Prateek Agarwal
Prateek Agarwal is currently pursuing his Ph.D. at the Indian Institute of Science under Dr. Tarun Rambha. His research blends elements of simulation-based optimization and transportation with focus on enhancing public transit systems' design and efficiency through advanced agent-based transit assignment models. As a recipient of the esteemed Prime Minister's Research Fellowship, he holds a B.Tech from GBPUAT, Uttarakhand, India, and a Masters from IISc, Bengaluru. His M.Tech thesis, titled Multi-level Partitioning Algorithms & Reliability Analysis for Transit Networks, was recognized with the Innovative Student Projects Award 2022 by the Indian National Academy of Engineering. In addition to his academic pursuits, Agarwal has accumulated practical experience through collaborations with companies such as Allcargo Logistics Ltd., Robert Bosch Ltd., Bengaluru Metropolitan Transport Corporation, and Tummoc through numerous projects aimed at improving transit reliability and efficient multimodal journey planning.
Latest News
[January 2023] New paper published in IEEE Transactions! Check it out: https://ieeexplore.ieee.org/document/10517862
[January 2023] Awarded Innovative Student Projects Award 2022 by Indian National Academy of Engineering INAE
Research Interests
Public Transit Assignment and Network Design: Develop an agent-based transit assignment model with the flexibility to handle constraints related to congestion and capacity to be used for short-mid term planning.
Efficient Routing Algorithms for Public Transit Vehicles: Improving bicritera (travel time and transfers) shortest path algorithms like TBTR, RAPTOR, and Transfer Patterns using concepts from graph theory. For example, using inverted hypergraphs to generate multi-level partitioning paradigm to speed-up the query phase and reduce the preprocessing associated with HypTBTR, HypRAPTOR.
Bus Priority Lanes Design Based on Spatio-Temporal Unreliability: Quantify reliability of transit services based on deviations from the scheduled timetable and analyze its effect on OD level travel time. This line of analysis can help transit operators to create timetables that are easier to follow and decide the optimal locations for bus priority lanes.
Multi-objective Traveling Salesman Problem: Developing efficient heuristic algorithms for solving large scale MOSTSP particularly useful for freight and delivery systems like Amazon, UPS
Skills
Coding: Python, R, C, C++, SQL, MATLAB
Tools: Aptech GAUSS, CPLEX, Apache Spark,
Others: LATEX, Tableau, Eclipse SUMO, PTV, Vissim, Hadoop
Education
2019- 2021 M.Tech (Research), Indian Institute of Science, Bengaluru, IndiaMajor: Transportation EngineeringThesis title: Multi-level Partitioning Algorithms & Reliability Analysis for Transit Networks(Innovative Student Projects Award 2022 by Indian National Academy of Engineering INAE)Advisor: Tarun Rambha
2014 - 2018 B.Tech. G.B.P.U.A.T, Uttarakhand, India.Major: Civil EngineeringProject title: Analysis of Stability of Slopes
Internships
Company: Central Public Works Department, Government of India.2017 (June-Aug) Objective: To do a detailed analysis of the stability of slope under several critical conditions using Swedish and Friction circle theories by computational and manual methods, and compare the results to determine the safe conditions along with FOS.