Yanchao Liu

Yanchao Liu

Associate Professor, Industrial & Systems Engineering

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Yanchao Liu

Biography

Dr. Yanchao Liu is an Associate Professor in the Department of Industrial and Systems Engineering at Wayne State University. Dr. Liu received his Ph.D. degree from the University of Wisconsin-Madison, M.S. from the University of Arkansas, and B.S. from Huazhong University of Science and Technology, all in Industrial Engineering. Prior to joining Wayne State University in 2017, he was a Data Scientist and Manager of Advanced Analytics at Sears Holdings Corporation and Director of Brand Marketing Analytics at Catalina Marketing Corporation. Dr. Liu’s research focuses on developing mathematical models and computing algorithms to empower the next-generation air and ground transportation systems, data analytics platforms and industrial artificial intelligence (AI) applications. His research has been supported by the National Science Foundation and the State of Michigan. He is a recipient of the NSF Career Award.

Courses Taught

  • DSA/DSB/DSE 7500: Data Science Practicum, Spring/Summer 2020, 2021, 2022, 2023
  • IE 5995: IoT and Edge AI Programming, Winter 2022 - Present
  • DSA 6000: Data Science and Analytics, Fall 2017 - Present
  • IE 6210: Applied Engineering Statistics, Fall 2017 - Fall 2021
  • IE 7710: Introduction to Stochastic Processes, Fall 2019 - Present

Publications

Journal Papers

(* Starred authors are PhD advisees)

  • J. Xiang, J. Chen and Y. Liu (2023). Hybrid multi-scale search for dynamic planning of multi-agent drone traffic, Journal of Guidance,Control and Dynamics, 2023.
  • Y. Liu (2022). "Routing battery-constrained delivery drones in a depot network: a business model and its optimization-simulation assessment", Transportation Research Part C: Emerging Technologies, Volume 152, July 2023, 104147.
  • Z. Zhou*, Y. Liu, T. Hu, C. Wang (2023). "Two unsupervised learning algorithms for detecting abnormal inactivity within a household based on smart meter data", Expert Systems with Applications, Volume 230, November 2023, 120565.
  • Y. Liu (2022). "bsnsing: A decision tree induction method based on recursive optimal boolean rule composition", INFORMS Journal on Computing, 2022. (Software is available on CRAN)
  • Y. Liu (2022). "An elliptical cover problem in drone delivery network design and its solution algorithms", European Journal of Operational Research, April 2022.
  • Y. Liu (2022). "Two lower-bounding algorithms for the p-center problem in an area", Computational Urban Science, 2 (5), 2022.
  • P. Wu, J. Xie, Y. Liu, J. Chen (2022). "Risk-bounded and Fairness-aware Path Planning for Urban Air Mobility Operations under Uncertainty", Aerospace Science and Technology, Vol. 127, 107738, August 2022.
  • X. Geng, S. Li, J. Heo, Y. Peng, W. Hu, Y. Liu, J. Huang, Y. Ren, D. Li, L. Zhang and L. Luo (2022). "Grain-Boundary-Rich Noble Metal Nanoparticle Assemblies: Synthesis, Characterization, and Reactivity", Advanced Functional Materials, 2022, 2204169.
  • Y. Liu (2021). "A Multi-agent Semi-cooperative Unmanned Air Traffic Management Model with Separation Assurance", EURO Journal on Transportation and Logistics, Volume 10, 2021, 100058.
  • Y. Liu (2021). "A faster algorithm for the constrained minimum covering circle problem to expedite solving p-center problems in an irregularly shaped area with holes", Naval Research Logistics, 69(3), pages 431-441, 2022.
  • Z. Zhou* and Y. Liu (2021). "A smart landing platform with data-driven analytic procedures for UAV preflight safety diagnosis", IEEE Access.
  • Y. Liu (2021). “A note on solving DiDi’s driver-order matching problem”, Optimization Letters, 15, pp 109-125, 2021.
  • Z. Zhou*, J. Chen and Y. Liu (2020). “Optimized landing of drones in the context of congested air traffic and limited vertiports”, in print, IEEE Transactions on Intelligent Transportation Systems, 2020.
  • Y. Liu (2019). “A Progressive Motion Planning Algorithm and Traffic Flow Analysis for High-Density 2D Traffic”, Vol. 53, No. 6, Transportation Science, 2019
  • Y. Liu (2019). “An optimization-driven dynamic vehicle routing algorithm for on-demand meal delivery using drones”, Computers & Operations Research, Vol 111, 2019.
  • M. C. Ferris and Y. Liu (2016), “Modelling Demand Response in Organized Wholesale Energy Markets”, Optimization Methods & Software, vol 31:5, 2016.
  • Y. Liu, J. T. Holzer and M. C. Ferris (2015), “Extending the Bidding Format to Promote Demand Response”, Energy Policy, vol. 86, pp 82-92, 2015.
  • Y. Liu, M. C. Ferris and F. Zhao (2014). “Computational Study of Security Constrained Economic Dispatch with Multi-stage Rescheduling”, IEEE Transactions on Power Systems, vol.PP, no.99, pp.1-10, 2014.
  • Y. Liu and M. C. Ferris (2013), “Payment Rules for Unit Commitment Dispatch”, The Electricity Journal, 26(4):34-44, 2013.

Conference Papers

  • Y. Liu (2023). brif: A novel and efficient implementation of random forests based on bit packing and parallel computing, Proceedings of the IISE Annual Conference & Expo 2023, May 20-23, 2023, New Orleans, LA.
  • Z. Zhou* and Y. Liu (2022). "A scalable cloud-based UAV fleet management system", Lecture Notes in Mechanical Engineering (LNME), Proceedings of FAIM 2022, June 19-23, 2022, Detroit, USA.
  • Yanchao Liu and Michael C. Ferris, “Security-constrained Economic Dispatch using Semidefinite Programming”, Power & Energy Society (PES) General Meeting, Denver, CO, 2015.
  • Yanchao Liu, Michael C. Ferris, Feng Zhao, Tongxin Zheng and Eugene Litvinov, “A Stochastic Unit Commitment with Derand Technique for ISO’s Reserve Adequacy Assessment”, PES General Meeting, Denver, CO, 2015. (Best conference paper)
  • Manuel D. Rossetti and Yanchao Liu, “Simulating SKU Proliferation in a Health Care Supply Chain”, Proceedings of the 2009 Winter Simulation Conference (WSC), 2365-2374, 2009.
  • Yanchao Liu, John R. English and Edward A. Pohl, “Application of Gene Expression Program- ming in the Reliability of Consecutive-k-out-of-n:F Systems with Identical Component Reliabilities”, ICIC 2007: The 3rd International Conference on Intelligent Computing, Springer, 217-224, 2007.
  • Yanchao Liu, Liang Gao, Yan Dong and Baolin Pan, “A New Method for Finding Constant Terms in the Context of Gene Expression Programming”, Proceedings of the International Conference on Bio-Inspired Computing - Theory and Applications, BIC-TA, 195-200, 2006.

Professional Affiliations

 Member of INFORMS, IEEE, AUVSI, ASTM

Awards and Honors

  • NSF Career Award, 2020
  • Faculty Research Excellence Award, College of Engineering, Wayne State University, 2021
  • Best Conference Paper, IEEE Power & Energy Society (PES), 2015
  • Best Reviewer, IEEE Transactions on Smart Grid, 2015
  • Distinguished Bachelor’s Thesis Award, Hubei Province, China, 2006

Other Professional Experience

  • Director, Brand Marketing Analytics, Catalina USA, Schaumburg, IL 2017
  • Manager, Advanced Analytics, Sears Holdings Corporation, 2016-2017
  • Senior Analyst, Advanced Analytics, Sears Holdings Corporation, 2014-2016

Patents

U.S. Patent Pending: A Smart Landing Platform with Data-driven Analytic Procedures for Unmanned Multicopter Aircraft Pre-flight Diagnosis, U.S. Provisional Patent Application Serial No. 63/249,752. Co-inventor: Zhenyu Zhou.

Education

B.S. in Industrial Engineering, Huazhong University of Science and Technology, Wuhan, China, 2006

M.S. in Industrial Engineering, University of Arkansas, Fayetteville, AR, 2008

Ph.D. in Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, 2014

Courses taught by Yanchao Liu

Fall Term 2024 (future)

Winter Term 2024 (current)

Fall Term 2023

Winter Term 2023

Fall Term 2022

Winter Term 2022

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