| Publication | Année de publication | Type de publication |
|---|---|---|
| CHEN, C. Y. T., E. SUN, Y.-B. LIN , "Reconciling spatiotemporal conjunction with digital twin for sequential travel time prediction and intelligent routing", Annals of Operations Research, 2025, vol. 348, pp. 671–716 | 2025 | Article |
| CHEN, C. Y. T., E. SUN, Y.-B. LIN, "Reliable information system for identifying spatio-temporal continuity of kinetic deformed objects with big point cloud data", Annals of Operations Research, 2025, vol. 349, pp. 103-138 | 2025 | Article |
| CHEN, C. Y. T., E. SUN, W. MIAO, Y.-B. LIN , "Reconciling business analytics with graphically initialized subspace clustering for optimal nonlinear pricing", European Journal of Operational Research, 2024, vol. 312, no. 2, pp. 1086-1107 | 2024 | Article |
| CHEN, C. Y. T., E. SUN, M.-F. CHANG, Y.-B. LIN, "Enhancing travel time prediction with deep learning on chronological and retrospective time order information of big traffic data", Annals of Operations Research, 2024, vol. 343, pp. 1095–1128 | 2024 | Article |
| CHEN, C. Y. T., L. B. LIN, W.-L. CHEN, K.-C. WU, Y.-W. LIN, E. SUN, C.-Y. LIU, "The CWT IoT Device for Detecting Rare Events of Orchid Disease", IEEE Internet of Things Journal, 2024, vol. 11, no. 12, pp. 15 | 2024 | Article |
| ŠIMOVIC, P. P., C. Y. T. CHEN, E. SUN, "Classifying the variety of customers’ online engagement for churn prediction with a mixed-penalty logistic regression", Computational Economics, 2023, vol. 61, pp. 451-485 | 2023 | Article |
| LAI, W., C. CHEN, E. SUN, "Risk factor extraction with quantile regression method", Annals of Operations Research, 2022, vol. 316, pp. 1543–1572 | 2022 | Article |
| CHEN, C.-C., C.-C. CHANG, E. SUN, M.-T. YU, "Optimal Decision of Dynamic Wealth Allocation with Life Insurance for Mitigating Health Risk under Market Incompleteness", European Journal of Operational Research, 2022, vol. 300, no. 2, pp. 727-742 | 2022 | Article |
| LAI, W., C. Y. T. CHEN, E. SUN, "Risk factor extraction with quantile regression method", Annals of Operations Research, 2022, vol. 316, pp. 1543–1572 | 2022 | Article |
| CHEN, Y.-T., E. SUN, M.-F. CHANG, Y.-B. LIN, "Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0", International Journal of Production Economics, 2021, vol. 238, pp. 108157 | 2021 | Article |
| BELOVAS, I., L. SAKALAUSKA, V. STARIKOVIČIUS, E. SUN, "Mixed-Stable Models: An Application to High-Frequency Financial Data", Entropy, 2021, vol. 23, pp. 739 | 2021 | Article |
| LAI, W., Y.-T. CHEN, E. SUN, "Comonotonicity and low volatility effect", Annals of Operations Research, 2021, vol. 299, no. 1-2, pp. 1057–1099 | 2021 | Article |
| CHEN, Y. T., E. SUN, Y. B. LIN, "Merging anomalous data usage in wireless mobile telecommunications: Business analytics with a strategy-focused data-driven approach for sustainability", European Journal of Operational Research, 2020, vol. 281, no. 3, pp. 687-705 | 2020 | Article |
| LIN, E., E. SUN, M. -T. YU, "Behavioral data-driven analysis with Bayesian method for risk management of financial services", International Journal of Production Economics, 2020, vol. 228, pp. 107737 | 2020 | Article |
| CHEN, Y.-T., E. SUN, Y.-B. LIN, "Machine learning with parallel neural networks for analyzing and forecasting electricity demand", Computational Economics, 2020, vol. 56, pp. 569-597 | 2020 | Article |
| CHEN, Y.-T., W. -N. LAI, E. SUN, "Jump Detection and Noise Separation by a Singular Wavelet Method for Predictive Analytics of High-Frequency Data", Computational Economics, 2019, vol. 54, no. 2, pp. 809-844 | 2019 | Article |
| CHEN, Y.-T., E.SUN, Y.-B.LIN, "Coherent quality management for big data systems: a dynamic approach for stochastic time consistency", Annals of Operations Research, 2019, vol. 277, pp. 3-32 | 2019 | Article |
| SUN, E., T. KRUSE, Y. T. CHEN, "Stylized Algorithmic Trading: Satisfying the Predicted Near-Term Demand of Liquidity", Annals of Operations Research, 2019, vol. 281, no. 1-2, pp. 315-347 | 2019 | Article |
| CHEN, Y. T., E.SUN, M. T.YU, "Risk Assessment with Wavelet Feature Engineering for High-frequency Portfolio Trading", Computational Economics, 2018, vol. 52, no. 2, pp. 653-684 | 2018 | Article |
| LIN, E. M. H., E.SUN, M.-T.YU, "Systemic risk, financial markets, and performance of financial institutions", Annals of Operations Research, 2018, vol. 262, no. 2, pp. 579-603 | 2018 | Article |
| SUN, E., R. J.WANG, M. T.YU, "Integrated Portfolio Risk Measure: Estimation and Asymptotics of Multivariate Geometric Quantiles", Computational Economics, 2018, vol. 52, no. 2, pp. 627-652 | 2018 | Article |
| SUN, E., Y. T.CHEN, "Automated Business Analytics for Artificial Intelligence in Big Data @X4.0 Era" dans Frontiers in Data Science., Ed., CSC Press Taylor & Francis Group, chap. 8, pp. 227-255, 2017 | 2017 | Chapitre |
Edward SUN
Comptabilité, Finance et EconomieEdward Sun est professeur senior en science des données et FinTech depuis 2018. Il a obtenu son doctorat (Dr. rer. pol.) en statistique et finance mathématique avec mention summa cum laude à l'Université de Karlsruhe (TH), l'une des trois premières universités d'élite. en Allemagne, en 2007 après avoir obtenu son BSc. et MSc. en Allemagne. En 2018, le Dr Sun a obtenu l'HDR en Sciences de Gestion de l'Université de Bordeaux, France. Son directeur de thèse principal est le professeur émérite de l'UCSB, aux États-Unis, qui a terminé le Dr. Sci. sous la direction de Leonid Kantorovich, lauréat du prix Nobel (1975) d'économie ; et un autre superviseur est le professeur émérite de l'Université de Yale, aux États-Unis, qui a coécrit avec les lauréats du prix Nobel, Franco Modigliani (1985) et Harry Markowitz (1990). Les intérêts de recherche du professeur Sun sont les mathématiques appliquées et la recherche opérationnelle, l'intelligence artificielle, l'analyse commerciale et décisionnelle, la science des données et l'ingénierie (Big) Data, les SIG, la gestion des opérations et la finance mathématique.