Professor Yun-Nung Chen works at the Department of Computer Science and Information Engineering , National Taiwan University , focusing on Natural Language Processing and Dialogue Systems . With a Ph.D. from Carnegie Mellon University , their research bridges Machine Learning and Language Understanding in conversational AI. Education Ph.D. in Language Technologies, Carnegie Mellon University (2015) M.S. in Computer Science, National Taiwan University (2011) B.S. in Computer Science, National Taiwan University (2009) Research Trends Recent work emphasizes Retrieval-Augmented Generation , Knowledge Editing in LLMs , and Temporal Modeling for dialogue systems. Key themes include cross-modal understanding , semantics-driven dialogue , and robust language modeling across domains. Scientific Recognition Best Student Paper, IEEE ASRU 2013 Best Student Paper, IEEE SLT 2010 Distinguished Master Thesis, ACLCLP 2011 Best Paper Finalist, ISCA INTERSPEECH 2012 Current projects involve StreamBench for continuous agent improvement and Taiwan LLM for culturally aligned language models.
Dr. Shun-Wen Hsiao is an Associate Professor in the Department of Management Information Systems at National Chengchi University (NCCU), Taiwan. He earned his PhD in Information Management from National Taiwan University and has been with NCCU since 2017, first as an Assistant Professor before his promotion to Associate Professor in 2023. His research spans: Cybersecurity : Malware analysis, threat detection, IoT security, and blockchain applications Artificial Intelligence : Neural networks for security, NLP, and recommendation systems FinTech : Blockchain frameworks, secure voting systems, and P2P lending risk models E-commerce : Livestreaming recommendation algorithms and consumer behavior analysis He has received multiple awards including: National Science Council Research Award (2023) Three consecutive Outstanding Team awards for Information Security R&D (2016-2018) Research grants from Taiwan's Ministry of Science and Technology Dr. Hsiao leads several major research projects funded by Taiwan's National Science and Technology Council, focusing on explainable AI for cybersecurity, financial technology security, and big data analytics platforms. His work frequently appears in top IEEE transactions and cybersecurity conferences.
Dr. Yu Fang is an Associate Professor in the Department of Information Management at National Chengchi University's College of Business in Taipei, Taiwan. With a strong academic foundation from National Taiwan University (BS and MS) and a PhD in Computer Science from the University of California, Santa Barbara, Dr. Fang has established herself as a prominent researcher in software security and formal methods, with recent expansion into AI security domains. PhD in Computer Science, University of California, Santa Barbara (2005-2010) MS in Information Management, National Taiwan University (1998-2000) BS in Information Management, National Taiwan University (1994-1998) Dr. Fang's research spans software security, formal verification, and string analysis, with significant contributions to vulnerability detection in web applications, static analysis of mobile applications, and more recently, security and testing of neural networks. Her work bridges theoretical formal methods with practical security applications, particularly in the context of modern software systems and AI technologies. The evolution of her research shows a clear trajectory from traditional software security toward addressing emerging challenges in AI security, including adversarial examples, deepfake detection, and fairness verification in machine learning models. Analysis of Dr. Fang's recent publications reveals a strategic expansion of her research focus. While maintaining her strong foundation in software security and formal methods, she has successfully transitioned into the rapidly evolving field of AI security. Her work now addresses critical challenges such as adversarial example detection using explainability methods (DeepSHAP), concolic testing for neural network fairness verification, and defenses against deepfake attacks. This represents a natural progression from her earlier work on string analysis and vulnerability detection in traditional software systems. Senior Excellent Teacher (10 years) award from National Chengchi University National Science Council (now Ministry of Science and Technology) Research Award Dr. Fang has secured substantial research funding, particularly from Taiwan's Ministry of Science and Technology, with current projects focusing on neural network automated testing and AI security. Her research group maintains active collaborations with both academic and industry partners, particularly in the financial technology sector where security and regulatory compliance are paramount. While specific lab affiliations aren't explicitly mentioned in the provided information, her research profile suggests strong connections to the Software Security Laboratory within the Department of Information Management.
