Montpellier Business School

Dr. Chen Yi-Ting

Chen Yi-Ting
Fonction Associate professor
Research themes AI and Machine Learning, Big Data, Business and Decision Analytics, Computer Science, Information Technology, Operations Research
Teaching department Sustainable development management: economy, human resources and diversity


Selected intellectual contributions

Chen Y. T., Sun E., Chang M.F. & Lin Y.B. 2021. 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, 238: 108157.

Chen Y.T., Sun E.W. & Lin Y.B. 2020. Machine learning with parallel neural networks for analyzing and forecasting electricity demand. Computational Economics. 56(2): 569–597.

Lai W., Chen YT & Sun EW (2021). Comonotonicity and low volatility effect. Annals of Operations Research. 299 (1-2): 1057-1099.

Chen Y.T., Sun E.W. & Lin Y.B. 2020. Merging anomalous data usage in wireless mobile telecommunications: Business analytics with a strategy-focused data-driven approach for sustainability. European Journal of Operational Research,
281(3): 687-705.

Sun E.W., Kruse T. & Chen Y.T. 2019. Stylized algorithmic trading: satisfying the predictive near-term demand of liquidity. Annals of Operations Research. 281(1/2): 315–347.

Chen Y.T., Lai W. & Sun E.W. 2019. Jump detection and noise separation by a singular wavelet method for predictive analytics of high-frequency data. Computational Economics. 54(2): 809–844.

Chen Y.T., Sun E.W. & Lin Y.B. 2019. Coherent quality management for big data systems: a dynamic approach for stochastic time consistency. Annals of Operations Research. 277 (1): 3–32.

Chen Y.T. & Sun E.W. 2018. Automated business analytics for artificial intelligence in Big Data @X 4.0 Era. In Dehmer, M. and Emmert-Streib, F. (Eds.) Frontiers in Data Science, 223-251. CRC Press.

Chen Y.T, Sun E.W. & Yu, M.T. 2018. Risk assessment with wavelet feature engineering for high-frequency portfolio trading. Computational Economics. 52(2): 653–684.

Contact us
Preferred contact method(Nécessaire)
Ce champ n’est utilisé qu’à des fins de validation et devrait rester inchangé.
Je préfère être contacté par(Nécessaire)
Ce champ n’est utilisé qu’à des fins de validation et devrait rester inchangé.