless, there has been a rise in societal concerns about the…

• Pushing Acoustic Sensing from the Laboratory to Real World: Theories, Applications, and Practical Problems

  Speaker: Dong Li Date: Jan 22, 11:45am–12:45pm Abstract: With the proliferation of voice assistants, speakers and microphones are essential components in billions of smart devices that people interact with on a daily basis, such as smartphones, smart watches, smart speakers,…