Neha Sharma

Product Engineer II · Geospatial Data Science
Esri GeoAI R&D Center · Delhi

GEOSPATIAL AI, FROM PIXELS TO IMPACT

Turning Earth observation into insight for a changing world.

I’m Neha Sharma, a GeoAI practitioner working at the intersection of remote sensing, spatial data science, and computer vision. I build geospatial AI solutions that help make complex places and patterns easier to understand.

Explore my research View projects

200+learners and professionals trained
2025co-editor, Taylor & Francis book
Gold medallistacademic distinction

Research & practice

As a Product Engineer II in Geospatial Data Science at Esri’s GeoAI R&D Center in Delhi, I work on applied geospatial AI. Previously, I was a Software Engineer 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

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 posts

May 15, 2025	Boosting GeoAI Model Performance with Test Time Augmentation
Dec 22, 2023	ArcGIS AI Models – Year in Review

selected publications

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},
}