Vakul Nath is a graduate student in the Department of Computer Science at Vanderbilt University and works as a research assistant at the Institute for Software Integrated Systems. He received his Bachelor’s degree in Computer Science from Stetson University in May 2024.

Vakul Nath Publications

1. V. Nath, F. Liu, G. He, D. Rogers, A. Chhokra, J. P. Talusan, M. Ma, A. Mukhopadhyay, and A. Dubey, SchoolRide: A Data-Driven Platform for School Bus Disruption Management, in Proceedings of the HSCC/ICCPS 2026: 29th ACM International Conference on Hybrid Systems: Computation and Control and 17th ACM/IEEE International Conference on Cyber-Physical Systems, 2026.
   Bibtex Abstract

   @inproceedings{iccps2026_schoolride,
     author = {Nath, Vakul and Liu, Fangqi and He, Guocheng and Rogers, David and Chhokra, Ajay and Talusan, Jose Paolo and Ma, Meiyi and Mukhopadhyay, Ayan and Dubey, Abhishek},
     title = {SchoolRide: A Data-Driven Platform for School Bus Disruption Management},
     year = {2026},
     booktitle = {Proceedings of the HSCC/ICCPS 2026: 29th ACM International Conference on Hybrid Systems: Computation and Control and 17th ACM/IEEE International Conference on Cyber-Physical Systems},
     location = {Saint Malo, France},
     keywords = {school transportation, disruption management, combinatorial optimization, cyber-physical systems},
     note = {Acceptance rate: 28\%; Short Paper; Track: Systems and Applications},
     series = {HSCC/ICCPS '26}
   }
   

   As a societal-scale transportation Cyber-Physical System (CPS), school transportation integrates large-scale physical operations with cyber components for planning and control under uncertainty. Despite its scale and societal importance, the system remains vulnerable to operational disruptions such as vehicle breakdowns, road closures, traffic congestion, and driver absences. This work demonstrates how data-driven optimization can enhance operational resilience in a real-world school transit context. To advance research in this domain, we introduce SchoolRide, a platform developed in close collaboration with a school district in the southern United States. SchoolRide serves as a comprehensive testbed for studying and evaluating robust operational policies for disruption management, enabling systematic investigation of strategies under realistic data and operational constraints. We design an integrated pipeline for dynamic bus status collection and formulate the School Bus Disruption Management (SBDM) problem as a combinatorial optimization task that replans routes based on predefined schedules, real-time status, and disruption events. The framework balances student service quality (e.g., waiting time and school delays) with operational efficiency (e.g., route adjustments and driver workload). We explore heuristic and optimization-based approaches that leverage historical disruption logs from the partner district to proactively replan routes and evaluate their performance using synthetic data generated from real-world operational records to protect privacy. The generated synthetic datasets will be released to facilitate future research in this domain. Our approach outperforms current operational policies, effectively preserving service quality while reducing disruptions and workload.