Dhanyasri Bolla

Urban Giants Under Threat: Unveiling Climate Vulnerabilities & Adaptive Strategies in Megacities

Research project analyzing climate vulnerabilities and adaptation strategies in 43 global megacities.

• Conducted a comparative analysis of 48 megacities' climate action plans.
• Explored relationships between climate risks, infrastructure systems, disasters, financial mechanisms, and stakeholders.
• Applied chi-square tests and Cramer's V to identify significant associations between adaptation elements.
• Identified emergent global themes and regional disparities in urban adaptation efforts.
• Developed insights to support evidence-based climate policy for high-density urban regions.

Uncovering the Hidden Benefits of Adaptation: Insights from a Systematic Review

Research project investigating co-benefits of climate adaptation strategies across sectors and regions.

• Investigated patterns of co-benefits including health, food security, and climate mitigation.
• Co-Authored a research paper in association with NIST by coding and categorizing co-benefits from 430+ scientific articles.
• Identified recurring themes such as health improvements, biodiversity preservation, and economic cost savings across climate adaptation projects.

Research Landscape Mapping (2024)

Developed a dataset by scraping and categorizing research publications across 20+ Web of Science categories related to climate adaptation.

• Built a visualization dashboard featuring treemap and bar chart representations to highlight the dominance of Environmental Sciences, Energy Fuels, and Engineering subfields.
• Provided analytical insights into cross-disciplinary overlaps (e.g., Environmental + Engineering + Management) to support megacity adaptation policy research.

Tracking Systemic Impacts of U.S. Foreign Aid Policy: A Qualitative Analysis and Codebook Development(2024)

In response to abrupt shifts in U.S. foreign aid policy in early 2025, this project aimed to systematically document and analyze the real-world impacts on organizations engaged in food aid and food security.

• Designed and implemented a 14-category codebook with 40+ sub-codes using an iterative grounded theory approach.
• Processed and analyzed 18 expert interview transcripts, converting unstructured qualitative data into structured datasets.
• Applied Python (Pandas, Excel) and NVivo/Atlas.ti-style coding methods to tag, organize, and synthesize hundreds of data points.
• Delivered a replicable framework enabling longitudinal tracking of systemic impacts in foreign aid and food security policy.

What Our Region Grows 3.0 (WORG)

Project involving automated analysis of USDA Census of Agriculture and inbound food-supplier flows to map regional dependencies.

• Automated the analysis of the USDA Census of Agriculture (2012, 2017, and 2022) to streamline processing workflows and improve reporting efficiency.
• Engineered CPI-normalized dashboards to accurately track, adjust, and visualize historical agricultural economic trends.
• Analyzed inbound food-supplier flows utilizing Freight Analysis Framework (FAF) SCTG data to map regional dependencies.

ASCE Virginia Report Project

Project focused on data standardization and visualization protocols for infrastructure reporting.

• Unified graphics and complex underlying datasets for the ASCE Report Card, establishing consistent data visualization protocols for infrastructure reporting.

Urban Giants Under Threat: Unveiling Climate Vulnerabilities & Adaptive Strategies in Megacities

Primary author of a research paper analyzing climate vulnerabilities and adaptation strategies in 43 global megacities.

Submitted for possible publication in AGU Earth's Future

Abstract: With their rapid expansion and escalating population densities, megacities face unprecedented challenges in ensuring climate resilience. Our research examines how megacities worldwide plan to adapt to climate change. Specifically, we evaluate the resilience and adaptive capacity enumerated in 43 global megacity climate reports by categorizing and coding data across five key dimensions: infrastructure systems, climate risks, natural disasters, financial sources, and stakeholder involvement. We analyze trends and relationships between variables across these megacity reports to deduce global trends in these urban areas using statistical analysis. Three key patterns emerge from our analysis of these megacity adaptation plans: (1) there is global convergence on the need for sustainable transportation infrastructure, (2) there is some misalignment between local climate risks and chosen adaptation investments, and (3) we found considerable underrepresentation of local stakeholders in planning processes. By identifying key areas of vulnerability, infrastructure plans, financial backing, and stakeholders, our research underscores gaps in current planning approaches that could be addressed in the future to make megacities safer and more sustainable.

Uncovering the Hidden Benefits of Adaptation

Co-Authored a research paper in association with NIST by coding and categorizing co-benefits from 430+ scientific articles.

Published in Environmental Research: Climate: Visit Paper

Abstract: This study analyzes 1,684 articles from the Global Adaptation Mapping Initiative to examine how different adaptation characteristics relate to co-benefits, or positive outcomes beyond reducing climate risk. It finds that links between adaptation type, sector, actor, or region and the presence of co-benefits are generally weak. Ecosystem-based adaptations are more likely to be associated with co-benefits, while technical or infrastructural responses are less likely than human behavioral responses. There are no significant differences across economic sectors, and some statistical results are inconsistent, creating ambiguity about which adaptations most often produce co-benefits. The findings point to the need for better frameworks and documentation to assess and capture co-benefits in adaptation planning.

AWS Certified Data Engineer – Associate (DEA-C01)

Amazon Web Services

Validates expertise in designing, implementing, and optimizing data pipelines, ETL processes, and secure data storage solutions using core AWS services including Glue, Redshift, Athena, Lambda, DynamoDB, S3, and more.

Skills Demonstrated: Data Pipeline Design, ETL/ELT Processes, Data Lakehouse Architecture, Serverless Computing, Cloud Security, Data Governance

AGU 2024 Poster Presentation

Presented a poster titled “Urban Giants Under Threat” at the AGU Fall Meeting 2024 in Washington, D.C., focusing on climate vulnerabilities and adaptation strategies in megacities.

SEAS R&D Showcase - GW Engineering

Presented a poster titled “Resilient Megacities” at School of Engineering and Applied Sciences Research and Development Showcase at George Washington University in Washington, D.C., focusing on climate vulnerabilities and adaptation strategies in megacities.

GWU Innovation Fest Poster Presentation

Presented a poster titled “Resilient Megacities” at the Inaugural GW Innovation Fest at George Washington University in Washington, D.C., focusing on climate vulnerabilities and adaptation strategies in megacities.

Multilateral Financial Institutions: Chief Audit Executive Group Conference 2025

Presented a poster titled “Resilient Megacities” at the Multilateral Financial Institutions: Chief Audit Executive Group Conference 2025 at Inter-American Development Bank, focusing on climate vulnerabilities and adaptation strategies in megacities.

Capital Region Celebration for Women in Computing

Presented a Research Short titled “Urban Giants Under Threat” at the Capital Region Celebration for Women in Computing, focusing on climate vulnerabilities and adaptation strategies in megacities.

☁️ AWS & Cloud Data Engineering

• AWS Certified Data Engineer – Associate (DEA-C01)
• AWS Services: Glue, Redshift, Athena, DynamoDB, CloudWatch, Kinesis, Lambda, EMR, S3, Lake Formation, IAM, Step Functions, EventBridge, SNS
• Metadata-Driven ETL/ELT Pipelines
• Data Warehousing, Data Lakes & Lakehouse Architecture
• Serverless Architecture, Parquet Optimization

📊 Data Analysis & Programming

• Python (Pandas, Boto3, NumPy, Matplotlib, Seaborn, XML/JSON Parsing)
• R (Tidyverse, dplyr, ggplot2, Shiny, Quarto Markdown)
• SQL, Spark (PySpark)
• Excel, Jupyter Notebooks

🔬 Research Skills

• Literature Review, Thematic Coding
• Comparative Policy Analysis
• Co-benefit Mapping (GAMI)
• Policy Modeling, Data-Driven Research
• Poster Presentation (AGU Conference 2024)

🏗️ Systems Engineering

• SysML (ConOps, OV-1, Functional Decomposition)
• Capella (Arcadia Methodology)
• Systems Thinking
• Trade-off & Architecture Analysis

💼 Finance & Decision Modeling

• NPV, IRR, Payback Period
• Sensitivity & Risk Analysis
• Cost-Benefit Modeling in Excel
• Engineering Economics

📈 Statistical & Research Methods

• Chi-Square, Cramer’s V, Regression
• Survey Design, Conjoint Analysis
• Binary Variable Coding
• LLM-based Textual Analysis

🌐 Web Development

• HTML, CSS, JavaScript, PHP (basic)
• Responsive UI Design
• API Integration
• Git, GitHub, Netlify, Formspree

💡 Conceptual Knowledge

• Climate Adaptation & Resilience
• Urban Systems & Sustainability
• Infrastructure Policy & Risk Mapping
• UI/UX, Energy Emissions Forecasting

🤝 Soft Skills

• Leadership & Collaboration
• Problem Solving & Critical Thinking
• Public Speaking & Communication
• Time & Project Management

☁️ Metadata-Driven Energy & Climate Data Lakehouse (AWS)

AWS Serverless Data Engineering Project

• Architecture: Designed a serverless ingestion framework using AWS Glue (Python Shell) and DynamoDB to dynamically fetch data from disparate sources (XML/JSON APIs) without hard-coding logic.
• Ingestion Engine: Built a resilient Python pipeline handling legacy API constraints (CAISO), implementing dynamic date parameter injection and automated SSL certificate handling for strict utility gateways.
• Complex Transformation: Engineered a custom "Brute Force" XML parser in Python to resolve schema drift and namespace conflicts in energy data, normalizing it alongside nested weather JSON into a unified Silver Layer (Parquet).
• Analytics & Insights: Leveraged AWS Athena (SQL) to perform cross-domain analysis, using ISO 8601 timestamp parsing to correlate solar radiation spikes with real-time grid load fluctuations.

Technologies & Skills: AWS (Glue, DynamoDB, Athena, S3, Lake Formation), Python, Pandas, Boto3, Parquet, ETL Pipelines, Data Lakehouse Architecture

⚖️ DAIL Forge: Research-Grade AI Litigation Backend

PostgreSQL Core & API Architecture

• Architected the modernization of the Database of AI Litigation by migrating legacy low-code data into a highly structured PostgreSQL core.
• Designed and delivered a fully documented Research API to enable advanced data filtering and exporting, alongside a controlled Curation API for secure data management.
• Engineered a built-in provenance ledger that automatically logs every database mutation with required reasoning and citations to ensure strict legal accuracy and transparency.
• Transformed the overall data infrastructure to support scalable, SQL-ready research, providing a robust backend for complex AI litigation analysis.

Technologies & Skills: PostgreSQL, REST APIs, System Architecture, Data Migration, Provenance Tracking, SQL, Database Design

⚡ Serverless Green Energy Arbitrage Engine (AWS)

AWS Lambda Event-Driven Pipeline

• Engineered a fully automated, serverless ETL pipeline utilizing AWS Lambda and EventBridge to continuously extract live hourly electrical grid fuel-mix data via the EIA REST API.
• Transformed and aggregated data using Python and Pandas (via custom Lambda Layers), implementing strict type-casting to calculate real-time carbon intensity metrics (gCO2/kWh).
• Architected a NoSQL data storage solution in Amazon DynamoDB, optimizing partition and sort keys for time-series data to build a historical environmental dataset.
• Deployed an event-driven alerting system via Amazon SNS with IAM-authenticated subscriptions, triggering automated notifications to optimize energy consumption during low-emission windows.

Technologies & Skills: AWS Lambda, EventBridge, DynamoDB, SNS, IAM, Python, Pandas, REST APIs, Serverless Architecture, Event-Driven Design

💹 Real-Time Financial Risk Engine (AWS Serverless)

Monte Carlo Simulation & Portfolio Risk Assessment

• Architecture: Designed a serverless pipeline using AWS Lambda, EventBridge, and SNS to automate daily portfolio risk assessment.
• Quantitative Finance: Implemented a Monte Carlo Simulation (1,000 runs) using NumPy/Pandas to calculate Value at Risk (VaR) with a 95% confidence interval.
• Data Engineering: Integrated external financial APIs (Alpha Vantage) with robust error handling, rate-limiting logic, and custom Lambda Layers for dependency management.
• DevOps: Automated daily cron schedules via EventBridge and configured real-time alerts via Amazon SNS for high-volatility events.

Technologies & Skills: AWS Lambda, EventBridge, SNS, Python, NumPy, Pandas, Monte Carlo Simulation, VaR, Quantitative Finance, API Integration

🤖 Project ANDRA: Real-Time Multimodal Threat Detection Agent

Hoya Hacks 2026 - AI/Computer Vision Project

• Engineered a real-time event-driven pipeline integrating computer vision (YOLOv8, OpenCV) with LLM reasoning (Google Gemini 2.0 Flash) to continuously assess spatial threat proximity via webcam feeds.
• Architected an asynchronous state-machine that processes asynchronous audio/video streams, utilizing dynamic bounding-box logic to trigger distinct AI behavioral modes.
• Integrated telecommunications automation via the Twilio API, deploying a "dead man's switch" protocol that automatically dispatches emergency voice calls based on sustained audio-silence detection.

Technologies & Skills: Python, YOLOv8, OpenCV, Google Gemini AI, Twilio API, Computer Vision, LLM Integration, Real-Time Processing, Asynchronous Programming

📊 Scootistic DC: Multi-Modal Ride Service Analysis

Marketing Analytics & Design Decisions Project - GWU

• Designed a conjoint survey to assess consumer preferences for an integrated subscription service across providers like Capital Bikeshare, Lime, and Veo.
• Modeled key attributes: vehicle type options (bike/scooter/both), ride duration caps (30/60/180 minutes), and extended ride fees ($1/$5/$10 per extra minute).
• Conducted regression analysis and visualized coefficient estimates with 95% confidence intervals to evaluate impact of ride characteristics on user choice.
• Performed power analysis to determine optimal sample size (450–500), with attention to the high variability in "Vehicle type : Both" preferences.
• Proposed pricing strategies and platform partnership models to enhance convenience, retention, and manufacturer insight into user trends.

Technologies & Skills: R Programming, Conjoint Analysis, Regression Analysis, Survey Design, Statistical Modeling, Power Analysis, Marketing Analytics

🔋 San Diego Renewable Energy Transition

Capstone Project

Modeled the impact of transitioning San Diego to 60% renewable electricity using scaled CAISO data. Forecasted CO₂ emissions reduction (30%) and cost savings ($1.56 Million/year) over 2025–2034. Explored how decentralized renewables improve urban resilience to wildfires and outages.

Technologies & Skills: Python, Pandas, Matplotlib, Excel, Data Modeling, Forecasting, Energy Systems Analysis, Climate Resilience

🚗 Automobile System Architecture

Systems Engineering Course Project

Developed a Concept of Operations (ConOps), Operational View (OV-1), and functional decomposition for a vehicle system. Explored architecture alternatives like EV and cargo truck variants.

Technologies & Skills: Systems Engineering, SysML, Capella, ConOps Design, Architecture Modeling

📊 Multi-Modal Ride Service Preferences

Marketing Analytics Project

Designed and distributed a survey to capture user preferences on pricing, vehicle types, ride caps, and extended fees. Applied conjoint analysis to model user decision-making.

Technologies & Skills: Survey Design, Conjoint Analysis, R Programming, Excel, User Behavior Modeling

📉 Financial Decision-Making Model

Engineering Finance Course Project

Built a model to evaluate engineering investment decisions under uncertainty. Incorporated NPV, IRR, and sensitivity analysis in real-world tech scenarios.

Technologies & Skills: Financial Modeling, NPV, IRR, Sensitivity Analysis, Excel

📈 Marketing & Operations Campaign

Intern @ Unschool

Led a team of 6 to drive user engagement and course enrollments through digital campaigns. Analyzed performance metrics to improve outreach strategy.

Technologies & Skills: Digital Marketing, Team Leadership, Google Forms, Excel, Campaign Analytics

📶 5G Waveforms Performance Analysis over 3D Channel Model

Bachelors Final Project

Compares various 5G waveform modulation techniques (like OFDM, FBMC, UFMC, etc.) across 3D wireless channel models to identify the most efficient method. The study concludes that FBMC outperforms others in terms of low PAPR and BER, and proposes future research using AI/ML for adaptive waveform selection.

Technologies & Skills: MATLAB, Simulink, 3D Channel Modeling, Wireless Communication, Modulation Analysis, DSP, Performance Evaluation, Technical Writing

💻 Kerala Tourism Website

Web Development Project

Developed responsive front-end components and contributed to back-end functionalities for a tourism website.

Technologies & Skills: HTML, CSS, JavaScript, PHP, Responsive Design, UX Optimization

🌍 Climate Adaptation Mapping Dashboard (LLM-Powered)

AI powered Climate adaptation analysis

An AI-powered web dashboard that analyzes climate adaptation plans using Large Language Models (LLMs) to extract structured insights from unstructured policy documents. The tool automatically classifies content into four core categories — climate risks, infrastructure systems, financial sources, and stakeholders — and provides LLM-generated summaries of each city's strengths and planning gaps.

Technologies & Skills: Flask, OpenAI API, PyMuPDF, Geopy, Leaflet.js, Bootstrap, JavaScript, HTML, CSS

🤖 GW Trustworthy AI Hackathon

DAIL Forge: A Research grade AI Litigation Backend with provenance

• DAIL Forge modernizes the Database of AI Litigation by migrating low-code data into a structured PostgreSQL core, delivering a documented Research API for filtering/export and a controlled Curation API.
• A built-in provenance ledger logs every change with reason and citations, preserving legal accuracy while enabling scalable SQL-ready research now.

Technologies & Skills: Python, FastAPI, PostgreSQL, SQLAlchemy (async), Alembic, Docker, Pandas/OpenPyXL, and PostgreSQL full-text search (GIN/TSVector + pg_trgm). Backend API development, database design/migrations, ETL & incremental data pipelines, data provenance/audit logging, and snapshot-based data versioning.

🤖 Hoya Hacks 2026 - Georgetown University

Project ANDRA: Real-Time Multimodal Threat Detection Agent

• Engineered a real-time event-driven pipeline integrating computer vision (YOLOv8, OpenCV) with LLM reasoning (Google Gemini 2.0 Flash) to assess spatial threat proximity.
• Architected an asynchronous state-machine processing audio/video streams with dynamic bounding-box logic.
• Integrated Twilio API for emergency telecommunications automation with "dead man's switch" protocol.

Technologies & Skills: Python, YOLOv8, OpenCV, Google Gemini AI, Twilio API, Computer Vision, Real-Time Processing

Cerebral Valley AI Fintech Hackathon 2025 - New York City

Participant

SwapStack - An Electronics based Lending Platform.

• Designed and built the core backend for an AI-driven P2P lending app at a fintech hackathon.
• Created the complete MySQL database schema and developed the API endpoints using Python and FastAPI.

Technologies & Skills: Python, FastAPI, MySQL, PyMySQL, Cloudinary, Docker, Git, GitHub, VS Code.

🌟 Vice President

The George Washington University Desis Organization
October 2024 – January 2026 | Washington, DC

Led planning, budgeting, managing member engagement and recruitment of executive board, ensuring smooth operations and initiatives to foster community among 250+ graduate Indian students.

Skills: Leadership, Community Engagement, Project Coordination, Team Management, Event Strategy, Budgeting

💰 Financial Officer

Google Developer Student Club, George Washington University
October 2024 – January 2026 | Washington, DC

Managed the budgeting, allocation, and tracking of funds for large-scale on-campus events with over 150+ participants. Coordinated with multiple teams to ensure proper financial planning and vendor payments, maintaining transparency and cost efficiency.

Skills: Budgeting, Event Planning, Financial Oversight, Collaboration, Reporting