Projects

A showcase of AI and data science projects that demonstrate real-world impact and technical excellence across various domains.

Airport Now: Real-Time Airport Status Dashboard
Production

Airport Now: Real-Time Airport Status Dashboard

Personal ProjectMar 2026

Built a traveler-facing web app that combines checkpoint wait data, live flight boards, nearby air traffic, route-level delay risk, and expiring traveler reports in a single airport view.

Impact:

Helps travelers make faster departure decisions by consolidating fragmented airport signals into one live interface.

Tech Stack:

React 19TypeScriptBunVercelAPI IntegrationRealtime Data
World Press Monitor: Token-Gated News Intelligence Portal
Production

World Press Monitor: Token-Gated News Intelligence Portal

Personal ProjectFeb 2026 - Present

Built a customer-only news intelligence portal with hourly RSS ingest, PostgreSQL-backed search, token-gated APIs, and filtered article access by section, source, country, and date.

Impact:

Moves high-volume news monitoring from static exports to authenticated, scalable, customer-specific access.

Tech Stack:

TypeScriptBunPostgreSQLDockerRSS IngestAPI Development
Audit Risk Intelligence Platform
Production

Audit Risk Intelligence Platform

Deloitte2024 - Present

Led the data pipeline and audit-risk labeling workflow for global news intelligence.

  • Built a data ETL pipeline for news metadata and source-credibility labeling across 17 countries, partnering with regional Deloitte SMEs to map trusted sources
  • Built relevance + audit-risk classification using title/summary/company tags; curated a goldenset with SMEs for evaluation
  • Implemented client-specific processing and DUNS-based entity updates to handle M&A changes near real time; processes 40–50K articles/day and ~20K labeled records
  • Delivered RiskSensing API on AKS with QA test suites, OpenTelemetry monitoring, and LLM cost optimization from ~$40/day to ~$6/day (GPT-4/4o/5)

Impact:

Keeps audit-risk data structured, current, and reliable for downstream RiskSensing, API Platform, and Omnia teams.

Tech Stack:

PythonAzureAKSOpenTelemetryLLMRAG+4
Unseen: Anonymous Voice Support
Active

Unseen: Anonymous Voice Support

Personal ProjectDec 2025 - Present

Anonymous voice support app for people preparing for jobs or major exams, or pushing through burnout and depression. No follows, no networking, no influencer dynamics.

Impact:

Creates a safe, low-pressure space where encouragement feels human and sincere.

Tech Stack:

React NativeExpoTypeScriptSupabaseSupabase AuthWhisper API (STT)+2
PayLoadApp: Mobile Invoice Generator
Completed

PayLoadApp: Mobile Invoice Generator

Personal ProjectAug 2025 - Oct 2025

Mobile invoicing for field technicians, dog walkers, and private tutors. Create invoices on-site with voice input or templates, attach proof photos, and share with clients immediately.

Impact:

Replaces paper forms with faster billing, clearer documentation, and more professional client communication.

Tech Stack:

React NativeExpoTypeScriptSupabaseSupabase AuthWhisper API (STT)+2
Code Notify: Cross-Platform Desktop Notifications for AI Coding Tools
Production

Code Notify: Cross-Platform Desktop Notifications for AI Coding Tools

Personal ProjectJul 2025 - Present

Built a cross-platform CLI for Claude Code, OpenAI Codex, and Gemini CLI that sends desktop, sound, and voice notifications when tasks complete or user input is needed.

Impact:

Reduces context switching for AI-assisted development with native notifications, project-specific settings, and simple Homebrew installation across macOS, Linux, and Windows.

Tech Stack:

ShellCLI DevelopmentCross-platform DevelopmentHomebrewDesktop NotificationsConfiguration Management
Nursing AI Diagnostic System with Human-in-the-Loop
Research

Nursing AI Diagnostic System with Human-in-the-Loop

GWU Research Lab2023-2024

Led the end-to-end development of an intelligent nursing diagnostic system. I designed and implemented a Retrieval-Augmented Generation (RAG) system that references a knowledge base of 80+ documented nursing scenarios. When new patient data is entered, the system retrieves the top 3 most similar scenarios to inform its diagnostic suggestions.

Impact:

Crucially, I architected a Human-in-the-Loop (HITL) feedback mechanism. Nurses can provide feedback on the AI's suggestions, which is then vectorized and stored in our Deeplake (Vector DB). This creates a self-improving system where accuracy and relevance continuously increase with each interaction.

Tech Stack:

RAGHuman-in-the-loopGPT-4Vector DatabaseData LakePython+1
Multi-modal AI for Autism Analysis
Research

Multi-modal AI for Autism Analysis

GWU Research Lab2023-2024

I was responsible for the entire audio processing pipeline. My primary role was to extract and analyze audio from raw video footage, tackling the significant challenge of low-quality audio in Korean. I developed a noise reduction process using spectral subtraction and a filtering logic to isolate the child's voice from background noise and parental speech, significantly improving the quality of data for the model.

Impact:

This work was critical for enabling the analysis of 'in-the-wild' videos, a key goal of our research. By successfully processing the audio data, I helped create a system that provides objective, data-driven insights to support clinicians, making behavioral analysis more efficient and accessible.

Tech Stack:

Audio ProcessingNoise ReductionSpectral SubtractionKorean NLPSpeech RecognitionPython+1
Private LLM with RAG
Completed

Private LLM with RAG

Atos Zdata2023

Developed a private LLM with RAG using LangChain and vector databases (FAISS, Qdrant) to support Q&A, summarization, and enterprise document retrieval. Built an auto-updating vector index that detects document changes in real time and compared LLMs (Llama-2, Falcon, GPT4ALL) for accuracy and latency.

Impact:

Enabled automated draft responses for RFP/RFI/SoW workflows and faster retrieval across internal knowledge bases.

Tech Stack:

PythonLangchainRAGFAISSQdrantLlama-2+2
Pepper Robot Navigation with HoloLens
Research

Pepper Robot Navigation with HoloLens

GWU Research Lab2023

Developed a multimodal AI system enabling the Pepper robot to navigate autonomously. The robot uses Microsoft HoloLens for real-time environment scanning, obstacle detection, and spatial mapping.

Impact:

This research aimed to give Pepper spatial awareness for free movement in new environments, with future goals of recognizing and remembering individuals. LLM was used for conversational interaction.

Tech Stack:

Microsoft HoloLensComputer VisionROSPythonRoboticsLLM+2
Pepper Robot AI Integration for Healthcare
Research

Pepper Robot AI Integration for Healthcare

GWU Research Lab2023

I took over a stalled project that used a traditional NLP model and a Unity 3D avatar. I completely redesigned the system by integrating the GPT API for fluid conversation and OpenAI's Whisper API for robust speech-to-text and text-to-speech capabilities. The virtual avatar was replaced with a physical Pepper robot for tangible user interaction.

Impact:

This overhaul transformed a non-interactive prototype into a successful project. The new system was not only presented at a university poster session but was also significant enough for my supervising professor to present at an academic conference.

Tech Stack:

GPT APIWhisper APISTT/TTSPepper RobotHuman-Robot InteractionPython+3
AI-Driven Defect Detection for Aerospace Composites
Academic

AI-Driven Defect Detection for Aerospace Composites

Bauman Moscow State Technical University (Bachelor's Thesis)2022

Developed a novel methodology combining Finite Element Analysis (FEA) with Machine Learning to predict structural integrity in aerospace components.

Impact:

Achieved 95-97% predictive accuracy by generating a proprietary dataset from scratch via complex ANSYS simulations.

Tech Stack:

ANSYS (FEA)Machine LearningComputer VisionData GenerationPython