Welcome to My Academic Website!
I am Nishat Naila Meghna, a Ph.D. student in the Department of Civil and Environmental Engineering at Virginia Tech, focusing on Transportation Engineering Research. As a passionate and driven student, I am committed to pushing the boundaries of the field through innovative research and sophisticated data analysis techniques. My research focuses on modeling individuals’ travel behavior using advanced econometrics and machine learning models, aiming to create more efficient and sustainable transportation systems that benefit communities worldwide.
Previous Collaboration
Currently, I am collaborating with the Amazon team on their ‘Amazon Research Award’ project, where I am applying my knowledge in data analysis to develop a hybrid recommendation system. This system models Household-Level Online Shopping Demand to create a more personalized shopping experience for customers while also reducing transportation-related emissions.
Research Philosophy
As a researcher, I am driven by a passion for making a meaningful impact on society. Through my work, I hope to contribute to the development of transportation systems that are safer, more equitable, and more sustainable. I am determined to advance the field of transportation engineering and drive positive change in our communities.
Currently Ongoing Projects
Currently, I am involved in three separate projects: Bike Infrastructure AND Urban Air Mobility (UAM). In the bike infrastructure project, our primary objective is to develop a policy evaluation tool that assesses the effectiveness of cycling policies and infrastructures before implementation. This tool will help planners and stakeholders understand the environmental, equity, and accessibility impacts, guiding informed decision-making for sustainable transportation solutions. The main objective of Urban Air Mobility (UAM) project is to understand and forecast the impact of flying taxi services on future urban and rural transportation patterns in the USA. The project aims to design advanced AI models to analyze potential market demands and supply interactions, ensuring that UAM services are accessible, affordable, and equitable across different socioeconomic groups.
Figure Bike Infrastructure: A Policy Analysis Tool for Measuring the Effectiveness of Cycling Infrastructure in Blacksburg Area.
The main work involved in this Bike Infrastructure project includes designing and conducting a combined revealed and stated preference survey among commuters in Blacksburg to gather data on their current and hypothetical choices related to cycling infrastructure. Based on this data, the project will develop advanced econometric models to assess the climate, equity, and accessibility impacts of these infrastructures. Finally, the results will be integrated into a user-friendly software system, enabling transportation planners and engineers to effectively evaluate and implement cycling policies.
Figure UAM: From Fiction to Reality: Using AI Models to Capture How Urban Air Mobility (UAM) Will Reshape Future Cities
The main works involved in Urban Air Mobility (UAM) project include designing and conducting a combined revealed and stated preference survey among residents of Washington, DC, and Blacksburg to understand their perceptions and willingness to use UAM services. The project will also develop advanced AI-based travel demand models to analyze the data collected and identify potential vertiport locations and UAM routes considering FAA and local zoning regulations. Additionally, the project will address equity considerations to ensure that UAM services are accessible and affordable for all socioeconomic groups.
Free time
- 🏃♂ 📖 Waliking, Reading Story Books
- 🗺️ Traveling 🌵 Planting
- 📺 Films and tv series! 😬
Funding
