I'm a Computer Science student at Oregon State University. My internships have centered on AI and backend engineering: RAG pipelines and multi-agent workflows with LangChain and LangGraph, high-concurrency FastAPI services, an AI agent platform for automated telescope scheduling and surveys, and the development and testing of AI algorithms. In research, I've worked on parametric, interpretable models of human vibroacoustic sounds (paper published at IEEE EMBC 2026) and differential privacy for federated CNN training.
Education
OSU
Oregon State University
2026 – Present · Oregon, United States
B.S. in Computer Science
Oregon, United States
USM
Universiti Sains Malaysia (USM)
2023 – 2026 · Penang, Malaysia
Computer Science coursework
Penang, Malaysia
Research, engineering & AI agents
IEEE EMBC 2026
Open-source fetal heart sound simulator
Research
A Dynamic Parametric Simulator for Fetal Heart Sounds
Paper published at IEEE EMBC 2026 and presented at the conference in July. Invited speaker at GOSIM 2025in Hangzhou.
Algorithms & engineering: Assisted in the development and testing of AI algorithms and supported engineering workflows.
Data & operations: Supported data processing, analysis, and cross-functional execution across technical and business tasks.
Coordination: Participated in team meetings, project coordination, and discussions on product and engineering initiatives.
Industry events: Represented AFK AI at NVIDIA GTC 2026(March 2026).
SAOShanghai Astronomical Observatory, Chinese Academy of SciencesResearch InternAug 2025 – Oct 2025·Remote · Part-timeAug 2025 – Oct 2025Remote · Part-time
Full-stack AI agent platform: Independently built an end-to-endAI agent research platform for automated telescope scheduling and cosmological surveys.
System design: Designed the interactive observation UI, the Python backend logic for scheduling telescope observations, and the database schema for observation parameters and astronomical images.
DevOps: Managed server deployment, environment setup, SSL certificates, and domain setup.
Core RAG algorithms: Developed RAG pipelines and multi-agent workflows with LangChain and LangGraph, including a self-correctingretrieve–generate–verify mechanism, and built medical knowledge Q&A with ChromaDB and DeepSeek.
Cloud infrastructure: Deployed Alibaba Cloud RDS and built a hybrid cloud–edge architecture with local HuggingFace embedding models.
Data engineering: Implemented Pandas ETL scripts for multi-format medical documents (PDF OCR, Excel, CSV), improving backend reliability.
LCLangChain
LGLangGraph
ChChromaDB
DSDeepSeek
HFHuggingFace embeddings
RDAlibaba Cloud RDS
PaPandas
CQChongqing AI Institute, Shanghai Jiao Tong UniversityPython Backend / AI InternSep 2024 – Oct 2024·Chongqing, ChinaSep 2024 – Oct 2024Chongqing, China
RAG optimization: Enhanced the RAG system with dual-path Milvus + Elasticsearch retrieval and RRF re-ranking, improving knowledge-base Q&A accuracy by 10–25%.
High concurrency: Built high-concurrency FastAPI services for a model demo platform; async refactoring (run_in_threadpool) resolved blocking at 200–300 QPS.
API delivery: Delivered Pydantic models, SSE streaming, and automated API testing with Apifox.
Project: Open-source Simulator for Human Vibroacoustic Sounds.
Core work: Developed parametric and interpretable vibroacoustic models (envelope and temporal modeling, spectral analysis, signal generation) and reproducible data pipelines to address the scarcity of medical auscultation data.
Outcomes: Paper published at IEEE EMBC 2026 and presented at the conference in July. Invited speaker at GOSIM 2025in Hangzhou.
TMEnvelope & temporal modeling
SASpectral analysis
SGSignal generation
SF
Jul 2025·Shanghai, China
Sino-French AI Summer School, Shanghai Jiao Tong University
Research Member
Project: Privacy protection for federated convolutional neural networks with differential privacy.
Implementation: Implemented differential privacy mechanisms for federated CNN training and designed the noise injection and privacy budget control strategies.
Outcome: The final project received the Innovation Achievement Award; paper in progress.
FLFederated learning
DPDifferential privacy
CNCNN
Publications, Talks & Awards
Publication
A Dynamic Parametric Simulator for Fetal Heart Sounds
Yingtong Zhou, Yiang Zhou, Zhengxian Qu, Kang Liu, Ting Tan
IEEE EMBC 2026·Presented at the conference·Jul 2026