جست‌وجوی استاد و پژوهشگر

Joseph Tao-yi Wangمشاهده پروفایل

استاد

• Experimental Economics
• Neuroeconomics
• Game Theory
• +۳ مورد دیگر

Joseph Tao-yi Wang is a Distinguished Professor in the Department of Economics at National Taiwan University (NTU). He holds a PhD from UCLA and previously served as a Postdoctoral Scholar and Visiting Associate at Caltech. His research spans experimental economics, neuroeconomics, game theory, and behavioral economics, with a focus on strategic decision-making, market design, and learning in games. Wang directs the Taiwan Social Sciences Experimental Laboratory (TASSEL), which hosts large-scale experimental research and conferences like the 2017 APESA. His work integrates eye-tracking, pupillometry, and machine learning to study cognitive processes in economic decisions. Wang is also active in educational innovation, developing flipped classroom models with experiments for economics courses. His publications consistently explore behavioral deviations from game-theoretic predictions, such as overcommunication in sender-receiver games and learning patterns in auctions. Recent work emphasizes reproducibility in management science and AI applications in education. Wang’s research uses diverse methodologies—from neuroimaging to field experiments—to test economic theories in real-world contexts. Wang mentors through NTU’s Berkeley Economics Student Assistant Program (BESAP) and organizes mini-courses for high school students. He has not received scientific awards per the available data.

Jieh Hsiangمشاهده پروفایل

استاد

• Automated Reasoning
• Programming Language Logic
• Artificial Intelligence
• +۵ مورد دیگر

Jieh Hsiang is a Distinguished Professor at National Taiwan University , with affiliations in the Department of Computer Science and Information Engineering, the Digital Archives and Automatic Inference Laboratory, and the Digital Humanities Research Center. He holds concurrent roles at the Institute of Information Science, Academia Sinica, and the Higher Education Research & Development Office, National Taiwan University. Education PhD in Computer Science, University of Illinois at Urbana-Champaign (1979–1982) BS in Mathematics, National Taiwan University (1972–1976) Research Interests Hsiang's work spans automated reasoning , digital libraries , digital humanities , and information retrieval . His research focuses on integrating computational methods with cultural heritage preservation , particularly through tools like DocuSky and databases such as the Taiwan Historical Digital Library . He explores AI applications in patent analysis , historical text mining , and semantic relationships in legal documents . Recent Trends in Publications His recent articles highlight advancements in BERT and GPT-2 fine-tuning for patent classification , LARGE language models for legal automation , and GIS-based analysis of historical archives . Themes include digital preservation , AI-driven legal text analysis , and cross-disciplinary computational tools for humanities scholars. Scientific Awards 2019 Ministry of Science and Technology Distinguished Research Fellow 2009 National Taiwan University Outstanding In-House Service Award 2008 Chinese Library Association Special Contribution Award 2006 IEEE Test-of-Time Award 1997 & 1999 National Science Council Outstanding Research Award 1997 Ministry of Education Outstanding Industrial-Academic Collaboration Award 1998–2001 Founder and First Chair of IFIP WG1.6 Labs and Collaborations Hsiang leads the Digital Archive and Automatic Inference Laboratory , developing platforms like DocuSky for digital humanities, Taiwan Historical Digital Library , and QGIS Cloud Maps for spatial analysis. His team collaborates internationally on projects involving historical document digitization , patent automation , and cross-domain knowledge integration .

• Financial Markets
• Quantitative Finance
• Machine Learning in Finance
• +۳ مورد دیگر

Dr. 羅秉政 is currently serving as an Assistant Professor at the Department of Money and Banking , National Chengchi University College of Commerce , where he has been employed since February 2022. His research focuses on quantitative finance and financial markets, with a particular emphasis on options hedging, investment strategies, and market forecasting. Education: Ph.D. in International Finance from National Taiwan University's College of Management. His work integrates statistical methodologies with financial applications, including projects on stochastic volatility modeling, multifactor investment performance, and predictive analytics for stock markets. He has received grants from the National Science and Technology Council (MOST) for studies involving: Recommender Systems in Securities Analysis Accounting Knowledge in Machine Learning Applications Asymmetric Prediction Error Costs in Asset Pricing

• Software security
• Formal verification
• String analysis
• +۳ مورد دیگر

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.

• Econometrics
• International Finance
• Foreign Exchange Forecasting
• +۲ مورد دیگر

Biing-Shen Kuo is a Professor at the Department of International Business, College of Commerce, National Chengchi University (NCCU) in Taiwan. His research focuses on econometrics and international finance, with expertise in exchange rate forecasting, financial econometrics, and machine learning applications in economics. He has led numerous research projects funded by Taiwan's National Science and Technology Council, including studies on exchange rate predictability and econometric inference methods. Education: Ph.D. in Economics, University of Rochester (1989-1995) M.S. in Public Finance, National Chengchi University (1983-1985) B.S. in International Trade, National Chengchi University (1978-1983) Research Focus: Dr. Kuo's work bridges theoretical econometrics and empirical finance, with consistent themes in exchange rate dynamics, predictive modeling, and economic policy impacts. His recent publications integrate machine learning with traditional econometric approaches, particularly for financial forecasting and market analysis. Honors and Awards: Special Appointment Professor, NCCU (multiple years) Teaching Excellence Awards (2011, 2015, 2016, 2019, 2020, 2021) National Science Council Award for Outstanding Research Talent Academia Sinica Young Scholar Research Award (1999) 20-Year Senior Excellent Teacher Award Professional Service: Served as Department Chair (2008-2014) and Vice Dean of the College of Commerce (2005-2008). Editorial board member for multiple economics journals including Economic Papers and Management Review .

• Financial Economics
• Econometrics
• Forecasting
• +۳ مورد دیگر

YU MIN YEN is a Professor at the Department of International Business, College of Commerce, National Chengchi University (NCCU), Taiwan. He has held academic positions at NCCU since 2014, progressing from Assistant Professor to Associate Professor, and since February 2025, to full Professor. His research and teaching focus on Financial Economics and Econometrics. Education: Ph.D. in Finance, London School of Economics and Political Science (2006–2012) M.Sc. in Finance, London School of Economics and Political Science (2005–2006) B.A. in Economics, National Taiwan University (1993–1998) Research Interests: His research spans a wide range of topics in financial econometrics, including forecasting macroeconomic variables, financial risk modeling, portfolio optimization, and the application of machine learning techniques in economic data analysis. He is particularly known for his work on quantile and expectile forecasting, robust estimation under model uncertainty, and the use of derivative-implied information for policy and investment decisions. His recent projects emphasize integrating big data analytics into inflation forecasting and developing robust methods for estimating treatment effects in the presence of endogeneity and heavy-tailed distributions. Scientific Awards: 資深優良教師 (10年) – National Chengchi University (2024) 學術研究優良獎 – National Chengchi University (2024, 2017) 國科會研究獎勵 – Ministry of Science and Technology (2021, 2019, 2018) Research Funding & Leadership: He has served as Principal Investigator on multiple three-year grants from Taiwan’s National Science and Technology Council (MOST), including: 「使用機器學習之分布中介處裡效果的穩健估計」(2023–2026) 「條件尾端平均處裡效果在有內生性之下估計方法之探究」(2021–2023) 「FZ損失函數之應用: 預測風險衡量指標及其他用途」(2019–2021) These projects reflect his commitment to advancing statistical methodologies for real-world economic and financial problems.

Kun-Mao Chaoمشاهده پروفایل

استاد

• Algorithms
• Bioinformatics
• Computational Molecular Biology
• +۳ مورد دیگر

Kun-Mao Chao is a Full-Time Professor at the Department of Computer Science and Information Engineering, National Taiwan University, where he has held multiple roles since 2002, including Chair Professor and Academician of Academia Sinica. He also serves in the Graduate Institute of Biomedical Electronics and Bioinformatics (2006–present) and holds adjunct appointments at various institutions. Education: PhD in Computer Science, Pennsylvania State University (1993) MS in Computer Engineering, National Chiao Tung University (1987) BS in Computer Engineering, National Chiao Tung University (1985) Research Expertise spans Algorithm Design (applied algorithms, approximation algorithms), Bioinformatics , and Computational Molecular Biology . His work focuses on problems like sequence alignment, spanning tree optimization, and DNA copy number variation analysis, often with interdisciplinary applications in medicine and epidemiology. Recent Publications (2012–2022) include studies on mathematical modeling for influenza vaccination policies , nanocarrier drug delivery systems , and XML database query algorithms , reflecting his diverse interests in both computer science and biomedical applications . Professional Activities: He has served as Editor for Information Processing Letters , PC Co-Chair for IEEE BIBE 2011 and ISAAC 2012, and on advisory committees for numerous conferences (APBC, BIBE, GIW, etc.). Laboratory: Leads the Algorithms and Computational Biology Laboratory at National Taiwan University, mentoring students in cutting-edge research areas.

Yen Huan Liمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• High-dimensional Statistics
• +۶ مورد دیگر

Yen Huan Li is an Associate Professor in the Department of Computer Science and Information Engineering at National Taiwan University's College of Engineering. He leads the Learning Theory and Optimization Methods Laboratory and maintains an active research program in theoretical machine learning and optimization. His research expertise spans machine learning, convex optimization, high-dimensional statistics, and quantum information theory . Professor Li specializes in decision making under uncertainty with weak or no assumptions about reality, developing theoretical frameworks that bridge game theory and machine learning. His recent work focuses on Blackwell approachability, probability forecasting calibration, online prediction algorithms, and optimization methods for strongly convex problems. These theoretical contributions have implications for designing robust machine learning algorithms that perform well under minimal assumptions. Professor Li is actively recruiting students and research assistants interested in theoretical aspects of machine learning and optimization. Prospective students must demonstrate knowledge of relevant theory papers and be prepared to discuss them in depth. His laboratory work emphasizes rigorous mathematical analysis of learning algorithms, with applications spanning from basic theoretical questions to practical algorithm design considerations. The research environment combines deep theoretical investigation with attention to practical implications for machine learning systems.

• E-Commerce
• Service Science
• Econometric Analysis
• +۴ مورد دیگر

Dr. Yen-Chun Chou is a Full-time Professor at the Department of Management Information Systems, National Chengchi University (NCCU), where he has held the position since February 2024. Previously, he served as Associate Professor (2018-2024) and Assistant Professor (2013-2018). His career spans over a decade at NCCU, focusing on E-Commerce, Service Science, and Econometric Analysis. Ph.D. in Information Systems from Arizona State University's W. P. Carey School of Business (2008-2013) Master of Science in Information Management from Carnegie Mellon University (2006-2007) Bachelor of Science in Information Management from National Chengchi University (2000-2004) Dr. Chou's research bridges E-Commerce with predictive analytics, machine learning, and operations management. His work explores emotional arousal in online reviews, sparse modeling for R&D efficiency, and interdisciplinary integration of buy-till-you-die modeling with machine learning. Recent projects include demand forecasting optimization and semiconductor product design analytics. His publications demonstrate expertise in supervised machine learning , technology adoption frameworks , and customer behavior modeling . Key topics include cross-item learning , meta-analysis of IT organizational adoption , and multi-theoretical productivity growth in IT services. Recipient of U-Micro Best Paper Award (Honorable Mention) and Ministry of Education's Special Outstanding Talent Grant Multiple awards from the National Science Council (now NSTC) and political university's Academic Research Excellence Awards Recognized as Distinguished Professor and Senior Excellent Teacher (10-year award) at NCCU Dr. Chou has served as Principal Investigator on over 12 MOST/NSTC projects since 2012, with current research focused on personalized marketing optimization (2025-2029) and semiconductor design analytics (2023-2025). His teaching fields include E-Commerce, Service Science, and Empirical Analysis.

• Software Security
• Formal Verification
• String Analysis
• +۵ مورد دیگر

Dr. Fang Yu is an Associate Professor at the Department of Management Information Systems, National Chengchi University, specializing in software security, formal verification, and string analysis. They hold a Ph.D. in Computer Science from the University of California, Santa Barbara. Research Expertise: Dr. Yu focuses on cybersecurity, formal methods for software verification, and machine learning applications in data clustering and adversarial example detection. Their work bridges theoretical computer science with practical security solutions. Publication Trends: Recent articles address biomedical data clustering ( scGHSOM ), explainable AI ( XFlag ), and adversarial defense mechanisms. Topics span bioinformatics, security verification, and fairness testing in neural networks. Awards: 資深優良教師(10年) (2020, National Chengchi University) 國科會研究獎勵 (2019, National Science Council, Taiwan) Projects: Principal Investigator for 15+ grants from Taiwan's National Science and Technology Council and Ministry of Education, focusing on AI security, IoT verification, and financial technology.

• Formal Methods in Software Engineering
• Programming Languages
• Neural Network Testing
• +۶ مورد دیگر

Chih-Duo Hong is an Assistant Professor at the Department of Management Information Systems , College of Business , National Chengchi University , holding this position since February 2023. He earned his Ph.D. in Computer Science from University of Oxford (2017-2022). Research Focus : Formal methods, automated reasoning, neural network testing, and software security Grants : Principal Investigator for multiple National Science and Technology Council projects on data transformation systems (2023-2026) His work spans parameterized verification , probabilistic systems , and neural network fairness , with publications in journals like IEEE Transactions on Software Engineering and ACM TOPLAS. He contributes to concolic testing , array systems abstraction , and constraint-based software optimization . Recent Topics : Formal verification of anonymity/uniformity in probabilistic systems Individual fairness testing for neural networks Regular abstractions for array constraints Collaborations include institutions like University of Oxford, National Chengchi University, and research partners Anthony Lin, Philipp Rümmer, Fang Yu.

• E-commerce
• Service Science
• Empirical Analysis
• +۳ مورد دیگر

Professor Zhou Yanjun is a faculty member at the Department of Management Information Systems, College of Commerce, National Chengchi University. He has been serving as a Professor since February 2024, after previously holding the positions of Associate Professor (2018-2024) and Assistant Professor (2013-2018) at the same institution. Professor Zhou received his PhD in Information Management from Arizona State University (2008-2013), a Master's degree in Information Management from Carnegie Mellon University (2006-2007), and his Bachelor's degree in Information Management from National Chengchi University (2000-2004). His research focuses on e-commerce, service science, empirical analysis, and quantitative analysis. Professor Zhou has published extensively in top-tier journals in information systems, operations management, and decision sciences. His work often bridges theoretical frameworks with practical applications in digital business environments, with particular emphasis on leveraging data analytics to solve complex business problems in retail and e-commerce contexts. Professor Zhou's research demonstrates a strong integration of machine learning techniques with traditional business theories, resulting in innovative approaches to problems such as customer retention, online review helpfulness, and resource allocation optimization. His work has significant implications for both academic theory development and practical business applications. United Microelectronics Corporation Management Science Paper Award - Honorable Mention Ministry of Education Special Outstanding Talent Award National Chengchi University Distinguished Professor Wu Ta-You Memorial Award - Ministry of Science and Technology Multiple Teaching Excellence Awards from College of Commerce Professor Zhou has successfully led multiple research projects funded by the Ministry of Science and Technology, focusing on personalized marketing optimization, data matrix simplification, and emotional arousal in online reviews. He has advised numerous graduate students and contributed to the academic community through editorial service and conference participation. Professor Zhou is actively involved in several research laboratories at National Chengchi University, including the Intelligent Financial Management and Smart Contract Laboratory, the Electronic Business and Service Science Laboratory, and the Digital Innovation Management Research Laboratory, where he applies advanced analytics to solve real-world business problems.