Naveed Tareen Pathan

Education

M.Tech in Transportation from VNIT Nagpur ( 2024)

B.Tech in Civil Engineering from K S School of Engineering and Management (2021)

Area(s) of Interest:

Travel demand modelling

Traffic flow theory

Transport policy

Travel behaviour

Transportation Network

Background and Current Research

Naveed Tareen Pathan's current research focuses on applying contagion-based approaches to understand congestion dynamics, including how congestion propagates and dissipates across transportation networks and the influence of road topology on these dynamics. He is also working on developing resilience indices and early warning systems for congestion. His research further explores dynamic demand estimation by accounting for variable capacity, congestion spillback, and assigning weights to Traffic Analysis Zones (TAZs) based on economic data, while integrating crowdsourced information.

During his master’s thesis, he investigated the acceptability of congestion pricing systems in developing countries through a case study in India, examining the factors that influence public acceptance and the potential of congestion pricing as a transport policy.

He has published a research article based on his Master's work:

Naveed Tareen Pathan, Vishrut S. Landge, Acceptability of congestion pricing system in developing countries: A case study in India, Case Studies on Transport Policy, Volume 20, 2025, Article 101458.

https://doi.org/10.1016/j.cstp.2025.101458

Motivation for Research:

During my master’s thesis, I primarily worked on congestion pricing. However, I realized that while congestion pricing is a valuable policy tool, real-time solutions that actively help mitigate traffic congestion on the ground were limited. This gap between long-term policy and immediate operational strategies sparked my interest in exploring data-driven, real-time approaches such as contagion-based models and resilience analysis to better understand and respond to congestion as it unfolds across the network.

Year of Joining: 2024

Supervisor(s): 

Prof. Sai Chand