TiTiler | Udit Asopa

Toolchain and Technologies

Fri, 30 Oct 2026 00:00:00 +0000

Coding and Analysis	Geospatial and EO Tools	Cloud and Development Platforms	Visualization and Reporting	Integration and Operations
Python (pandas, numpy, matplotlib, seaborn) Statistical scripting for EO analytics SQL & R (basic) Custom data transformations DAX & M for BI tools	QGIS, ArcGIS, Google Earth Engine (GEE) GDAL & SNAP LiDAR data processing tools SARscape for InSAR workflows Raster-vector integration suites	Google Earth Engine cloud apps AWS (EC2, S3 basics) Git & version control workflows Databricks notebooks Jupyter-based automation	Power BI & geospatial dashboards Seaborn and matplotlib visualizations KPI tracking and visual storytelling Custom reports for disaster analytics Interactive map-based interfaces	Bash & CLI scripting for task automation GitHub Actions & team repos API integration with Esri tools Pipeline orchestration for SAR data DevOps-style reproducibility tools

Geospatial Data Infrastructure

pgSTAC — PostgreSQL-backed infrastructure for storing and querying STAC catalogue metadata.
Apache Polaris and Apache Iceberg — Catalogue and open table-format tooling for interoperable analytical data.
OGC APIs — Open standards for accessing geospatial data through interoperable web services.
TiTiler — Dynamic map tile services for cloud-optimized geospatial raster data.
GDAL — Tools and libraries for processing and translating raster and vector geospatial formats.

Member of Technical Staff

Tue, 01 Sep 2026 00:00:00 +0000

Geospatial Data Engineering for Physical AI

At NestAI, I work as a GIS Data Engineer, building geospatial data infrastructure for Physical AI and autonomous systems. My work focuses on making spatial data easier to organize, process, discover, and serve for AI research and operational applications.

Role Focus

Geospatial pipelines: Building data workflows for spatial datasets, including Earth observation imagery and other raster and vector data.
Catalogues and data architecture: Organizing and making geospatial assets discoverable through STAC-based catalogue infrastructure.
Geospatial data services: Serving spatial data through standards-based APIs and map applications.
Data quality and reliability: Supporting consistent, reliable data flows for downstream analytics and AI workflows.
Cross-functional engineering: Working with engineering and AI teams to make geospatial data usable in their workflows.

Software and Tools

pgSTAC: PostgreSQL-backed STAC catalogue infrastructure for managing and querying geospatial assets.
Apache Polaris and Apache Iceberg: Catalogue and table-format tooling for managing interoperable analytical data.
OGC APIs: Open standards for interoperable access to geospatial data and services.
TiTiler: Dynamic tile services for visualizing cloud-optimized geospatial raster data.
GDAL: Geospatial data processing and format interoperability for raster and vector datasets.