We are always looking for highly-motivated students and postdocs who want to work with us! For more information, click here!
Welcome to the group M3Nets (Multi-Modal Mobility Networks) at Beihang University!
Our focus is on developing scalable algorithms and analysis techniques for large transportation networks, with a particular focus on air transportation. Using novel data science methods, we are trying to bridge the gap between theoretical analysis (what should individual passengers be doing) and practice (what are passengers actually doing?).
- December 4th, 2017: The journal IEEE Transactions on Intelligent Transportation Systems has accepted our study ADS-BI: Compressed Indexing of ADS-B Data, where we propose a novel compressed index structure for managing and querying ADS-B aircraft data at a large scale.
- November 8th, 2017: The journal Safety Science has accepted our study Complementary Strengths of Airlines under Network Disruptions, which investigates the robustness of more than 200 global airline networks and estimates how much possible disruptions can be absorbed by other airlines using the notion of static complementary strength.
- October 31st, 2017: The Journal of Advanced Transportation has accepted our study Finding p-hub median locations: An empirical study on problems and solution techniques, in which we implement and evaluate several widely-used methods for solving five standard hub location problems. Our work helps other researchers to get an overview on the best solution techniques for the problems investigated in our study.
- January 10th, 2017: We have received funding from the Young Thousand Talents Plan of China (青年千人计划).
- January 1st, 2017: We have received funding for two NSFC projects.
- The first project, MaoDunNet, studies the robustness of complex networks.
- The second project studies the analysis and improvement of air transportation systems.