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Shagun Mittal

PhD Student
Purdue University
West Lafayette, IN, United States

Shagun Mittal, a PhD student in Transportation Systems at Purdue University, is a data analysis enthusiast with five years of experience as a research assistant in the Urban Mobility and Network Intelligence Lab. Currently, he is also pursuing a a Master of Science in Computer Science and Statistics from Purdue University. He holds a Master of Science in Transportation Systems from Purdue University and a Bachelor of Engineering in Civil Engineering from IIT Tirupati, India.
Shagun's research focuses on leveraging large-scale datasets, statistical analysis, data visualization, and machine learning models to address challenges in urban transportation planning. He has led multiple World Bank and Indiana DOT projects, demonstrating his expertise in applying big data and AI techniques to infer mobility patterns and poverty-based inequalities in cities across the Americas, Africa, and Asia.
As a research assistant at Purdue University, Shagun has been instrumental in developing novel methods to assess mobility patterns and identify socio-demographic characteristics for informed policy decisions. He has worked with a wide variety of datasets, including cell phone location data, transit network data, and land use datasets, to provide actionable insights for urban planning and transportation management.
Shagun's research has been published in prestigious journals such as Transportation Research Record and Transportmetrica A: Transport Science. He has presented his work at international conferences, including the Transportation Research Board Annual Meeting and the Triennial Symposium on Transportation Analysis. In October 2023, he was invited to speak at the "Unleashing the Power of Data: Advancing Metro Traffic Demand Forecasting" conference organized by I-Metro in Delhi, where he introduced the New Mobility Diagnostics, a novel approach leveraging machine learning and cell phone data analytics for granular visibility into human mobility patterns.
In addition to his research experience, Shagun has held internship positions at the World Bank and the Pacific Northwest National Lab (PNNL). As a data scientist intern at the World Bank, he analyzed bus service demand and supply in Delhi using big data, providing the Delhi Transport Corporation with a business plan to expand bus ridership. At PNNL, he conducted data analytics, modeling, and optimization to infer optimal policies for improving curbside parking management and electric vehicle adoption.
Shagun's commitment to excellence has been recognized through various honors, including the Mary Ann Zimmerman Purdue Civil Engineering Innovation Award and the Best Academic Performer award at IIT Tirupati. He actively serves as a reviewer for several transportation journals and is a member of the Institute of Transport Engineers and Asha for Education - Purdue Chapter.

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