2026
ResumeOpenClaw — AI-Tailored Resumes & Cover Letters in Seconds
ResumeOpenClaw is a privacy-first web app that generates ATS-optimized resumes and cover letters tailored to any job description. Paste your CV and a JD, and Claude rewrites your bullets with relevant keywords, selects the most impactful experiences, and outputs a polished LaTeX PDF — all processed directly between your browser and Anthropic. No CV data ever touches our servers. Built with React, FastAPI, Claude API, and Tectonic (LaTeX compiler).
ResumeOpenClaw — AI-Tailored Resumes & Cover Letters in Seconds
ResumeOpenClaw is a privacy-first web app that generates ATS-optimized resumes and cover letters tailored to any job description. Paste your CV and a JD, and Claude rewrites your bullets with relevant keywords, selects the most impactful experiences, and outputs a polished LaTeX PDF — all processed directly between your browser and Anthropic. No CV data ever touches our servers. Built with React, FastAPI, Claude API, and Tectonic (LaTeX compiler).
OfferOpenClaw — AI-Powered PhD Faculty Outreach Automation Agent
OfferOpenClaw is an email-triggered automation agent that streamlines PhD faculty outreach. Simply email your CV and the system automatically scrapes faculty pages, analyzes research alignment via Semantic Scholar, rates compatibility (0–10), and generates personalized cold emails for top matches — all results delivered back to your inbox. Built with Claude API, BeautifulSoup, Gmail IMAP/SMTP, and PyMuPDF.
OfferOpenClaw — AI-Powered PhD Faculty Outreach Automation Agent
OfferOpenClaw is an email-triggered automation agent that streamlines PhD faculty outreach. Simply email your CV and the system automatically scrapes faculty pages, analyzes research alignment via Semantic Scholar, rates compatibility (0–10), and generates personalized cold emails for top matches — all results delivered back to your inbox. Built with Claude API, BeautifulSoup, Gmail IMAP/SMTP, and PyMuPDF.
2025
Yelp ChatDB — Natural Language Restaurant Search System
Yelp ChatDB is a full-stack chatbot application that enables users to search for restaurants and manage personal wishlists using natural language queries. The backend leverages GPT for intent parsing, MongoDB for caching and data storage, and the Yelp Fusion API for real-time restaurant data. The frontend is a lightweight React-like interface that supports conversational search.
Yelp ChatDB — Natural Language Restaurant Search System
Yelp ChatDB is a full-stack chatbot application that enables users to search for restaurants and manage personal wishlists using natural language queries. The backend leverages GPT for intent parsing, MongoDB for caching and data storage, and the Yelp Fusion API for real-time restaurant data. The frontend is a lightweight React-like interface that supports conversational search.
Transit Triumph or Traffic Tangle? Evaluating Los Angeles’ Transit Equity for the 2028 Car-Free Olympics
This project assesses the feasibility of a “car-free” 2028 Los Angeles Olympics, where all venue access relies on public transport. Using the Two-Step Floating Catchment Area (2SFCA) method, it analyzes accessibility, evaluating infrastructure, population density, and socioeconomic factors. By mapping the accessibility index (AI) across neighborhoods, the study examines whether the transit network can support the event. Future directions explore equity in access and the long-term transportation legacy of the Games.
Transit Triumph or Traffic Tangle? Evaluating Los Angeles’ Transit Equity for the 2028 Car-Free Olympics
This project assesses the feasibility of a “car-free” 2028 Los Angeles Olympics, where all venue access relies on public transport. Using the Two-Step Floating Catchment Area (2SFCA) method, it analyzes accessibility, evaluating infrastructure, population density, and socioeconomic factors. By mapping the accessibility index (AI) across neighborhoods, the study examines whether the transit network can support the event. Future directions explore equity in access and the long-term transportation legacy of the Games.
Foursquare Open Source Places - POI Data Processing
Foursquare Open Source Places (FSQ OS Places) is a high-quality, open POI (Points of Interest) dataset released by Foursquare, containing over 104 million POIs worldwide. While platforms like OpenStreetMap (OSM) and Overture Maps aim to improve open POI coverage, FSQ OS Places provides a more extensive and precise dataset. This repository provides a step-by-step guide on downloading POI data and converting it from GeoJSON to Shapefile (SHP) for use in ArcGIS Pro, QGIS, and other GIS applications.
Foursquare Open Source Places - POI Data Processing
Foursquare Open Source Places (FSQ OS Places) is a high-quality, open POI (Points of Interest) dataset released by Foursquare, containing over 104 million POIs worldwide. While platforms like OpenStreetMap (OSM) and Overture Maps aim to improve open POI coverage, FSQ OS Places provides a more extensive and precise dataset. This repository provides a step-by-step guide on downloading POI data and converting it from GeoJSON to Shapefile (SHP) for use in ArcGIS Pro, QGIS, and other GIS applications.
DeepLabV3Plus for Satellite Image Segmentation - OpenEarthMap
This repository contains the computer code that supported the publication of our research: "Multi-source Tri-environmental Conceptual Framework for Fire Impact Analysis" (under review in Urban Informatics). This package helps researchers quickly generate high-resolution population density layers using dasymetric mapping, a sophisticated geospatial technique that leverages detailed land cover data to distribute demographic data across predefined spatial units, such as census blocks.
DeepLabV3Plus for Satellite Image Segmentation - OpenEarthMap
This repository contains the computer code that supported the publication of our research: "Multi-source Tri-environmental Conceptual Framework for Fire Impact Analysis" (under review in Urban Informatics). This package helps researchers quickly generate high-resolution population density layers using dasymetric mapping, a sophisticated geospatial technique that leverages detailed land cover data to distribute demographic data across predefined spatial units, such as census blocks.
2024
Dasymetric Mapper: High-Resolution Population Density Layer Generation
This repository contains the computer code that supported the publication of our research: "Multi-source Tri-environmental Conceptual Framework for Fire Impact Analysis" (under review in Urban Informatics). This package helps researchers quickly generate high-resolution population density layers using dasymetric mapping, a sophisticated geospatial technique that leverages detailed land cover data to distribute demographic data across predefined spatial units, such as census blocks.
Dasymetric Mapper: High-Resolution Population Density Layer Generation
This repository contains the computer code that supported the publication of our research: "Multi-source Tri-environmental Conceptual Framework for Fire Impact Analysis" (under review in Urban Informatics). This package helps researchers quickly generate high-resolution population density layers using dasymetric mapping, a sophisticated geospatial technique that leverages detailed land cover data to distribute demographic data across predefined spatial units, such as census blocks.
Geospatial Analysis of Socioeconomic Status and Restaurant Distribution in LA
This data science project aims to perform a geospatial analysis of socioeconomic status and its impact on restaurant distribution across Los Angeles County. By leveraging diverse web sources, this study examines the correlation between socioeconomic factors — like education and income — and the variety of restaurants available in different areas. The goal is to understand how these elements influence food service diversity, contributing valuable insights into urban planning and social equity.
Geospatial Analysis of Socioeconomic Status and Restaurant Distribution in LA
This data science project aims to perform a geospatial analysis of socioeconomic status and its impact on restaurant distribution across Los Angeles County. By leveraging diverse web sources, this study examines the correlation between socioeconomic factors — like education and income — and the variety of restaurants available in different areas. The goal is to understand how these elements influence food service diversity, contributing valuable insights into urban planning and social equity.