Hi, I'm Pranav Dhawan

Currently building AI workplace automation at the American Chemical Society in Washington, DC.
Founder, SideQuest India.
MS Data Science from George Washington University.

View My Work Get In Touch Visit SideQuest

ABOUT ME

I’m an AI Engineer, Data Scientist, and Founder of SideQuest India, focused on building production AI systems and early-stage products.

My background spans AI agents, NLP, computer vision, document intelligence, analytics, and workflow automation. I hold a Master’s in Data Science from George Washington University and a Bachelor’s in Computer Science and Engineering.

I’m currently building SideQuest, a social platform designed to make it easier for people to discover plans, go out, and connect through real-world experiences.

I’m most interested in ambiguous problems, fast iteration, and building products people actually use.

Experience with

American Chemical Society
EY
HCLTech
Lumina Datamatics

SKILLS & TECHNOLOGIES

Language ML Data & Cloud Visualization AI

PROFESSIONAL EXPERIENCE

July 2026 - Present

Current

Founder

SideQuest India

Founded and lead SideQuest India end to end across product, growth, website, and operations — a social platform for discovering plans, going out, and connecting through real-world experiences.

Launched the first web experience to 500+ users in its first 7 days.

May 2026 - Present

Current

AI Workplace Engineer Intern

American Chemical Society | Washington, DC

Owned the architecture and production deployment of an AI-orchestrated service-desk workflow integrating Microsoft Copilot, Ivanti, and SharePoint; automated classification, response generation, routing, and follow-up for approximately 245 of 350 monthly tickets.

Engineered an onboarding and offboarding agent that automates lifecycle-aware tracking and documentation of employee hardware assignments, strengthening asset traceability from provisioning through return.

Authored the AI governance framework for formal organizational adoption, defining data-protection, knowledge-access, human-review, and responsible-deployment controls for enterprise AI workflows.

Technologies Used:

Microsoft Copilot Ivanti SharePoint AI Governance Human-in-the-Loop Automation

June 2026 - Present

Current

Independent Contractor - AI

Siva Info LLC | New York, NY

Owned development of edition-aware PDF-diff tooling that identifies text movement, grammatical edits, deletions, and additions, creating a reliable change-detection layer for downstream content updates.

Re-engineered an XML tagging and classification pipeline across approximately 3,000 entries, increasing completeness and accuracy from 32% to 99% while cutting processing time by approximately 50%.

Technologies Used:

XML Document Processing PDF Comparison Pipeline Automation

August 2024 - May 2026

Graduated

Master of Science, Data Science

George Washington University | Washington, DC

GPA: 3.74/4.0

Completed a published research paper and technical report from the Multimodal Techniques for Financial Time Series Forecasting capstone project.

Completed dataset reports analyzing U.S. government health, CBP.gov, and WMATA datasets.

Relevant Coursework:

Machine Learning Deep Learning NLP Data Mining Data Warehousing Data Visualization Cloud Computing Time Series Analysis

February 2024 - August 2024

Machine Learning Engineer

Lumina Datamatics | Chennai, India

Owned the end-to-end development and AWS SageMaker deployment of a YOLOv8 document intelligence pipeline processing more than 10,000 documents per day, eliminating manual processing and improving extraction accuracy by 16%.

Replaced legacy LayoutParser components with a custom computer vision pipeline evaluated using mAP@50 and mAP@50-95, reducing inference latency by approximately 0.3 seconds per page.

Architected and deployed a hybrid RAG system for internal legal document search using Sentence Transformers, FAISS, BERT QA, and BART, reducing retrieval time from minutes to under 5 seconds.

Redesigned factual extraction around extractive BERT QA after identifying hallucinated structured fields from generative BART outputs, improving grounding for dates, names, and case metadata.

Technologies Used:

Python YOLOv8 Computer Vision RAG BERT QA FAISS AWS SageMaker

August 2020 - May 2024

Graduated

B.Tech in Computer Science and Engineering

Manipal University Jaipur | Rajasthan, India

GPA: 8.51/10.0

Wrote a comparative analysis paper on transformer models versus LSTM for sentiment classification across the X platform.

Relevant Coursework:

Algorithms & Data Structures Database Management Systems

July 2023 - September 2023

Machine Learning Intern

HCLTech | Noida, India

Built clustering, Logistic Regression, and Random Forest models across data from 500+ employees, achieving 87% predictive accuracy and identifying the five strongest drivers of workforce performance.

Engineered 12+ behavioral and productivity features using SQL and Python and surfaced model findings through Tableau dashboards.

Technologies Used:

Python SQL Logistic Regression Random Forest Tableau

May 2023 - July 2023

Summer Intern

EY | Gurugram, India

Developed Power BI dashboards for Sales and HR functions, visualizing revenue trends, customer acquisition, headcount, attrition, and compensation benchmarks.

Automated ETL workflows across more than five data sources using Alteryx, eliminating manual cleaning errors and supporting 100% reporting accuracy across monthly business reviews.

Technologies Used:

Power BI Alteryx ETL Data Visualization

FEATURED PROJECTS

Stock Screen

A real-time AI-powered terminal that unifies stock analysis, market news, company filings, forecasting workflows, and market context into a single interface. Designed for investors, it helps compare signals quickly and turn live market data into actionable research. Archived: it was used by 100+ profiles, but there were not enough paid users to keep it running.

GCP Python ML

Code

Multimodal Techniques for Equity Forecasting

Conducted a benchmark study on the FinMultiTime dataset using multiple data modalities, evaluating 10+ different model architectures and ensembles. The findings were published in a research paper and technical report.

Python LSTM FinBERT Attention

Code

Edge-Based PII Detection & Censoring System

Achieved 98.1% F1-score and 97.9% recall across 54 PII entity types by architecting and benchmarking 4 transformer architectures, selecting DeBERTa as the production model and deploying via ONNX for <100ms inference.

DeBERTa ONNX Streamlit

Code

Singularity — a cited answer in the activity timeline beside an inspector showing the exact local source range used

Singularity — Local-First Memory for AI Assistants

A local memory and permission layer for AI assistants: it imports your chat history, answers from your own files with citations you can open to the exact source range, and holds every outbound call behind a redaction gate you approve before anything leaves the machine.

TypeScript RAG SQLite FTS5 Ollama

Code

Client work 2 production websites

Alongside my ML work, I design, ship, and maintain production websites for businesses — the same ownership and operating discipline I bring to AI systems.

AEROSPACE · NEW DELHI

Aevantis Aerospace

Production marketing site for an unmanned-systems manufacturer, presenting product lines, capabilities, and an enquiry flow.

I maintain the site’s content, hosting, and performance.

Visit site

OUTDOOR ADVERTISING · DELHI NCR

Admiles Media

Production site for an outdoor advertising company, with media-location information, project galleries, and lead capture.

I maintain the site’s content, hosting, and performance.

Visit site

GET IN TOUCH

Download Resume

pranavdhawan99@gmail.com