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Dr. Kuilin Zhang
Associate Professor, Department of Civil, Environmental, and Geospatial Engineering, College of Engineering
Affiliated Associate Professor in the Department of Computer Science in the College of Computing
Michigan Technological University
office: Dillman 301i
SITS-Lab: Dow 842
Address: 1400 Townsend Dr., Houghton, MI 49931
Email: klzhang@mtu.edu
Telephone: 906-487-1828
orcid: https://orcid.org/0000-0002-8180-5016
Dr. Kuilin Zhang is Associate Professor in the Department of Civil, Environmental, and Geospatial Engineering (CEGE) in the College of Engineering, and Affiliated Associate Professor in the Department of Computer Science (CS) in the College of Computing at Michigan Technological University (Michigan Tech), Houghton, Michigan, U.S.A. Dr. Zhang is also a faculty affiliate to Michigan Tech Transportation Institute (MTTI), Institute of Computing and Cybersystems (ICC), and Center for Agile Interconnected Microgrids (AIM).
Dr. Zhang received his Ph.D. degree in Transportation Systems Analysis and Planning from the Department of Civil and Environmental Engineering at Northwestern University in December 2009. After working as a Postdoctoral Fellow in the Transportation Center at Northwestern, he joined the Energy Systems Division at Argonne National Laboratory as a Postdoctoral Appointee in November 2010. He joined Michigan Tech in August 2013 through the university-wide Strategic Faculty Hiring Initiatives (SFHI) in Multimodal Transportation Systems.
Dr. Zhang is a member of the Transportation Research Board (TRB) standing committees of Transportation Network Modeling (ADB30) and Freight Transportation Planning and Logistics (AT015), as well as a voting member of the Society of Automotive Engineers (SAE) Cooperative Driving Automation (CDA) Committee and BSM Task Force. He is also a member of IEEE, INFORMS, and ITE. Dr. Zhang was a recipient of the NSF CAREER Award in 2019. He and his student also received the 2022 Gartner Prize for the "Best Paper on Traffic Flow Theory" from TRB ACP50 Traffic Flow Theory and Characteristics Committee at TRB Annual Meeting 2023.
announcement
PhD. Research Assistants with Full Scholarship Openings:
Multiple hourly research assistant positions are available in the area of Connected and Automated Vehicles (CAV) for Michigan Tech undergraduate students who know C++ programming and wireless communication. NEW
Multiple Ph.D. positions and one Postdoc are available. NEW
Area 1: Connected and Automated Vehicles (CAVs) - 2 Ph.D. students. Required skills - C++ programming and wireless communication.
Area 2: Intermodal Logistics Modeling - 2 Ph.D. students and one Postdoc (2 years) - Required skills - C++ programming and optimization.
We are excited to receive the DOE ARPA-e INTERMODAL grant for 30 months, $1.2M. Argonne National Lab is also on our team. We will develop an intermodal logistical modeling platform to reduce time, cost, and energy usage under disruptions to provide more resilient and greener transportation and logistics service for shipping containers from ports to warehouses for the entire US up to 2050, with renewable transportation energy charging/fueling facilities in consideration to achieve the Net Zero vision for the decarbonized world. NEW
Our paper "Leveraging Connected Vehicle Platooning Technology to Improve the Efficiency and Effectiveness of Train Fleeting under Moving Blocks" has been accepted for publication by Transportation Research Part C: Emerging Technologies. This work is a collaborative work with colleagues from UIUC, UIC, and Vanderbilt for our USDOT FRA project on train platooning. Ph.D. student - Yun-Chu Hung is a student author for this paper. Congratulations to Yun-Chu! NEW
We are honored to receive the 2022 Gartner Prize for the "Best Paper on Traffic Flow Theory" from TRB ACP50 Traffic Flow Theory and Characteristics Committee at TRB Annual Meeting 2023. Congratulations to Ph.D. student - Yingtong Tan. NEW
Our paper "The Impact of Cooperative Adaptive Cruise Control on Traffic Stability" has been accepted for publication by Transportation Research Record: Journal of Transportation Research Board. Congratulations to Ph.D. student Yun-Chu Hung for her first publication. This research has been supported by the NSF CAREER Award.
Our paper "A Real-Time Distributed Cooperative Adaptive Cruise Control Model Considering Time Delays and Actuator Lag" has been accepted for publication by Transportation Research Record: Journal of Transportation Research Board. Congratulations to Ph.D. student Yingtong Tan for her first publication. This research has been supported by the NSF CAREER Award.
Two papers have been presented in the TRB 101st Annual Meeting, January 8-13, 2022, Washington, DC.
A Real-Time Distributed Cooperative Adaptive Cruise Control Model Considering Time Delays and Actuator Lag (with Y. Tan) - submitted to ACP50 Traffic Flow Theory and Characteristics committee
The Impact of Connected and Automated Vehicles on Traffic Stability (with Y. Hung) - submitted to ACP50 Traffic Flow Theory and Characteristics committee
Dr. Zhang received a research grant from US DOT FRA on "Railroad Crossing Vehicle Warning (RCVW) Application Demonstrations with Connected Vehicles" as a co-PI. The project starts in September 2021 and ends August 2023.
Welcome Yiming Yang to join Dr. Zhang's group as a Ph.D. student in Fall 2021. Yiming is from Chang'an University, Xi'an, Shaanxi, China. He received his BS and MS degree in Control Science and Engineering. Yiming worked on autonomous vehicle driving control during his graduate study at Chang'an University. At Michigan Tech, his research interest focuses on applying control theory and machine learning to connected and automated vehicles, and on-road vehicle testing.
Dr. Zhang was invited to talk in the Distinguished Speaker Webinar in the C2SMART (Connected Cities with Smart Transportation) at New York University, New York, NY, on May 13, 2021.
Our paper "Online Predictive Connected and Automated Eco-Driving on Signalized Arterials Considering Traffic Control Devices and Road Geometry Constraints under Uncertain Traffic Conditions" has been accepted for publication on Transportation Research Part B. You can access the 50 day's free article via my personalized share link. This research has been supported by the NSF CAREER Award.
https://www.sciencedaily.com/releases/2021/03/210302185412.htm
https://www.eletimes.com/cooperative-eco-driving-automation-improves-energy-efficiency-and-safety
https://techxplore.com/news/2021-03-cooperative-eco-driving-automation-energy-efficiency.html
https://scienmag.com/cooperative-eco-driving-automation-improves-energy-efficiency-and-safety/d.htm
Congratulations Ali for receiving a Doctoral Finishing Fellowship Award!
Our paper "A Distributionally Robust Stochastic Optimization-based Model Predictive Control with Distributionally Robust Chance Constraints for Cooperative Adaptive Cruise Control under Uncertain Traffic Conditions" is online for free access in 50 days on a prestigious journal - Transportation Research Part B. This research has been supported by the NSF CAREER Award.
https://www.sciencedaily.com/releases/2020/09/200929123704.htm
https://techxplore.com/news/2020-09-smart-cruise-drivers-decisions.html
https://www.newswise.com/articles/smart-cruise-control-steers-drivers-toward-better-decisions
https://www.selfdrivingcars360.com/what-lies-ahead-cooperative-data-driven-automated-driving/
Congratulations to Ali Jalooli, a Ph.D. student from Computer Science co-advised with Dr. Min Song from Stevens Institute of Technology, who has successfully passed his dissertation defense on May 20, 2020. Dr. Laura Brown from the CS Department and Dr. Zhaohui Wang from the ECE Department are served as a committee member. The dissertation topic is "Enabling technologies for the internet of things: optimized networking for connected and autonomous vehicles." Ali will join the Department of Computer Science at California State University - Dominguez Hills as a tenure-track assistant professor in Fall 2020.
Media coverage: Cloud Sourcing Electricity Usage - how to relate human activities in a building to energy consumption? This covers our paper published on IEEE Transactions on Smart Grid, collaborated with a power systems expert, Professor Chee-Wooi Ten in the Department of Electrical and Computer Engineering at Michigan Tech. Dr. Shuaidong Zhao, a recent Ph.D. student of Dr. Zhang and currently a senior quantitative analyst in the Advanced Data & Analytics Team at National Grid US, is a co-author of this paper.
Congratulations to Ali Jalooli, a Ph.D. student from Computer Science, for accepting a tenure-track assistant professor position in the Department of Computer Science at California State University, Dominguez Hills. Ali is co-advised by Dr. Min Song at Stevens Institute of Technology and Dr. Zhang. Ali's dissertation topic focuses on vehicular ad-hoc networks for connected and automated vehicles. Ali will defend his dissertation in May 2020 and start his faculty career in Fall 2020.
Ph.D. students Qinjie Lyu and Yingtong Tan presented at the poster session in the Michigan Traffic Safety Summit, at East Lansing, MI, March 9-11, 2020
Safety and energy benefits of connected and automated vehicles (CAVs) - a case study in the Houghton CAV testbed using CARDS (Qinjie Lyu)
Improving driving safety and efficiency at grade crossings via highway-rail connectivity (Yingtong Tan)
Our paper on "A Novel Clustering Scheme for Heterogeneous Vehicular Networks" has been accepted for presentation at the IEEE ICC 2020, June 7 – 11, in Dublin, Ireland and for publication in its proceedings. Congratulations Ali.
Dr. Zhang received a research grant from US DOT FRA on "Leveraging Connected Highway Vehicle Platooning Technology to Improve the Efficiency and Effectiveness of Train Fleeting" as a subaward from the University of Illinois Urbana Champaign (UIUC).
Welcome Yun-Chu Hung to join Dr. Zhang's group as a Ph.D. student. Yun-Chu is from National Chiao Tung University (NCTU), Hsinchu, Taiwan. NCTU's transportation program has been recognized as the top one in Taiwan. Yun-Chun received her BS degree in Transportation and Logistics Management and MS degree in Traffic and Transportation from NCTU. Her research interest focuses on applying operations research and machine learning to connected and automated vehicles and intelligent transportation systems.
Dr. Zhang attended the 2019 INFORMS Annual Meeting, Seattle, WA
Chaired a TSL/ITS Session on "Optimization and Control Models for Connected and Automated Vehicles"
Presented in two TSL oral sessions:
Presented in one RAS poster session:
Data-driven Study on the Log Movements for the Upper Midwest: Impact of Rail Car Fleet Size on Freight Storage and Car Idling (with Sangpil Ko and Pasi Lautala)
Dr. Zhang received a research grant from US DOT FRA on "Developing Safe and Efficient Driving and Routing Strategies at Railroad Grade Crossing Based on Highway-Railway Connectivity" as a PI. Dr. Pasi Lautala, the Director of the Rail Program at Michigan Tech and Dr. Reg Souleyrette, Professor and Civil Engineering Department Chair at UKY are co-PIs. This project is a two-year project with $567,230 budget. Ph.D. students who are interested in connected and automated vehicles (CAVs) modeling and road testing and grade crossing signal control are welcome to apply for the research scholarships.
Our paper on "Establishment of Enhanced Load Modeling by Correlating with Occupancy Information" has been accepted for publication in IEEE Transactions on Smart Grid (Impact Factor: 10.486). This paper is a joint work with Dr. Chee-Wooi Ten's Power Systems Group with his recent student Dr. Yachen Tang in the Electrical and Computer Engineering Department at Michigan Tech. Dr. Zhang's recent student Dr. Shuaidong Zhao, Senior Quantitative Analyst at National Grid US also worked on this paper.
Dr. Zhang presented in an invited seminar on "Improve Observability of Dynamic Traffic System Using Connected Vehicle Data" at Ford Motor Company in Dearborn, MI, on August 30, 2019.
Welcome Yingtong Tan to join Dr. Zhang's research team as a Ph.D. student. Yingtong is from South China University of Technology (SCUT). She received her BS degree in Automation and MS degree in Control Theory and Control Engineering in the School of Automation Science and Technology at SCUT. Her research interests focus on applying optimization, control, and machine learning to connected and automated vehicles.
Dr. Zhang has been promoted to a tenured associate professor in August 2019.
High school student Sara Stawarz from Livonia, MI, worked as a STEM Summer Intern with Dr. Zhang and Ph.D. Qinjie Lyu on a 5-day project "Connected and Automated Vehicle Eco-Driving at a Signalized Intersection", July 15-19, 2019.
Dr. Zhang's research group hosted 24 middle and high school students for the Summer Youth Program (SYP) on using smartphone app - Traffic Counter for traffic volume studies using data collection and analytics. July 16 and July 23, 2019.
Dr. Zhang had a presentation on "An integrated network fleet and routing optimization model for on-demand shared mobility systems using connected and automated vehicles" in the Breakout Session "Enabling Transportation Network: From Individual Vehicle Motion Control to Network Fleet Management" at 2019 Automated Vehicle Symposium (AVS 2019) in Orlando, FL, July 15-18.
Dr. Zhang was invited to attend the National Science Foundation Workshop on Control for Networked Transportation Systems (CNTS) in Philadelphia, Pennsylvania, July 8 - 9, 2019.
Media Coverage on recent Ph.D. student Dr. Shuaidong Zhao and Dr. Zhang's work on connected vehicle (CV) data - Filling in the gaps of connected car data helps transportation planners. This work was supported by an NSF grant on mobile sensing CMMI-CIS-1538105.
https://www.eurekalert.org/pub_releases/2019-04/mtu-fit042519.php
https://www.sciencedaily.com/releases/2019/04/190426075435.htm
http://affinis.us/5-new-things-autonomous-connected-vehicles/
https://mobility21.cmu.edu/filling-in-the-gaps-of-connected-car-data-helps-transportation-planners/
https://www.rdmag.com/news/2019/04/filling-gaps-connected-car-data-helps-transportation-planners
Dr. Zhang presented in the School of Business and Economics (SBE) Seminar at Michigan Tech on April 17, 2019 on A Best-Case Rosenthal Equilibrium based Coordination Mechanism for N-person Online Routing Games of Connected and Automated Vehicles, which is a paper with Ph.D. student Qinjie Lyu. .
Dr. Zhang will present a connected and automated routing and driving system (CARDS) for modeling and simulation connected and automated vehicles under different traffic congestion levels at American Center for Mobility (ACM) for the ARPA-e NEXTCAR project for energy efficient driving on May 8, 2019.
MTU News on the NSF CAREER Award - Kuilin Zhang Wins CAREER Award for Connected and Autonomous Vehicles. Thanks Allison Mills @aw_mills!
TR-C paper "A distributionally robust optimization approach to reconstructing missing locations and paths using high-frequency trajectory data" is online. 50-day free access link is here. This work is supported by an NSF award CMMI-CIS-1538105.
HERE Technologies, the leading map and location data company in the world, is collaborating with Dr. Zhang by providing HD Live Map samples for Connected and Automated Vehicle (CAV) Research. Dr. Zhang will demonstrate how to use HD Live Map data for simulation and modeling connected and automated vehicles in his NSF CAREER project. Thanks HERE.
Dr. Kuilin Zhang has received an NSF CAREER award titled "CAREER: Tackling Congestion in Smart Cities via Data-Driven Optimization-Based Control of Connected and Automated Vehicles". Ph.D. Positions are available.
Dr. Kuilin Zhang serves as a Panel member for the NCHRP 14-42 project on "Determining the Impact of Connected and Automated Vehicle Technology on State DOT Maintenance Programs"
Dr. Kuilin Zhang has received a new grant on using Drones to monitor traffic dynamics for MDOT as a co-PI for the project "Integration of Unmanned Aerial Systems Data Collection into Day-to-Day Usage for Transportation Infrastructure". The project is a a three-year project (budget is $871,000) led by Mr. Brooks as a PI from MTRI.
Ph.D. Student Qinjie Lyu presented her first poster at the 98th TRB Annual Meeting in Washington, DC, January 13-17, 2019.
My first Ph.D. student Shuaidong Zhao successfully passed his dissertation defense on November 1, 2018. Congratulations to Dr. Zhao! Shuaidong has started his role as a Senior Quantitative Analyst in the Advanced Data & Analytics Team at National Grid US in New York, NY in January 2019.
Congratulations to Ph.D. Student Shuaidong Zhao for receiving the prestigious Outstanding Scholarship Award from the Graduate School at Michigan Tech in 2018.
Two papers have been presented in TRB 98th Annual Meeting, January 13-17, 2019, Washington, DC.
A Data-Driven Optimization based Model Predictive Control for Real-Time ECO Approach and Departure at Signalized Intersections under Uncertain Traffic Conditions (with S. Zhao) - submitted for presentation only to AHB45 Traffic Flow Theory and Characteristics committee
A Best-Case Rosenthal Equilibrium based Coordination Mechanism for N-person Online Routing Games of Connected and Automated Vehicles (with Q. Lyu) - submitted for presentation only to ADB30 Transportation Network Modeling Committee
Congratulations to Ph.D. student Shuaidong Zhao for receiving the Doctoral Finishing Fellowship from the College of Engineering. Shuaidong will have his final Ph.D. Dissertation Defense in November 1, 2018. Shuaidong will join National Grid US as a Senior Quantitative Analyst in December 2018.
Dr. Zhang was an organizer of a breakout session on Artificial Intelligence and Deep Machine Learning Tools and Algorithms for Automated Vehicles: The State of the Art and Practice in the Automated Vehicles Symposium (AVS), July 9-12, 2018, San Francisco, CA.
Ali Jalooli has formally joined the SITS-Lab. Ali is a Ph.D. student in the Department of Computer Science at Michigan Tech. Ali's research interests focus on fundamental theories to integrate vehicle ad-hoc networks and traffic flow networks for connected and automated vehicles. Dr. Min Song from Stevens Institute of Technology is Ali's co-advisor.
Our semi-automated annotation tool for UAV traffic monitoring is available online on YouTube. Thanks for Qinjie's excellent job.
Congratulations to Ph.D. student Shuaidong Zhao for receiving the Wilbur Haas Graduate Research Excellence Award in 2018. The award is made annually to graduate level students in civil or environmental engineering to recognize outstanding student scholarship and research contributions in the Department of Civil and Environmental Engineering at Michigan Tech.
Congratulations to my first Ph.D. student Shuaidong Zhao for accepting a job offer from National Grid US, New York, NY. Shuaidong will work as a Senior Quantitative Analyst in the Advanced Data & Analytics Team at National Grid US starting January 2019. Shuaidong will work on integrating transportation network and power grid systems modeling and analysis.
Dr. Zhang started to work with Dr. Lautala as a co-PI on a freight logistics project: Log Movement in the Superior Region – Rate and Capacity Based Analysis of Modal Shares, sponsored by Michigan Economic Development Corporation (MEDC) and Michigan Department of Transportation (MDOT) to look into how railway can help forest products logistics and transportation in the greater Superior region using log movement data from yards to mills.
Three papers have been presented in TRB 97th Annual Meeting, January 7-11, 2018, Washington, DC.
A data-driven Model Predictive Control framework for robust Cooperative Adaptive Cruise Control using mobile sensing data (with Zhao, S.)
A data-driven dynamic route choice model under uncertainty using connected vehicle trajectory data (with Zhao, S.)
A comprehensive overview of improving traffic flow observability using UAVs as mobile sensors (with Zhao, S. Brooks, C., et al.)
Dr. Kuilin Zhang is now Affiliate Assistant Professor in the Department of Computer Science at Michigan Tech. He will collaborate with CS faculty and advise CS graduate students for big data analytics, connected and automated vehicles, and high-performance computing.
A research paper - Observing Individual Dynamic Choices of Activity Chains from Location-based Crowdsourced Data, collaborated with Ph.D. student Shuaidong Zhao, has been accepted by Transportation Research Part C. This work is supported by NSF project CMMI-CIS-1538105.
DOE ARPA-e has put the MTU NEXTCAR project as the only one over 10 teams in their project spotlight - Traveling Smarter While Saving Energy, on June 22, 2017.
Ph.D. student Qinjie Lyu has joined our research team since Summer 2017. Qinjie was a Ph.D. candidate in Information and Communication Engineering at Beijing University of Posts and Telecommunications (BUPT). She will bring her expertise in wireless communication and machine learning to our on-going projects in connected and automated vehicles (CAV) and UAV mobile sensing. Welcome Qinjie to Houghton!
The eight Chevrolet Volt cars from GM are on campus at Michigan Tech now. We start to connect these cars through LTE and DSRC, and equip them with GPS and other sensors. We start to collect connected vehicle data in real-time for developing the connected and automated routing and driving systems (CARDS).
Dr. Zhang has served as a scientist client of the CS4760/CS5760: Human-Computer Interactions & Usability course in Spring 2017 to develop an app for mobile sensing from crowds to observe individual person activity-travel tracking system (iPATTS). A 6 CS undergraduate students will work as a team (Team iPatts) to design and implement the app idea, and 3 CS graduate students will work as consultants of this project. Dr. Zhang will meet with the team regularly throughout the development of the app. This app will be used in Dr. Zhang's Transportation Planning class in Fall 2017 for data collection. This app will be an example to integrating research and education from Dr. Zhang's on-going NSF CMMI-CIS-1538105 project on mobile sensing and crowdsourced data.
Two papers were presented in TRB 96th Annual Meeting, January 8-12, 2017, Washington, DC.
A Data-Driven Optimization Model to Observe Individual Dynamic Choices of Activity-Travel-Path using Connected Vehicles as Mobile Sensors (with Zhao, S.)
Observing Space-Time Queueing Dynamics at a Signalized Intersection using Vehicles as Mobile Sensors (with Zhao, S.)
Dr. Kuilin Zhang presented at INFORMS Annual Meeting, November 12-15, 2016, Nashville, TN
Modeling Plug-in Electric Vehicles Driving and Charging Behavior using Real-World Connected Vehicles Data
Dr. Kuilin Zhang has been awarded a $2.8M three-year project from US DOE ARPA-E NEXTCAR program as a co-PI on "Connected and Automated Control for Vehicle Dynamics and Powertrain Operation on a Light-Duty Multi-Mode Plug-in Hybrid Electric Vehicle".
MTU news - Michigan Tech Automotive Energy Efficiency Research Receives Federal Award of $2.8 Million from US Department of Energy
HybridCARS - ARPA-E Funding $32Million for 10 Reduced-Energy Vehicles Projects.
DOE - DOE Announces 10 New Projects to Improve Connected and Automated Vehicle Efficiency.
Dr. Kuilin Zhang will work with the RSG Inc for a two-year project on improving the Statewide Passenger and Freight Travel Demand Model for Michigan DOT.
The Traffic Network Observability website has been launched for the NSF project collaborated with Arizona State University and Michigan Tech Research Institute. YouTube channel and Github repository are also established to disseminate the research outcomes.
Dr. Kuilin Zhang has been appointed as the Committee Research Coordinator (CRC) for the TRB Standing Committee on Freight Transportation Planning and Logistics (AT015) starting May 2016. As the CRC, Dr. Zhang will provide assistance to TRB committees in developing and maintaining robust research portfolios.
Dr. Kuilin Zhang has received a two-year project from Michigan DOT as a co-PI on Implementation of Unmanned Aerial Vehicles (UAVs) for Assessment of Transportation Infrastructure - Phase II starting from March 2016. Dr. Zhang will collaborate with PI Colin Brooks from MTRI and other four Tech professors to work on this exciting project. Dr. Zhang will be in charge of using UAVs to observe traffic flow dynamics, which applies the theoretical models and algorithms derived from his on-going NSF project collaborating with Colin Brooks (co-PI).
Dr. Kuilin Zhang has received a two-year project from US DOT FTA on Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events starting from December 2015. Dr. Zhang will collaborate with three Chicago-based universities including the University of Chicago (Argonne National Laboratory), the University of Illinois at Chicago, and Illinois Institute of Technology on this project. This project will be based on the POLARIS platform that Dr. Zhang was a key modeler and developer when he worked at Argonne National Laboratory.
Ph.D. Student Shuaidong Zhao had his first TRB presentation on observing individual dynamic choices of activity chains from location-based crowdsourced data in TRB 95th Annual Meeting, January 10-14, 2016, Washington, DC.
Dr. Kuilin Zhang is on the host committee of the 22nd International Symposium on Transportation and Traffic Theory (ISTTT 22), July 24-26, 2017, Evanston, IL.
Congratulations to Senior Patty Thompson in the CE4410 Transportation Planning class for her award of the prestigious 2015 Eisenhower Graduate Fellowship. Patty will study her graduate study at Iowa State University in Fall 2015.
Dr. Kuilin Zhang has been awarded his first NSF grant (1538105) from the NSF-CMMI-CIS program as a PI. This grant aims to improve spatial observability of dynamic traffic systems through active mobile sensor networks and crowdsouced data. Dr. Zhang will collaborate with researchers from Michigan Tech Research Institute and Arizona State University for this three-year project starting from June 15, 2015.
Dr. Kuilin Zhang has been appointed as a member of the Editorial Advisory Board of Transportation Research Part E - Logistics and Transportation Review for a three-year term (2015-2017)
Three papers have been presented in TRB 94th Annual Meeting, January 11 - 15, 2015, Washington, DC
Optimizing Multi-Layer Merge-In-Transit Supply Chains (with D. Yang). ADB30 Transportation Network Modeling Committee.
A Bayesian Adaptive Inference Approach to Estimating Heterogeneous Gap Acceptance Functions (with J. Zhu). AHB45 Traffic Flow Theory and Characteristics Committee.
POLARIS: Agent-Based Modeling Framework Development and Implementation for Integrated Travel Demand and Network and Operations Simulations (with J. Auld et al.). ADB40 Transportation Demand Forecasting Committee.
Dr. Kuilin Zhang presented in the Networks and Operations Session at the Northwestern University Transportation Center 60th Anniversary Celebration Technical Symposium, November 13-14, 2014, Evanston, IL
Dr. Kuilin Zhang presented at INFORMS Annual Meeting, November 8-12, 2014, San Francisco, CA
Reliable Mobile Sensor Network Design through Optimizing Packets Transmissions in VANETs
Enhancing Observability of Dynamic Traffic Systems: A Stochastic Linear Programming Approach
Dr. Kuilin Zhang chaired two sessions at INFORMS Annual Meeting, November 8 - 12, 2014, San Francisco, CA
RAS Session on Demand-Responsive Rail Service Design
TSL/ITS Session on Optimal Sensor Locations in Traffic Networks
Dr. Kuilin Zhang has been appointed as Webinar and Workshops Coordinator for TRB ADB30 Transportation Network Modeling Committee.
Dr. Kuilin Zhang was awarded Certificate of Reviewing Excellence for Transportation Research Part E: Logistics and Transportation Review, Elsevier, due to his contribution as a peer review in 2013.
Member of Program Committee: ACM SIGSPATIAL International Workshop on Computational Transportation Science, November 4-7, 2014, Dallas, TX
Presentation: Multi-Layer Pooling Supply Chain Design: Model Formulation and Solution Algorithms, Industrial & Systems Engineering Research Conference, May 31 - June 3, 2014, Palais des Congres de Montreal, Montreal, Canada.
Session Co-Chair: Modeling Theories and Practices in Freight Planning and Logistics, Part 1, 2014 Transportation Research Board (TRB) 93rd Annual Meeting, Jan 12-16, 2014, Washington, DC.