// Languages
function listLanguages()
{
let languages = [
"Python",
"JavaScript",
"R",
"SQL",
"Scala",
"C++"
];
console.log(languages);
}
Hello & Welcome
I Am A
An eloquent tale of my journey
Data scientist by training, an AI engineer by impact. I'm an AI and Data Science Engineer who loves turning complex ideas into real, usable solutions. I've worked across legal, biomedical, and education spaces, building systems powered by large language models and retrieval-augmented generation that help people make smarter decisions. Whether it's streamlining legal research or speeding up biomedical insights, I enjoy working on projects that make a real impact. I recently completed my Master's in Data Science at George Washington University with a GPA of 3.97, where I got to dive deep into everything from NLP to cloud deployment. Along the way, I've built and shipped AI tools at the World Bank and Avenio Corporation, taking ideas from prototype to production. I know how to take an idea, build a prototype, deploy it in the real world, and make sure it delivers value. I'm hands-on with everything from machine learning and cloud infrastructure to user experience and product thinking. I care about making AI systems that are not just technically sound but actually useful.
6
Languages
8
Tools
1
Certificates
12
Projects
Skills I've Developed and Mastered
I'm hands-on with everything from machine learning and cloud infrastructure to user experience and product thinking. I specialize in building AI systems powered by large language models and retrieval-augmented generation, taking projects from prototype to production deployment across AWS, GCP, and Azure.
- Large Language Models & Agentic AI Systems
- Cloud Deployment & MLOps
- Machine Learning & Deep Learning
- Retrieval-Augmented Generation & Context Engineering
Work Experience
Apr 2025 – Present
Founding Software & AI Engineer, Avenio Corporation, San Francisco, CA (Remote)
• Architected RAG pipeline for 10K biomedical documents, improving retrieval speed 40% using LangChain, Qdrant, and PGVector.
• Built persona-driven AI agents processing 100K queries at 4s latency via multi-agent orchestration.
• Implemented prompt versioning and evaluation hooks, reducing hallucinations and improving reliability.
• Delivered production pipelines with observability dashboards and AWS deployments via Docker/Kubernetes, ensuring 99.9% uptime.
Jan 2025 – May 2025
AI Engineer (Capstone Fellow), World Bank Group, Washington, D.C.
• Improved access to legal information with a multilingual AI assistant, achieving 90% accuracy.
• Processed 478 legal documents using Python (scraping, OCR, and cleaning) to create a structured, searchable dataset.
• Enabled local language responses to make legal content more accessible to non-English speakers.
• Deployed the assistant on GCP using Docker, ensuring scalable access and average response time of 3.2 seconds.
March 2025 – Present
Student Technical Support Specialist Washington, D.C., USA
- Guided students on software setup, code debugging, and managing Git workflows.
- Resolved Python, R, and SQL issues in Jupyter and VS Code environments.
Jan 2025 – Present
Graduate Instructional Assistant – Data Visualization, The George Washington University, Washington, D.C., USA
- Guided undergraduates in mastering data visualization using Python and RStudio.
- Helped design assignments and grade projects focused on visual analytics.
- Delivered hands-on sessions for interactive dashboards and data storytelling.
- Supported students in applying statistical methods and visualization principles.
Aug 2024 – Dec 2024
Graduate Instructional Assistant – Data Science Capstone, The George Washington University, Washington, D.C., USA
- Guided students in data extraction, preprocessing, and analysis for capstone projects.
- Led discussions on project strategy, model evaluation, and data visualization.
Education
Anticipated May 2025
Master of Science, Data Science, The George Washington University, Washington DC.
Relevant Coursework: Data Mining, Data Warehousing, Visualization of Complex Data, Machine Learning, Cloud Computing, Algorithm Design, NLP for Data Science, Linux for DevOps, Foundational Pedagogy GradAsst.
Jun 2019 - Jul 2023
Bachelor of Technology, Computer Science, Amrita Vishwa Vidyapeetham, India.
Relevant Coursework: Natural Language Processing, Machine Learning, Distributed Systems, DBMS, Time Series Analysis, Mining of Massive Datasets, Social Network Analysis.
Projects
NeXT Mission: AI-Powered Veteran Support
Developed a web platform to support U.S. military veterans transitioning to civilian life, featuring a resume builder, AI chatbot, mentor discovery Powered by Meta LLaMA 4 and Groq API.
Multi-Agent Financial Analytics Engine
Built a multi-agent AI bot for real-time financial insights using OpenAI, Groq, and Yahoo Finance APIs. Automated financial analysis and insight generation for end users.
Data-Driven Insights for Apple Stock Market Predictions
Developed robust time-series forecasting models, including LSTM with XGBoost and Voting Regressor, and enhanced ARIMA models.
Advanced Data Visualization of Los Angeles Crime Patterns
Developed and optimized a data visualization platform for analyzing Los Angeles crime trends using Tableau and Python.
Credit Card Churn Analysis: Predictive Modeling for Customer Retention
Developed a churn prediction model using Random Forest, Logistic Regression, and Decision Tree algorithms.
Supply Chain Management Database Efficiency Analysis
Investigated the efficiency of MySQL, MongoDB, and Neo4j in supply chain management by benchmarking their performance.
Languages & Tools
// Clouds
function listClouds()
{
let clouds = [
"Amazon Web Services (AWS)",
"Google Cloud Platform (GCP)",
"Microsoft Azure"
];
console.log(clouds);
}
// NLP and LLMs
function listNLPandLLMs()
{
let nlpAndLLMs = [
"LangChain",
"LlamaIndex",
"Hugging Face",
"OpenAI GPT",
"Transformers",
"BERT",
"spaCy"
];
console.log(nlpAndLLMs);
}
// ML Frameworks & Tools
function listMLFrameworks()
{
let mlFrameworks = [
"TensorFlow",
"PyTorch",
"Scikit-learn",
"Keras",
"XGBoost",
"Pandas",
"NumPy"
];
console.log(mlFrameworks);
}
// Frameworks
function listFrameworks()
{
let frameworks = [
"Docker",
"Kubernetes",
"FastAPI",
"Django",
"React",
"Next.js",
"Streamlit",
"Spark",
"Kafka"
];
console.log(frameworks);
}
// Vector Databases & DevOps
function listVectorDBs()
{
let vectorDBs = [
"Qdrant",
"Pinecone",
"FAISS",
"Weaviate",
"PGVector",
"GitHub Actions",
"PostgreSQL"
];
console.log(vectorDBs);
}
SearchRank AI: Neural Search & Ranking System
Abstract: Intelligent search system with neural ranking using BERT for semantic search and learning-to-rank algorithms.
Tools & Technologies Used: PyTorch, BERT, FAISS, Learning-to-Rank.
Conclusion: Production-ready neural search engine for personalized retrieval and ranking.
TripFlow AI: Multi-Agent Travel Planner
Abstract: Built a custom AI travel planner using OpenAI Agent Kit with modular workflows combining classification and itinerary agents.
Tools & Technologies Used: OpenAI Agent Kit, Flight Widget, MCP Servers, Visual Workflow Editor.
Conclusion: Created a real-time flight search and travel planning system with drag-and-drop UI for rapid prototyping and seamless agent orchestration.
JobWatch AI: Automated Job Application Tracker
Abstract: Built an AI-powered automation that tracks job applications while I sleep, processing emails at 1 AM daily using OpenAI to extract job details.
Tools & Technologies Used: Make.com, OpenAI GPT, Gmail API, Google Sheets, Slack, No-Code Automation.
Conclusion: Automated job tracking workflow eliminates duplicates, provides Slack alerts, and maintains a fully updated application tracker with zero manual effort.
NeXT Mission: AI-Powered Veteran Support
Abstract: An AI-powered platform supporting military veterans transitioning to civilian life with a resume builder, chatbot, mentor discovery.
Tools & Technologies Used: Python, Django, Vue.js, Meta LLaMA 4, Groq API, MongoDB, SerpAPI.
Conclusion: A unified platform showcasing Meta's models for real-world impact, developed for the ai+expo hackathon.
Multi-Agent Financial Analytics Engine
Abstract: Built a multi-agent AI bot for real-time financial insights using OpenAI, Groq, and Yahoo Finance APIs.
Tools & Technologies Used: Python, FastAPI, OpenAI API, Groq API, Yahoo Finance API.
Conclusion: Delivered a web-based solution that automates financial analysis and insight generation.
AI Meets Law: Transforming Legal Research with RAG and Fine-Tuned LLM
Abstract: Integrated RAG and fine-tuned LLMs for efficient and precise legal research.
Tools & Technologies Used: Python, Streamlit, FAISS, GPT fine-tuning, SentenceTransformer
Conclusion: Delivered an AI solution for precise legal research with user-friendly interaction.
Text Classification Using SciBERT
Abstract: Multi-label text classification with SciBERT and a multi-head architecture for scientific abstracts.
Tools & Technologies Used: Python, SciBERT, PyTorch, LSTM, CNN
Conclusion: Delivered a high-performing text classifier leveraging SciBERT and innovative deep learning techniques.
Data-Driven Insights for Apple Stock Market Predictions
Abstract: Developed time-series forecasting models to analyze Apple Inc.'s stock data spanning nearly four decades.
Tools & Algorithms Used: Python, LSTM, XGBoost, Voting Regressor, ARIMA
Conclusion: Improved accuracy in stock predictions through feature engineering, hyperparameter optimization, and ensemble techniques.
Advanced Data Visualization of Los Angeles Crime Patterns
Abstract: Created a data visualization platform for analyzing Los Angeles crime trends using a 900K record dataset.
Tools Used: Tableau, Python
Conclusion: Enhanced law enforcement strategies through interactive dashboards highlighting key geographic and temporal patterns.
Credit Card Churn analysis
Abstract: Developed a churn prediction model to enhance customer retention in the credit card industry.
Tools & Algorithms Used: R, Random Forest, Logistic Regression, Decision Tree
Conclusion: Significantly improved customer loyalty strategies through analysis of transaction data.
Supply Chain Management Database Efficiency Analysis
Abstract: Investigated the efficiency of various databases in supply chain management using DataCo's dataset.
Tools Used: MySQL, MongoDB, Neo4j
Conclusion: Optimized database selection for supply chain applications based on data retrieval speed and network pathfinding performance.
Retail Analytics: Utilizing ML for Subscription Insights
Abstract: Predictive analytics framework using Random Forest and Neural Network models for Customer Shopping Preference analysis.
Tools & Algorithms Used: Python, Random Forest, Neural Network
Conclusion: Achieved 97% prediction accuracy in customer subscription behavior through advanced data normalization, categorical encoding, and hyperparameter optimization techniques.
Indoor Multi-Camera Human Tracking
Abstract: Developed a state-of-the-art multi-camera people detection and tracking system for indoor environments.
Tools Used: Python, OpenCV, TensorFlow, Keras
Conclusion: Achieved substantial performance improvements in open environments by successfully addressing occlusion challenges.
Achievement Hub
AWS Certified Cloud Practitioner
Earned the AWS Certified Cloud Practitioner certification, demonstrating foundational knowledge of AWS Cloud services.
Validated expertise in cloud fluency, AWS services, and ability to identify essential AWS tools for cloud-focused projects.
Founding Engineer – Avenio Corporation
Joined Avenio Corporation as a Founding AI/ML Engineer, building real-time agentic AI assistants for biomedical research.
Developed scalable AI pipelines using LLMs, LangChain, and AWS to deliver fast, accurate insights from scientific literature.
AI+ Expo Hackathon (Meta Track – Runner-Up)
Secured 2nd place in the Meta Track at the AI+ Expo Hackathon for building NeXT Mission, a veteran-focused AI assistant powered by Meta's LLaMA 4.
Recognized for impactful use of generative AI and full-stack deployment under tight hackathon timelines.
AWS Summit & Expo – Washington, DC
Participated in the AWS Summit, engaging with cloud professionals and hands-on workshops on GenAI, ETL pipelines, and cloud-native tools.
Explored innovations in AI/ML infrastructure and broadened my knowledge in scalable cloud deployment.
Graduation – Master's in Data Science (GWU)
Graduated with a Master of Science in Data Science from The George Washington University with a 3.97 GPA.
Honed skills in machine learning, NLP, and statistical modeling, laying the foundation for applied AI research.
World Bank – AI Project Presentation
Presented a GenAI legal assistant project at the World Bank, applying RAG pipelines and LLMs to improve access to legal resources.
Earned recognition from mentors and peers for innovation, clarity, and potential policy impact.
Graduate Instructional Assistant – Data Science Capstone
Guided undergraduates through their end-to-end capstone projects—from idea generation to final presentations. Grateful to Professor Sushovan Majhi for his mentorship and trust throughout the semester.
Fine-Tune Your LLM
Through this course, I honed advanced skills in fine-tuning large language models to suit specific business and technical needs.
RAG and Fine-Tuning Explained
This course enhanced my understanding of Retrieval-Augmented Generation (RAG) and fine-tuning techniques for LLMs, showcasing their practical applications.
TensorFlow: Working with NLP
In this course, I acquired hands-on skills in TensorFlow for building natural language processing (NLP) models efficiently.
GPT-4 Foundations: Building AI-Powered Apps
This course provided me with foundational knowledge to build AI-powered applications using GPT-4, focusing on software development and generative AI principles.
Introduction to Generative AI with GPT
This achievement highlights my foundational knowledge in the principles of generative AI using GPT models, focusing on their capabilities and application scenarios.
Generative AI: Working with Large Language Models
I gained advanced skills in large language models (LLM), natural language processing (NLP), and generative AI.
Introduction to Prompt Engineering for Generative AI
I gained essential skills in natural language processing, generative AI & Prompt Engineering.
Generative AI: Introduction to Large Language Models
I gained valuable insights into the architecture and applications of large language models and generative AI.
Introduction to Large Language Models
I gained foundational knowledge in the architecture and functionality of large language models (LLMs).
Learning Design Thinking
I acquired advanced competencies in design thinking methodologies for the effective visualization and interpretation of complex datasets.
Design Thinking: Prototyping
I acquired advanced competencies in design thinking methodologies and prototyping techniques.
Student Athletic Assistant at George Washington University
This picture reflects my role as a Student Athletic Assistant at George Washington University, where I ensured excellent guest services and resolved attendee concerns at basketball events.
DataCamp Intermediate SQL
This certification from DataCamp affirms my intermediate skills in SQL, focusing on complex queries and database manipulation for data analysis.
GitHub Stats & Activity
Featured Repositories
Loading repositories...
Contact Me