Director of General Software and Technology, Shenzhen Research Institute of Big Data
Lab Director for General Optimization Solver Development Lab
Adjunct Professor of Practice, School of Data Science, CUHK(Shenzhen)
Ph.D. Operations Research and Computer Science, Mass Institute of Technology, 1995
M.S. Master of Engineering in Computer Science, McMaster University, 1991
B.S. Software Engineering in Computer Science, Peking University, 1990
The Primal-dual Subproblem Column Generation Approach for the Pairing Optimizer, Airline Operations Recovery/Pricing and Revenue Management, Continuous Linear Programs, Algorithms for Manufacturing Systems, Applied Statistics, Combinatorial Optimization
Professor Xiaodong Luo is the director of general software and technology at Shenzhen research institute of big data. He is also a professor of practice at the Chinese University of Hong Kong Shenzhen. He studied software engineering at Peking University with a bachelor’s degree and then graduated from McMaster University with a master’s degree, majoring in Computer Science. Professor Luo got his Ph.D. in Operations Research and Computer Science at Mass Institute of Technology.
Professor Luo has over twenty-five years of industry experience, with close to twenty years in the airline industry and six years in Supply Chain management. In crew scheduling, Professor Luo spearheaded the implementation of the primal-dual subproblem column generation approach for the pairing optimizer. For airline operations recovery, Professor Luo worked with Sabre recovery ops product team as well as 3-4 summer interns on improving the speed and solution quality of the Sabre recovery suite of products. Also, He was a part-time lecturer for the computer science undergraduate course “UML-Object Oriented Analysis and programming.”
He can model complex business problems, conduct algorithmic design and coding, perform product support as well as help customers adopting advanced decision support systems. He has made improvements to many optimization engines by speeding them up, making them more scalable, and enabling them to produce more robust, better-quality solutions. He has nurtured many academic connections, collaborating with many high-quality operational researchers, many of these collaborations bring advancement to the state of the art of the field. Over the years, he has directed more than a dozen successful summer intern projects and has helped many of his co-workers get off the ground with applied research. He has won quite a few awards, has written more than a dozen technical papers, and has given many technical talks.
- “A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming，” Qinyu Han, Linxin Yang, Qian Chen, Akang Wang, Ruoyu Sun, Xiaodong Luo，Proceedings of Machine Learning Research Conf. Paper (accepted)，2023
- “Aircraft Routing Recovery Optimization with Cruise Speed Control,” Haohao Liu, Zhouchun Huang, Xiaodong Luo, Yinxiao Hu, Jie Ding，Aeronautical Computing Technique, 2023/01/30
- “The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights,” Xiaodong Luo and many other co-authors, Proceedings of Machine Learning Research，2022/02/01
- “Variable Pricing: An Integrated Airline Pricing and Revenue Management Model,” Miju Ahn, Xiaodong Luo and Sergey Shebalov. Journal of Revenue & Pricing Management, April 2020.
- “An Iterative Cost-driven Copy Generation Approach for Aircraft Recovery Problem,” Zhouchun Huang, Xiaodong Luo, Xianfei Jin and Sureshan Karichery. Preprint, submitted for publication to Transportation Research, Part B, September 2019.
- “Joint forecasting for airline pricing and revenue management,” Kavitha Balaiyan, Rk Amit, Atul Kumar, Xiaodong Luo and Amit Agarwal. Journal of Revenue & Pricing Management, Volume 14(number 6), March 2019.
- “Airline Crew Augmentation: Decades of Improvements from Sabre,” Xiaodong Luo, Yogesh Dashora and Tina Shaw. INFORMS Journal on Applied Analytics, Vol. 45, No. 5, October 2015.
- “Iterative Methods for Large Markov Decision Problems,” Xiaodong Luo. Preprint, January 2015.
- “Efficient Implementation of Quasi- Maximum-Likelihood Detection Based on Semidefinite Relaxation,” Mikalai Kisialiou, Xiaodong Luo and Zhi-Quan Tom Luo. IEEE Transactions on Signal Processing, 57(12):4811-4822, December 2009.
- “An efficient quasi-maximum likelihood decoder for PSK signals,” and Zhi-Quan (Tom) Luo, Xiaodong Luo and Mikalai Kisialiou, Proceedings for 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing. (ICASSP '03), 6-10 April 2003.
- “A New Algorithm for State-Constrained Separated Continuous Linear Programs,” Xiaodong Luo and Dimitris Bertsimas. SIAM Journal on Control and Optimizations, Volume 37, Number 1, pp. 177-210, 1998.
- “Conditions for a Projection-Type Error Bound for the Linear Complementarity Problem to Be Global,” Paul Tseng and Xiaodong Luo. Linear Algebra and Its Applications, 253 (1-3) (1997) pp. 251-278.
- “Continuous linear programming: theory, algorithms and applications,” Xiao-Dong Luo. Ph.D. Thesis, Massachusetts Institute of Technology, Sloan School of Management, 1995.
- “Extension of Hoffman’s Error Bound to Polynomial Systems,” Zhi-Quan Luo and Xiaodong Luo. SIAM Journal on Optimization, Vol. 4, No. 2, pp. 383-392, May 1994.
- “Worst Case Complexity of Potential Reduction Algorithms for Linear Programming,” Dimitris Bertsimas and Xiaodong Luo. Mathematical Programming 77(2), January 1993.
- “An error analysis of the fast recursive least squares algorithms,” Xiaodong Luo and Shanzhen Qiao. Technical report no. 231, Comm. Res. Lab., McMaster University, Hamilton, Ontario, Canada, 1991