```html Shubhanshu Bishwash | Agentic AI & Geospatial Expert

Shubhanshu Bishwash

Currently At
Morgan Stanley Capital International
Alumni Of
Indian Institute of Technology Indore

Seasoned AI & Geospatial Engineer with deep expertise in Generative AI, Machine Learning, and Satellite Data Processing. Architecting autonomous multi-agent workflows, deploying Vision Transformers, and building no-touch AI pipelines that transform terabytes of raw Earth observation data into actionable climate intelligence, predictive analytics, and operational automation for global enterprises.

shubhanshub2007@gmail.com +91 98349 81942 Mumbai, IN
Agentic AI Vision Transformers Earth Observation Cloud Architecture PostGIS Climate Modeling Python Time-Series
AI & Geospatial Proficiency
Agentic AI & LLM Toolchain
Cursor Codex Claude Code Anthropic Suite OpenAI Hugging Face

Working with local LLMs (LLaMA), MCP servers, autonomous agents, multi-agent orchestration, and no-touch AI pipelines. Expert in prompt engineering, agent routing, and deploying inference interfaces for enterprise workflows.

Machine Learning & Simulation
Vision Transformers (ViT) U-Net CNN GANs Monte Carlo Predictive Modeling

Time-series analysis, predictive modeling, Monte Carlo simulations, statistical forecasting, and simulation data proficiency. Expertise in climate risk forecasting, ESG scoring, and forward-looking analytics.

Geospatial Technology & Data
Google Earth Engine PostGIS / GeoPandas SAR / LiDAR Sentinel / Landsat Data Modeling

Earth observation, satellite data processing, DEM/SAR fusion, multi-temporal analytics, and cloud-native geospatial systems on AWS/GCP.

LIVE SKILLS FEED
Shubhanshu Bishwash — AI & Geospatial Engineer
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Technical Skill Ecosystem

Programming & Data
Python PostgreSQL/PostGIS MySQL MATLAB Xarray, Pandas GDAL NetCDF/HDF5
AI & Machine Learning
Agentic AI Cursor, Claude Code OpenAI/Anthropic LLaMA & Local LLMs ViT / U-Net CNN GANs (ERS-GAN) Monte Carlo
GIS & Earth Observation
ArcGIS / ESRI QGIS / PyQGIS Google Earth Engine SNAP LiDAR & SAR GeoPandas Satellite Processing
Cloud & Platforms
AWS / GCP / Azure Tableau Power BI Matplotlib Insomnia

AI Pioneer

Deploying AI and ML architectures for 4+ years, consistently achieving >92% accuracy on complex geospatial vision tasks.

Global Scale

Currently processing data across 25,000+ global issuers in the MSCI ACWI universe, covering physical risk and emissions.

Oil & Gas Impact

Built an in-house geospatial exploration app for EOG Resources featured in their quarterly earnings report.

Urban & Economic

Quantified COVID-19 economic impact via nightlight drops (–37.2% in Delhi) and modeled urban expansion in 1,000+ towns.

Professional Experience

Morgan Stanley Capital International

Climate DataOps Engineer
March 2026 – Present
Mumbai, IN

Multi-Agent Workflows

Geospatial Predictive Models

Data Harmonization

ESG & Compliance

Encora Inc. [Client: EOG Resources]

Software Engineer / Geospatial Data Engineer
March 2025 – 2026
Mumbai, IN
Highlight: Built an in-house geospatial exploration application adopted by ~70% of staff; featured in quarterly earnings report.

In-House AI & Vision Transformers

Trained ViT architectures on multi-spectral imagery for automated methane plume detection (>92% accuracy), cutting manual inspection by 60%+.

Parallelized Data Pipelines

Engineered preprocessing pipelines for >10 TB of drone/satellite data, improving throughput by 40% across multi-index time-series.

Earth Observation Research

Initial member of the EO research group; facilitated formal tech partnerships with major upstream firms.

Remote Sensing QA & Audit

Main POC for data quality in multi-million-dollar acquisitions; enabled 100% audit traceability across 400+ reclamation sites.

Valectus Pvt. Ltd.

GIS Data Engineer
March 2024 – March 2025
Mumbai, IN

Automated GIS ETL Pipelines

Engineered automated pipelines using Python (GDAL, GeoPandas) and PostGIS, saving 1,200+ manual hours/year and $120K for NYU Stern.

AI-Driven LULC Classification

Developed CNN-UNet (97% accuracy) and applied GANs to enhance legacy satellite imagery for remote road detection.

Cloud-Native Flood Modeling

Designed systems on GCP using GEE/Azure, fusing DEM, SAR, and multi-temporal data with Monte Carlo simulations.

Urban & Economic Analytics

Quantified COVID-19 impact via nightlight drops; built SAR-based urban expansion models across 1,000+ Sub-Saharan towns.

Nineleaps Technologies

Data Engineer
Nov 2023 – Feb 2024
Bangalore, IN

High-Volume ETL Architecture

Designed and implemented ETL pipelines across 10+ diverse data sources, improving processing speed by 35%.

BI Dashboard Engineering

Built interactive Tableau and Power BI dashboards driving operational efficiency for a top-3 cab service across 50+ cities.

IIT Indore

Teaching Assistant
June 2022 – Dec 2022
Indore, IN

Graduate Lecture Coordination

Led sessions on Kalman Filters & Random Signals for graduate students.

MATLAB Simulation Support

Assisted with hands-on simulation labs and algorithm implementation.

Education

IIT Indore
Master of Technology (M. Tech.)
IIT Indore | Astronomy, Astrophysics & Space Engineering | GPA: 8.3/10
June 2023

Thesis: Potential of Sentinel 1/2 for deforestation detection

Coursework: Remote Sensing, Space Engineering, Astrostatistics, Navigation Systems

University of Mumbai
Bachelor of Engineering
University of Mumbai | Electronics Engineering | GPA: 7.2/10
June 2021
Extracurricular: 6 months of dedicated internship experience specializing in GIS.

Technical Skills

Programming & Data

Python SQL (PostgreSQL/PostGIS, MySQL) MATLAB NumPy, Pandas, Xarray Time-Series Analysis GDAL NetCDF/HDF5/GeoTIFF

AI & ML

Agentic AI Codex, Cursor, Claude Code OpenAI, Anthropic Suite Huggingface No-Touch AI Pipelines U-Net CNN / ViT GANs (ERS-GAN) LLaMA & Local LLMs

GIS & Spatial

ArcGIS / ESRI QGIS / PyQGIS / C++ Google Earth Engine PostGIS / GeoPandas SAR / LiDAR Processing SNAP

Cloud & Visualization

AWS / GCP / Azure Tableau Power BI Matplotlib Insomnia

Key Projects & Awards

Sentinel Change Detection

Python, GDAL, GEE, PostgreSQL/PostGIS | May 2023

Developed change detection algorithms using Sentinel-1 (89%) and Sentinel-2 (84%) imagery. Implemented PostgreSQL/PostGIS pipelines for efficient spatial data management and species-level analysis, computing advanced forest health monitoring metrics (user/producer accuracy, Cohen's kappa).

Photogrammetric Species Identification

scikit-learn, SVM, Random Forest | Nov 2023

Developed a photogrammetric pipeline using Sentinel-1 C-band and Sentinel-2 optical data to classify 17+ tree species in Indian forests. Integrated GDAL with Python (Pandas, NumPy, SQL) and leveraged Random Forest and SVM for refined band-specific data fusion.

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