Rufus Linh is a developer with a strong proficiency in Node/Javascript and MongoDB. Rufus has contributed to enhancing Spotify's next song recommendation feature, making it faster. With a background comprising approximately 60% engineering and 40% research, Rufus is keen on exploring roles that involve more research. He is particularly fascinated by the recent advancements in multi-modal AI, such as Google's newly introduced Gemini, and is eager to participate in related R&D initiatives.
Project list
Ballistic Matching System - Vietnam
Developed a large-scale firearm identity matching system by processing 3D scans of bullet toolmarks. The system is trained on the open NBTRD dataset and enhances search efficiency by transforming search time from minutes to sub-seconds. This was achieved by replacing an open-sourced R engine with a Java implementation of Hierarchical Navigable Small World (HNSW) for vector search. Utilized and adapted open-source algorithms such as CMC and CMS to create a model that translates 3D scans into searchable vector embeddings.
Supervise a small team on technical nuances
Collaborate with project managers to ensure project timeline
Technologies: Java, Spring Boot, R, Three.js, HNSW, CMC, CMS
Devexa AI Project - Vietnam
AI solution for customer care and sales tailored specifically for financial service providers.
Understand clients' key pain points and challenges.
Propose matching solutions.
Technologies: Kotlin, Java Spring Boot
Game Event Website Backend Development - Southeast Asia
Developed a robust and efficient backend for the event websites associated with popular gaming titles.
Build high-performance backend systems for event sites of leading games
Developed a cloud gaming service that leverages kernel-based virtual machines and NVIDIA GPUs to function as game servers, with customized open-source Moonlight clients.
Utilized kernel-based virtual machines and NVIDIA GPUs as game servers.
Customized open-source Moonlight to serve as clients.
A start-up providing AI recommendation services for small to medium enterprises. The AI agent is capable of reading, seeing, hearing, and understanding user behavior to recommend relevant products and services. The inception of this project began with a research paper.
Work in a small team.
Rotate responsibilities in software engineering.
Involve in data science tasks.