Vaibhav Kumar

Vaibhav Kumar Upadhyay, PhD

Assistant Professor

Data Science and Engineering

Head In Charge (Computer Center)

Indian Institute of Science Education and Research, Bhopal

Research Interests:

Geospatial Artificial Intelligence (GeoAI), 2D/3D GIS, Urban Informatics.

ORCID, Google Scholar, ResearchGate

B.E. : Computer Science and Engineering, MS Ramaiah Institute of Technology, Bangalore

M.Tech : Geoinformatics, Indian Institute of Remote Sensing, Dehradun

PhD : Centre for Urban Science and Engineering, Indian Institute of Technology Bombay

PI: GeoAI4Cities Lab

Advisor: SimDAAS Pvt. Ltd.

My research focuses on developing smart digital twins for urban environments, integrating geospatial AI, remote sensing, and 3D data science. The work is structured around three major verticals.

I focus on twin attribution and feature extraction using high-resolution remote sensing data, including imagery and LiDAR. This involves semantic segmentation, object detection, and attribution of key urban features critical for downstream planning and analysis.

I work on the development of digital twins using learning and optimization techniques, particularly deep learning applied to 3D representations such as point clouds, meshes, and depth maps. My research explores accurate 3D data generation, as well as transformations across different 3D formats to enable interoperability and flexibility in simulation environments.

I emphasize synthetic 3D representation generation using multimodal data sources. This includes the automatization of large-scale outdoor 3D maps using deep generative models trained on aerial, street-view, and ground-truth data.

I apply these smart digital twins to diverse use cases, including urban planning, climate resilience, and simulation environments for autonomous systems. My goal is to build scalable, transferable models that support intelligent decision-making in complex urban settings.

Sponsored Projects

Title: Deep Augmentation of LiDAR Point Clouds using CNN

Funding agency: IISERB (Nov 2021)

Status:Finished

Role: PI

Title: AI-Driven DroneTech Centre and Innovation Hub

Funding agency: MPSeDC, GoMP

(May 2025)

Status: Approved

Role: PI

Title: Deep Learning Based Approach to Quantify the Emergency Vehicle Accessibility in Dense Urban Areas Using Lidar and Aerial Imagery

Funding agency: NGP: DST (Nov 2023)

Status:Ongoing

Role: PI

Title: Large-Scale Manually Annotated LiDAR Datasets from Indian cities to Facilitate Semantic Segmentation

Funding agency: iHub-Data, IIIT-Hyderabad (Nov 2024)

Status:Ongoing

Role: PI

Title: LiDAR Driven Thermal Profiling for Green Equity: Mapping Vegetation’s Role in Urban Heat Mitigation and Community Well-Being

Funding agency: Champions Grant, Royal Academy of Engineering, London

Status:Ongoing

Role: PI

Title: Fruit level precision spraying system for orchard using deep learning and synthetic dataset

Funding agency: AgriHub, IIT Indore

Status:Ongoing

Role: PI

Title: Spatiotemporal Street View Data Generation using Deep Learning for Women Safety Perception Mapping of Indian Cities

Funding agency: ASEAN, SERB

Status: Ongoing

Role: PI

Title: PUSHPAK - National Mission on Drone Technology, IIT Bombay

Funding agency: MeitY

Role: CoPI

Status: Ongoing

If you are passionate about 3D Vision, Urban Planning, and various verticals of automating Digital Twins (Development and Application) using AI, please Leave A Message or email me if you are interested.

Hot from the Lab!!: First of its kind, Freely available labeled LiDAR data repository from Indian Cities. Access it at :https://www.lidaverse.com/#/

RECENT PUBLICATIONS

Sameer Verma, Vaibhav Kumar, Point-PAD: Point Cloud Upsampling with Kernel Representation and Attention, 2025, Pattern Analysis and Applications. (InPress)
Anurag Nihal, Pyare Lal, Vaibhav Kumar, Urban multi-domain mixing (UMDMix) based unsupervised domain adaptation for LiDAR semantic segmentation, Neurocomputing, 2025, 131526, ISSN 0925-2312, https://doi.org/10.1016/j.neucom.2025.131526.
Ayush Dabra, Pyare Lal Chauhan, *Vaibhav Kumar, Deep Learning and Multi Source 2D and 3D Geospatial Data for Urban Quality of Life Assessment, International Journal of Applied Earth Observation and Geoinformation, Volume 144, 2025, 104838, ISSN 1569-8432, https://doi.org/10.1016/j.jag.2025.104838.

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