Debayan Mandal
Ph.D. Student
Geospatial Exploration and Resolution (GEAR) Lab Member
Research
Debayan Mandal's research aims to build geospatial digital twin cities for vulnerable coastal communities by fusing geospatial big data with theoretical models. These digital twin cities serve the crucial functions of near-real-time modeling of infrastructural damages and societal impacts from coastal hazards, evaluating short-term and long-term community resilience under different climate change scenarios, and informing sustainable management and planning. By focusing on the fusion of geospatial big data and theoretical models, Debayan's research addresses the need for innovative approaches to measure and improve disaster resilience, particularly in the face of increasing disasters and population growth in disaster-prone areas worldwide. His research aligns closely with the United Nations Sustainable Development Goals and contributes to the field of GIScience by developing practical methodologies and tools to support decision-making and enhance community resilience.Impact
Debayan Mandal's research on fusing geospatial big data with theoretical models to build geospatial digital twin cities for vulnerable coastal communities holds immense societal relevance. By providing near-real-time modeling of infrastructural damages and societal impacts from coastal hazards, evaluating community resilience, and informing sustainable management and planning, his work addresses the pressing need for measuring and improving disaster resilience. Furthermore, his investigation on the use and misuse of social media in spatial analytics and disaster resilience research sheds light on the uncertainty and adverse consequences of inappropriate geolocating strategies, contributing to the field's understanding of analyzing location-based social media data for effective disaster management.Selected Publications
Journal Publications:
- Ghosh, A. Goenka, M. Deo, D Mandal (2017), Vernacular Architecture as an Idiom for Promoting Cultural Continuity in South Asia, AI & Society Journal. (DOI 10.1007/s00146-017-0754-z)
- Yang Mingzheng, Lei Zou, Heng Cai, Yi Qiang, Binbin Lin, Bing Zhou, Joynal Abedin, and Debayan Mandal. (2022), Spatial–Temporal Land Loss Modeling and Simulation in a Vulnerable Coast: A Case Study in Coastal Louisiana Remote Sensing 14, no. 4: 896. https://doi.org/10.3390/rs14040896
- Binbin Lin, Lei Zou, Nick Duffield, Ali Mostafavi, Heng Cai, Bing Zhou, Jian Tao, Mingzheng Yang, Debayan Mandal & Joynal Abedin (2022) Revealing the linguistic and geographical disparities of public awareness to Covid-19 outbreak through social media, International Journal of Digital Earth, 15:1, 868-889, (DOI: 10.1080/17538947.2022.2070677)
- Bing Zhou, Lei Zou, Ali Mostafavi, Binbin Lin, Mingzheng Yang, Nasir Gharaibeh, Heng Cai, Joynal Abedin, Debayan Mandal, VictimFinder: Harvesting rescue requests in disaster response from social media with BERT, Computers, Environment and Urban Systems, Volume 95, 2022, 101824,ISSN 0198-9715, https://doi.org/10.1016/j.compenvurbsys.2022.101824
Book Chapter:
- Joseph, D Mandal (2018), Comparative Study of Predictive Models In Microbial Induced Corrosion, Machine Learning and IoT: A Biological Perspective. (ISBN:- 9781138492691; Publication Date: 19th July, 2018, Publisher: Routledge, Taylor and Francis Group)
Conference Presentations:
- Debayan Mandal, Nikhil Bhatia, Roshan Srivastav., “Quantifying the Uncertainty in streamflow predictions using SWAT for Brazos–Colorado coastal watershed, Texas”, AGU Fall Meeting’16, San Francisco, 15 December 2016.
- Debayan Mandal, Venkatesh B, Roshan Srivastav., “Impact of Climate Variability and Land-use changes on river flow characteristics – A case study of the San Jacinto River Basin”, AOGS Annual Meeting’16, Singapore, 11 August 2017.
- Debayan Mandal, Binbin Lin, Bing Zhou, Heng Cai, Joynal Abedin, Mingzheng Yang, Lei Zou., “Visualizing and Evaluating the Geocoding Uncertainty in Social Sensing for Disaster Management”, International Cartographic Conference’21, Florence, Italy 16 December 2021.
- Debayan Mandal, Binbin Lin, Bing Zhou, Heng Cai, Joynal Abedin, Mingzheng Yang, Lei Zou., “Uncertainties in Geolocating Social Media Data for Disaster Research”, AutoCarto’22, Redlands, 26 February 2022.
- Debayan Mandal, Binbin Lin, Bing Zhou, Heng Cai, Joynal Abedin, Mingzheng Yang, Lei Zou., “A modular machine learning Platform for Resilience Inference Measurement and Enhancement”, AAG Annual Meeting’22, Virtual, 26 February 2022.
Education
Doctor of Philosophy in GEOGRAPHY - Texas A&M University, College Station - 2021-Ongoing
Master of Science in CIVIL ENGINEERING - Texas A&M University, College Station - 2019-2020
Bachelor of Technology in CIVIL ENGINEERING - Vellore Institute of Technology, Vellore - 2013-2017
Awards
Undergraduate Mentoring Program 2016 mentee, American Geophysical Union, Dec 2016. (Fifty Undergraduate Students, among those who attended the meeting, were given the opportunity to be mentored by the senior presenters from a similar field.)Second Position for Quiz during Water Conservation Week, VIT University, 2017.
Featured in a book for inspiring story for budding engineers, Shape-IT (Dr. Subramani R, Ms Vaijayanthi S), 2017 (ISBN: - 978-1-946869-16-6)
Departmental Fellowship for Civil Engineering, in Texas A&M University, for the year 2019.
Texas Public Education Grant, 2019-2020 academic year term.
Departmental Fellowship for Civil Engineering, at Texas A&M University, for Spring 2021.
Travel Funding (USNC) to participate in the 30th International Cartographic Conference, Italy December 14 through 18, 2021.
Student Assistantship, AutoCarto 2022 conference
Travel Grant, Department of Geography, AY 2022-2023.
Selected to participate in the I-GUIDE Summer School
Courses
GEOG 478: WebGIS Lab - Instructor: Dr. Heng CaiGEOG 232: Cartography and Visualization Lab - Instructor: Dr. Elizabeth Breyer
GEOG 478: WebGIS Lab - Instructor: Dr. Zhe Zhang
