جستجوی استاد راهنمای دانشگاهی

• Consumer Behavior
• Consumer Psychology
• Brand Management
• +۴ مورد دیگر

Lien-Ti Bei is a Distinguished Professor in the Department of Business Administration at National Chengchi University's College of Commerce in Taipei, Taiwan. She also serves as Chairman of the Center for Public and Business Administration Education. With over 25 years of academic experience, Professor Bei has established herself as a leading scholar in consumer behavior and marketing research in Taiwan and Asia. Her research interests span Consumer Behavior, Consumer Psychology, Brand Management, and Marketing Research, with recent work focusing on ESG implementation, consumer neuroscience applications in marketing, and sustainable business practices. Professor Bei's work bridges theoretical marketing concepts with practical business applications, particularly in the Asian context. Her publication record shows consistent productivity with over 50 journal articles in SSCI/TSSCI-indexed journals since 1995, including recent publications in Journal of Engineering and Technology Management, Journal of Product & Brand Management, and Harvard Business Review Chinese Edition. Her research demonstrates an evolution from traditional brand extension and consumer behavior topics toward contemporary issues like ESG, AI-human interaction, and sustainable marketing practices. Distinguished Professor at National Chengchi University (multiple years) Asia's Top 100 Marketing Scholars (2017) Chungni Outstanding Teaching Award Multiple Research Awards from Taiwan's National Science and Technology Council Management Journal Paper Award Professor Bei has successfully secured numerous research grants, primarily from Taiwan's National Science and Technology Council, with current projects extending through 2026. Her active role as Principal Investigator on multiple grants demonstrates ongoing research productivity. She serves as Editor for Management Review and has contributed to special issues on sustainable development and consumer behavior trends.

Tsan-sheng Hsuمشاهده پروفایل

استاد پژوهش

• Graph Theory
• Algorithm Design
• Data Privacy Protection
• +۳ مورد دیگر

Tsan-sheng Hsu is a Research Professor at the Institute of Information Science (IIS), Academia Sinica in Taiwan. He has been a tenured full research fellow since June 2003, after serving as an assistant research fellow starting in 1993 and associate research fellow from 1997-2003. He also served as Deputy Director of IIS from 2002-2004 and Director of Academia Sinica Computing Center from 2008-2010. Since 2019, he has been Editor in Chief for the Journal of Information Science and Engineering. Dr. Hsu's educational background includes: Bachelor of Science in Computer Sciences from National Taiwan University (1981-1985), graduating first in class Master of Science in Computer Sciences from University of Texas at Austin (1990) Ph.D. in Computer Sciences from University of Texas at Austin (1993) Dr. Hsu's primary research interests focus on graph theory and its applications , where he investigates fundamental properties of graphs and develops algorithms for connectivity augmentation problems. His work in algorithm design, analysis, implementation and performance evaluation spans sequential, parallel, and distributed algorithms. In data-intensive computing , he explores data privacy protection, large-scale social network analysis, and computer Chinese chess. His research often bridges theoretical breakthroughs with practical applications in network reliability, statistical data security, and efficient computation. Dr. Hsu's publication record demonstrates a consistent focus on graph theory problems, particularly connectivity augmentation, graph searching, and distance-hereditary graphs. His work shows progression from theoretical foundations to practical applications, with an emphasis on developing efficient algorithms with provable performance guarantees. The majority of his publications appear in top theoretical computer science venues, reflecting his strong contributions to fundamental algorithmic research. Dr. Hsu has received several prestigious awards and honors: Bert Kay Dissertation Award from University of Texas at Austin (1993) Academia Sinica Research Award for Junior Research Investigators (2003) Phi Tau Phi Scholastic Honor Society membership (1985) MCD fellowship and IBM graduate fellowship during doctoral studies Dr. Hsu leads the Massive Data Computation and Management Lab at Academia Sinica, where he directs research on graph theory applications, algorithm design, and data privacy. His research has been supported by various projects including theoretical foundation work on graph augmentation and searching problems, as well as applied research in inference control, computer Chinese chess, and parallel computation. He has collaborated extensively with researchers from institutions including Northwestern University, National Tsing Hua University, and National Taiwan University.

• 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

• International Investment
• Business Forecasting
• E-commerce Economics and Strategies
• +۳ مورد دیگر

YEE-TIEN FU is an Associate Professor at the Department of International Business, College of Commerce, National Chengchi University. He holds a PhD in Engineering-Economic Systems and an MS in Statistics from Stanford University, an MS in Industrial Engineering from Virginia Tech, and a BS in Industrial Engineering from Chung Yuan Christian University. Research Areas: International Investment, Business Forecasting, E-commerce Economics and Strategies Key Themes: Corporate governance, financial innovation, cross-border business models, and data-driven decision-making His recent work focuses on business strategy and financial technology , with publications analyzing Stanford’s endowment management, cross-Strait e-commerce collaboration, and ethical compensation frameworks. He has presented at conferences like the Western Decision Sciences Institute and British Academy of Management, emphasizing big data analytics and sustainable innovation . Scientific Honors: Senior Excellent Teacher (20 years) from Ministry of Education Senior Excellent Teacher awards from National Chengchi University (20 and 10 years) NSC Type A Research Award His teaching spans International Investment, Applied Financial Engineering, and Computer Simulation. Contact: iamtedfu@nccu.edu.tw

• Financial Engineering
• Derivatives
• Financial Econometrics
• +۶ مورد دیگر

Shih-Kuei Lin is a Professor in the Department of Money and Banking at National Chengchi University's College of Commerce, where he has served since 2010, advancing from Associate Professor to full Professor. He has held significant leadership roles including Department Chair from 2016-2020 and currently serves as a full-time faculty member with ongoing research projects through 2027. His educational background includes a Ph.D. in Statistics from National Chengchi University (2000-2004), a Master's in Statistics from the same institution (1995-1997), and a Bachelor's in Mathematics from National Cheng Kung University (1990-1994). His research expertise spans Financial Engineering, Derivatives, Financial Econometrics, Actuarial Finance, and has recently expanded to include Financial Big Data, Green Finance, Climate Finance, and Banking Management Strategy. Professor Lin's work demonstrates a sophisticated approach to financial modeling, particularly in derivatives pricing under complex market conditions including jump diffusion models, regime-switching frameworks, and stochastic volatility environments. His recent publications show an increasing focus on ESG integration, climate finance applications, and machine learning approaches to portfolio management. His research has been consistently published in top-tier finance journals including the Journal of Banking and Finance, Review of Quantitative Finance and Accounting, and International Review of Financial Analysis. His research portfolio includes over 40 publications since 2003, with a particularly productive period from 2019-2024. His work shows evolution from traditional financial engineering topics toward contemporary issues including climate risk, ESG integration, and machine learning applications in finance. National Science Council Research Award (multiple years: 108, 109, 110, 111, 112, 113) Senior Excellent Teacher (20 years) from National Chengchi University Senior Excellent Teacher (10 years) from National Chengchi University Professor Lin has served as Principal Investigator for numerous research projects funded by Taiwan's National Science and Technology Council, with current projects extending through 2027 focusing on derivatives pricing and risk management. He has also collaborated with various financial institutions including Taiwan Business Bank, Cathay Financial Holdings, and Standard Chartered Bank on applied research projects. His departmental leadership as Chair of the Department of Money and Banking from 2016-2020 demonstrates his commitment to academic administration alongside his research activities.

• 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.

Yu Qingxiangمشاهده پروفایل

استاد

• Big Data Analysis
• Demographics
• Game Theory
• +۱ مورد دیگر

Yu Qingxiang is a Professor in the Department of Statistics at the Business School, National Chengchi University . His research expertise spans Big Data Analysis, Demographics, Game Theory, and Spatial Statistics. Education: Bachelor in Mathematics from National Taiwan University, PhD in Statistics from University of Wisconsin Yu has received multiple awards from National Chengchi University, including the Academic Research Excellence Award (2014, 2011), Senior and Excellent Teachers recognition (2014), and Service Medal (2005). His career at National Chengchi University includes serving as Department Head (2003-2005) and continuous professorship since 2006. Academic Research Excellence Award (2014) Academic Research Excellence Award (2011) Excellent Research Award for Internationalization of Academic Research Results (2008, 2005, 2004, 2001) Outstanding Teacher Award (2004)

• Retail Operations
• Supply Chain Management
• Quantitative Analysis
• +۵ مورد دیگر

Professor Hao-Chun Chuang is a distinguished faculty member in the Department of Management Information Systems at National Chengchi University's College of Commerce. He holds a Ph.D. in Information and Operations Management from Texas A&M University and has steadily progressed through the academic ranks at NCCU, serving as Assistant Professor (2013-2016), Associate Professor (2016-2022), and currently Professor (2022-present). His research expertise spans Retailing, Smart Operations, Quantitative Analysis, Supply Chain, and System Dynamics, with a strong focus on empirical operations management research. Professor Chuang has published extensively in top-tier journals including Journal of Operations Management, Omega, Production and Operations Management, and European Journal of Operational Research, demonstrating a consistent trajectory of high-impact research in retail operations and analytics. His publication record reveals a clear evolution from foundational work on retail inventory management and shelf availability toward more sophisticated applications of machine learning and predictive analytics in operations management. Recent publications increasingly integrate advanced data science techniques with traditional operations management problems, particularly in retail demand forecasting, customer behavior analysis, and service operations optimization. Major Scientific Awards: International Young Outstanding Scholar Research Program (multiple years) JOM Associate Editor Service Award (2024) OMEGA Best Paper Award 2023 Wu Ta-You Memorial Award Academic Research Excellence Award from NCCU (multiple years) Yu Shan Academic Award from College of Commerce (multiple years) Senior Excellent Teacher (10 years) recognition Professor Chuang has successfully led numerous research projects funded by Taiwan's National Science and Technology Council, with current projects focusing on empirical theory development in operations management from a machine learning perspective. His work bridges academic rigor with practical applications in retail operations, demonstrating strong industry relevance while maintaining scholarly excellence.

• Information Management
• IT Portfolio Management
• RFID Data Management
• +۶ مورد دیگر

Professor YU-JU TU is a distinguished faculty member in the Department of Management Information Systems at National Chengchi University in Taipei, Taiwan. Currently holding the position of Professor since February 2025, she has progressed through the academic ranks from Assistant Professor (2014-2020) to Associate Professor (2020-2025) before achieving her current position. She earned her Ph.D. in Business Administration from the University of Illinois, Urbana Champaign between 2008 and 2014. Professor TU's research expertise centers on information management with specific focus areas including IT portfolio management, RFID data management, and decision support systems. Her scholarly work demonstrates a consistent trajectory in examining how information systems can solve complex business problems, particularly in supply chain management, retail applications, and emerging technologies like autonomous vehicles and drone delivery systems. Her research bridges theoretical frameworks with practical applications, often addressing security, privacy, and ethical considerations in technology implementation. Her publication record shows remarkable productivity with numerous articles in top-tier journals including Information & Management, Decision Support Systems, European Journal of Information Systems, and Communications of the ACM. Her research portfolio reveals a clear evolution from foundational RFID security work to broader applications in autonomous systems and ethical considerations in technology deployment. Recent work increasingly addresses contemporary challenges in drone delivery security, misinformation detection, and ethical consumerism in technology-mediated supply chains. 資深優良教師(10年) from National Chengchi University (2024) 學術研究優良獎 from National Chengchi University (2022) Multiple Excellent Digital Learning Course Awards (2014-2020) College of Commerce Teaching Excellence Award (2018, 2020) List of Teachers Ranked as Excellent by Students from UIUC (2013) Professor TU actively leads multiple research projects funded by Taiwan's National Science and Technology Council, with current work focusing on RFID/IoT systems, drone systems for last-mile delivery, and sustainable applications. She has served as Principal Investigator for numerous projects examining security and privacy risks in emerging technologies, demonstrating her leadership in bridging academic research with practical industry applications. Her work with the Ministry of Education on cross-agency big data statistical database construction further highlights her contribution to national-level information infrastructure development.

Pei-Yu Houمشاهده پروفایل

استادیار

• Operations Management
• Statistical Data Analysis
• Natural Language Processing
• +۳ مورد دیگر

Pei-Yu Hou is an Assistant Professor in the Department of Business Administration at National Chengchi University's College of Commerce, specializing in Operations and Supply Chain Management. Dr. Hou joined the university in August 2024 and maintains an active research agenda that bridges technical computing with business applications. Dr. Hou's research expertise spans Operations Management, Statistical Data Analysis, Natural Language Processing, and Database Management. Their work demonstrates an interdisciplinary approach combining computer science techniques with business administration principles, particularly in supply chain systems. The research trajectory shows progression from technical engineering foundations to practical business applications. Dr. Hou has published in top-tier venues including the Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22), with research focusing on knowledge-graph embeddings and pathway analysis. Their current scholarly work shows strong connections between artificial intelligence methodologies and operational business challenges, particularly in supply chain management. Operations Management Statistical Data Analysis Natural Language Processing Database Management Supply Chain Management AI Applications in Business Dr. Hou is currently Principal Investigator for significant research projects funded by the National Science and Technology Council focused on utilizing AI models to construct and explore supply chain networks, indicating a growing research program with practical business implications.

Chung-Ming Kuanمشاهده پروفایل

استاد

• Econometric Theory
• Financial Econometrics
• Macroeconomic Forecasting
• +۳ مورد دیگر

Chung-Ming Kuan is an NTU Chair Professor and Distinguished Professor in the Department of Finance at National Taiwan University, with a joint appointment as Professor in the Department of Economics. He was elected as an Academician of Academia Sinica in 2002, one of Taiwan's highest academic honors. Education: M.A. in Economics from the University of California, Davis (1984) Ph.D. in Economics from the University of California, San Diego (1989) Professor Kuan's research spans several key areas in econometrics and economics. His primary research interests include Econometric Theory, Financial Econometrics, Macroeconomic Forecasting, and Program Evaluation. His work demonstrates a strong focus on developing robust statistical methods and applying them to financial and economic problems, with particular attention to Taiwan's economy. His teaching encompasses Econometric Theory, Financial Econometrics, Statistics, and Time Series Analysis. Analysis of Professor Kuan's recent publications reveals a consistent focus on advanced econometric methods, particularly in hypothesis testing, quantile regression, and time series analysis. His work often addresses practical challenges in financial econometrics and macroeconomic modeling, with many studies applying sophisticated techniques to Taiwan's economic data. A notable trend is his development of methods that avoid common pitfalls like data snooping bias and inconsistent estimation of asymptotic covariance matrices. Scientific Awards: Academician, Academia Sinica (elected 2002) Professor Kuan has made significant contributions to econometric theory and its applications. His research has been published in top journals across econometrics, finance, and economics. He has supervised numerous graduate students and has been actively involved in teaching advanced econometrics courses at National Taiwan University. His work has influenced both theoretical developments in econometrics and practical applications in financial markets and economic policy. As evidenced by his extensive publication record and academic appointments, Professor Kuan maintains active research programs in multiple areas of econometrics, with particular emphasis on robust statistical methods and their applications to financial and macroeconomic 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.

Shih-wei Liaoمشاهده پروفایل

دانشیار

• Blockchain
• Fintech
• Big Data
• +۶ مورد دیگر

Associate Professor Shih-wei Liao is a faculty member in the Department of Information Engineering at National Taiwan University, leading the ABC Lab / NTU Consensus Lab. His research bridges blockchain technology, Fintech, and Big Data systems with real-world applications. His research expertise spans: Blockchain systems (consensus protocols, environmental monitoring, Gcoin implementation) Fintech applications (digital currency, RegTech, automated clearinghouse) AI/ML optimization (CNN memory traffic, medical imaging, pollution forecasting) Compiler and virtual machine design (Android legacy systems) Recent publications (2018-2021) show strong focus on environmental blockchain applications, IoT security, and medical AI - with work published in IEEE conferences, Blockchain Robotics AI conferences, and journals like IEEE Network. His research demonstrates consistent evolution from foundational Android systems to cutting-edge blockchain applications. Awards include: Google Founders' Award for Android contributions CGO'04 Best Paper Award Nominee The ABC Lab maintains active industry partnerships with major technology companies and financial institutions, evidenced by seminars with Bitfinex/Tether executives and collaborations on Taiwan's Asia Silicon Valley Project. Professor Liao pioneered NTU's Blockchain course in 2015 and leads the NTU RegTech initiative. The lab operates from office R514 with Friday office hours (15:00-17:00), focusing on 'impact, learning-by-doing, interdisciplinary' approaches as stated in their mission.