Research Direction
Current research focuses on addressing the challenges and limitations of applying requirements engineering to AI-based systems, particularly concerning explainability, user interaction, and ethical considerations. This involves exploring various model architectures and algorithms across diverse applications, including intrusion detection, image augmentation, and autonomous vehicles, with a strong emphasis on improving the reliability and trustworthiness of AI systems. The overarching goal is to develop robust and responsible AI methodologies, impacting both the advancement of AI research and the safe deployment of AI in various sectors. This includes developing methods for handling unstructured data and improving the efficiency of AI training and deployment, particularly in resource-constrained environments.
Papers
Multimodal Sentiment Analysis: A Survey
Songning Lai, Xifeng Hu, Haoxuan Xu, Zhaoxia Ren, Zhi Liu
Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors
Long Chen, Yuchen Li, Chao Huang, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang