Zaid Saeed Khan is an Assistant Professor of Operations at SDSB, LUMS. He holds a PhD in Transportation Systems from New York University (NYU), an MS in Computation for Design & Optimization from Massachusetts Institute of Technology (MIT), and a BS in Computer Science from LUMS. At SDSB, he teaches courses in operations and transportation management, having previously taught in the Computer Science department at LUMS.
Zaid’s research explores how emerging technologies can address critical urban mobility and logistics challenges. His work centers on public transport operations, with a special focus on the use of autonomous modular vehicles to enhance network efficiency and reliability. Beyond this, his broader research interests include congestion pricing, sustainable transportation, traveler information systems, and supply chain optimization. He has published multiple peer-reviewed articles in top-tier transportation journals such as Transportation Research Part A, B, and C, with over 200 citations to date. He is deeply committed to interdisciplinary scholarship that bridges operations research, computer science, and urban mobility, and brings that same integrative perspective into his teaching and student mentorship.
Khan, Z. & Menendez, M. (2024). A Seamless Bus Network Without External Transfers Using Autonomous Modular Vehicles.. Transportation Research Part C: Emerging Technologies.
Khan, Z. & Menendez, M. (2023). Bus Splitting and Bus Holding: A New Strategy Using Autonomous Modular Buses For Preventing Bus Bunching.. Transportation Research Part A: Policy And Practice.
Khan, Z. & Menendez, M. (2023). No Time for Stopping: A Stop-Less Autonomous Modular (Slam) Bus Service.. Transportation Research Part C: Emerging Technologies.
Thodi, B., Khan, Z., Jabari, S. & Menéndez & Menéndez, M. (2022). Incorporating Kinematic Wave theory Into A Deep Learning Method For High-Resolution Traffic Speed Estimation.. IEEE Transactions on Intelligent Transportation Systems, 23 (10), 17849-17862..
Khan, Z., He,, W. & Menendez, M. (2022). Application of Modular Vehicle Technology to Mitigate Bus Bunching.. Transportation Research Part C: Emerging Technologies, 146 (103953.).
Khan, Z. (2018). Bottleneck Model With Heterogeneous information. Transportation Research Part B: Methodological, 112, 157-190.
Khan, Z. & Menendez, M. (2023). Bye Bye To Bus Bunching: A New Solution Integrating The Splitting And Holding Of Autonomous Modular Buses.. 102nd Annual Meeting of the Transportation Research Board, Washington DC, United States of America.
Khan, Z. & Menendez, M. (2023). Beating Bus Bunching By Combining The Splitting And Holding Of Autonomous Modular Buses. In Transportation Research Board Committee on Traffic Flow Theory and Characteristics Midyear Meeting, Amsterdam, Netherlands., Amsterdam, Netherlands.
Khan, Z., He,, W. & Menendez, M. (2022). Application of Modular Vehicle Technology to Mitigate Bus Bunching.. In 101st Annual Meeting of the Transportation Research Board, Washington DC, United States of America.
Khan, Z. & Menendez, M. (2022). Using Autonomous Modular Buses To Mitigate Bus Bunching.. In UAE Graduate Student Research Conference, Dubai, United Arab Emirates.
Khan, Z. & Menendez, M. (2022). A Stop-Less Bus Service Paradigm Using Autonomous Modular Buses.. In 4th Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS),, Dresdan, Germany.
Khan, Z. & Menendez, M. (2022). A Combined Bus Splitting And Holding Strategy to Prevent Bus Bunching Using Autonomous Modular Buses.. In 10th Symposium of the European Association for Research in Transportation (hEART)., Leuven, Belgium.
Thodi, B., Khan, Z., Jabari, S. & Menéndez & Menéndez, M. (2021). Anisotropic Kernels For Deep Convolutional Neural Network-Based Traffic Speed Reconstruction.. In 100th Annual Meeting of the Transportation Research Board, Washington DC, United States of America.
Thodi, B., Khan, Z., Jabari, S. & Menéndez & Menéndez, M. (2021). Learning Traffic Speed Dynamics From Visualizations.. In IEEE International Intelligent Transportation Systems Conference (ITSC), Indianapolis, IN, United States of America.
