Amin Vahedian Khezerlou

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PUBLICATIONS

       Vahedian, A., Zhou, X. (2021). Precise Bayes Classifier: Summary of Results. (Accepted *New) 21st IEEE International Conference on Data Mining (IEEE ICDM 2021), December 7-10, 2021, Auckland, New Zealand. Acceptance rate 9.9%.

       Vahedian, A., Zhou, X., Li, X., Street, W. N., Li, Y. (2021). DILSA+: Predicting Urban Dispersal Events Through Deep Survival Analysis with Enhanced Urban Features. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 12(4), 1-25.

       Vahedian, A., Zhou, X., Tong, L., Street, W.N. & Li, Y. (2019). Predicting Urban Dispersal Events: A Two- Stage Framework through Deep Survival Analysis on Mobility Data. In 2019 AAAI Conference on Artificial Intelligence (AAAI'19), January 27, 2019, Honolulu, HI, USA.

       Vahedian, A., Zhou, X., Tong, L., Li, Y., & Luo, J. (2019). Forecasting Gathering Events through Trajectory Destination Prediction: a Dynamic Hybrid Model. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE).

       Khezerlou, A. V., Zhou, X., Li, L., Shafiq, Z., Liu, A. X., & Zhang, F. (2017). A traffic flow approach to early detection of gathering events: Comprehensive results. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 8(6), 74.

       Zhou, X., Rong, H., Yang, C., Zhang, Q., Khezerlou, A.V., Zheng, H., Shafiq, Z., Liu, A.X. (2018). Optimizing Taxi Driver Profit Efficiency: A Spatial Network-based Markov Decision Process Approach. IEEE Transactions on Big Data (IEEE TBD).

       Vahedian, A., Zhou, X., Tong, L., Li, Y., & Luo, J. (2017, November). Forecasting gathering events through continuous destination prediction on big trajectory data. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (p. 34). ACM.

       Zhou, X., Khezerlou, A. V., Liu, A., Shafiq, Z., & Zhang, F. (2016, October). A traffic flow approach to early detection of gathering events. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (p. 4). ACM.

       Khezerlou, A. V., & Alizadeh, S. (2014). A New Model for Discovering Process Trees from Event Logs. Applied intelligence, 41(3), 725-735.

 

PEER-REVIEWED WORKSHOP ARTICLES

       Xiong, H., Vahedian, A., Zhou, X., Li, Y., & Luo, J. (2018). Predicting Traffic Congestion Propagation Patterns: A Propagation Graph Approach. In 11th ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS'18), November 6, 2018, Seattle, WA, USA.

       Chiu, J., Vahedian, A. & Zhou, X. (2018). Understanding Business Location Choice Pattern: A Co-Location Analysis on Urban POI Data. In 2nd INFORMS Workshop on Data Science, November 3, 2018, Phoenix, AZ, USA.

       Vahedian, A., Li, X., Xiong, H., Zhou, X., Colbert, A. (Oct. 2019). Motivated or Exhausted: A Data-Driven Study of Taxi Driver Behavior Following Traffic Congestions. 3rd INFORMS Workshop on Data Science. Seattle, Washington, USA.

 

ARTICLES UNDER REVIEW AND WORKING PAPERS

       Johnson, N., Prasad, S., Vahedian, A., Altay, N., Jain, A. (Revised. June 2021). Intelligent Pickings: From Rags to Riches. International Journal of Operations and Production Management.

       Vahedian, A., Zhou, X., Colbert, A. (Working paper). Effects of Traffic Congestion on Taxi Driver Motivation: A Novel Analysis of Empirical Distributions (Target Journal: ISR).