Neha Sharma

Artificial Intelligence Developer
MIT CSAIL · Remote, India

Working Group Member
WCRP Digital Twins · Global

GEOSPATIAL AI · EARTH SYSTEMS · HUMAN-CENTERED DESIGN

Reading our changing world through data, place, and AI.

I’m Neha Sharma, an Artificial Intelligence Developer at MIT and a geospatial researcher working across GeoAI, remote sensing, and scientific discovery. I help build visual data science and multimodal tools that make complex information easier to explore.

Explore my research View projects

MIT CSAILArtificial Intelligence Developer
WCRPDigital Twins Working Group
200+learners and professionals mentored

Featured book · 2025

Smart Buildings and Cities with Remote Sensing and GIS

Co-edited by Neha Sharma, Shiv Mohan, and Navneet Munoth

A cross-disciplinary guide to using remote sensing and GIS for smarter buildings and cities, from site analysis and land-use mapping to urban planning.

Explore the book See my chapters

CRC Press · Taylor & Francis

Research & practice

At MIT CSAIL, I contribute to research and outreach for next-generation AI and scientific discovery, including a visual data science platform, multimodal knowledge exploration, and human–AI collaboration.

I’m also a member of the World Climate Research Programme’s Digital Twins – Beyond Physical Systems Working Group, part of the Digital Earths Lighthouse Activity. I collaborate on Digital Earth and Digital Twin frameworks connecting human and physical Earth systems, with applications in climate risk, water, agriculture, energy, and urban planning.

Previously, I was a Product Engineer in Geospatial Data Science at Esri’s GeoAI R&D Center in Delhi (February 2023–January 2026). Before that, I worked in GeoAI at Larsen & Toubro in Chennai, contributing to projects across the built environment.

My research interests include remote sensing, GIS, spatial data science, computer vision, and GeoAI. I have co-authored papers in international and national conferences and journals, and co-edited Smart Buildings and Cities with Remote Sensing and GIS (Taylor & Francis, 2025), connecting remote sensing with architecture and planning.

An interdisciplinary foundation

My path brings together an MS in Data Science from Liverpool John Moores University (2023), an M.Tech in Geomatics from CEPT University (2020), and a B.Arch from MANIT Bhopal (2018). I also hold a PG Diploma in Data Science from IIIT Bangalore (2021), a Google Project Management Certificate (2025), and a Certified ScrumMaster credential (2024).

Community & what’s next

Since 2020, I have co-organized and served as a subject matter expert for the Council of Architecture–Training & Research Center’s national GAP program, connecting geomatics, architecture, and planning. I also volunteer with ISG, IEEE, and CEPT University, and enjoy mentoring learners through workshops and training programs.

I also run a global geospatial group on LinkedIn—join the conversation.

Join my global geospatial group

I’m interested in collaborative research and human-centered GeoAI for urban resilience, environmental sustainability, and geospatial intelligence—turning spatial data into useful insight for the places and communities it represents.

News & updates

Jul 30, 2026	New publication: Satellite Image-Based Spatial Analysis of Urban Air Quality Index, published in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2026).
Jul 07, 2025	Started making my personal website on GitHub!
May 25, 2025	Awarded ‘Outstanding Achiever’ in MS in Data Science by Liverpool John Moores University & UpGrad.
Apr 02, 2025	My first book got published - Smart Buildings and Cities with Remote Sensing and GIS!

Latest writing

Oct 24, 2026	How to Download Landsat 8 & Landsat 9 Satellite Imagery from USGS EarthExplorer
Feb 14, 2026	Inside Mantis AI: Visual Data Science, Cognitive Cartography, and GenAI Platform from MIT CSAIL
Jan 13, 2026	3DCityDB Series (Part 4): Importing CityGML Data into Your 3D City Database

Selected publications

Journal Paper

Satellite Image-Based Spatial Analysis of Urban Air Quality Index

Darshana Rawal, Sindhu Ranganath, Neha Sharma, and 1 more author

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2026

DOI Bib

@article{rawal2026satelliteaqi,
  title = {Satellite Image-Based Spatial Analysis of Urban Air Quality Index},
  author = {Rawal, Darshana and Ranganath, Sindhu and Sharma, Neha and Vyas, Anjana},
  journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
  volume = {XLIX-B3-2026},
  pages = {773--781},
  year = {2026},
  doi = {https://doi.org/10.5194/isprs-archives-xlix-b3-2026-773-2026},
  url = {https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/773/2026/},
  keywords = {Remote Sensing, Air Quality, GeoAI, Urban Environment}
}

Book

Smart Buildings and Cities with Remote Sensing and GIS

Shiv Mohan, Navneet Munoth, and Neha Sharma

, New York, USA, 2025

Abs DOI Bib Blog

This book provides a comprehensive overview of the use of remote sensing and GIS in the design, construction, and management of smart buildings and cities. It covers a wide range of topics including architectural site analysis, land use land cover mapping, and the application of satellite missions and data products for urban planning. The book is aimed at researchers, practitioners, and students in the fields of architecture, urban planning, and remote sensing.

@book{sharma2025smartbuildings,
  title = {Smart Buildings and Cities with Remote Sensing and GIS},
  author = {Mohan, Shiv and Munoth, Navneet and Sharma, Neha},
  editors = {Mohan, Shiv and Munoth, Navneet and Sharma, Neha},
  publisher = {Taylor and Francis},
  geography = {Global},
  year = {2025},
  volume = {1st},
  location = {New York, USA},
  isbn = {10-1032586113},
  doi = {https://doi.org/10.1201/9781003453321},
  altmetrics = {true},
  dimensions = {true},
  keywords = {Remote Sensing, GIS, Smart Buildings, Smart Cities, Urban Planning, Architectural Site Analysis, Land Use Land Cover Mapping, Satellite Missions, Data Products},
  url = {https://www.taylorfrancis.com/books/edit/10.1201/9781003453321/smart-buildings-cities-remote-sensing-gis-shiv-mohan-navneet-munoth-neha-sharma},
  blog_show = {true},
}

Conf. Paper

Fine-Grained Roof Type Classification & Multimodal Multitasking Building Detection & Height Estimation Using High Resolution Satellite Imagery

Neha Sharma, Sultanova Nailya, Jamila Mustafina, and 1 more author

, Malaysia, 2024

Abs Bib

This paper presents a novel approach for fine-grained roof type classification and building detection using high-resolution satellite imagery. The proposed method utilizes multimodal multitasking techniques to enhance the accuracy of building detection and height estimation. The results demonstrate significant improvements in classification performance, providing valuable insights for urban planning and development.

@paper{sharma2024roofclassification,
  title = {Fine-Grained Roof Type Classification \& Multimodal Multitasking Building Detection \& Height Estimation Using High Resolution Satellite Imagery},
  author = {Sharma, Neha and Nailya, Sultanova and Mustafina, Jamila and Ismail, Noor Lees},
  authors_show = {true},
  editors = {},
  publisher = {Springer, Singapore},
  booktitle = {International Conference on Data Science and Emerging Technologies (DaSET 2024)},
  year = {2024},
  organization = {UNITAR International University, LJMU, DOSM Malaysia, KLMUC},
  isbn = {978-981-96-7748-1},
  url = {https://link.springer.com/book/9789819677481#overview},
  geography = {Global},
  keywords = {Roof Type Classification, Building Detection, Height Estimation, High Resolution Satellite Imagery, Multimodal Multitasking, Urban Planning},
  location = {Malaysia},
  dimensions = {true},
}