CV
Hi, here is a brief summary of my Resume, you can also click pdf to see.
Contact Information
| Name | Tingyu Zhang |
| Professional Title | Master's Student in Computer Science | ML Research & Engineering |
| tingyu.z@northeastern.edu | |
| Phone | 206-741-8937 |
| Location | , Seattle, Washington |
Professional Summary
Master’s student in Computer Science at Northeastern University Seattle (4.0 GPA) with a background in Applied Mathematics. Published researcher at ICLR 2026, with hands-on experience in ML systems, LLM agents, and production engineering.
Experience
-
2025 - 2025 Shenzhen, Guangdong
Research Assistant
Southern University of Science and Technology
- Designed and trained a continual learning Multi-Armed Bandit (MAB) model with parallel optimization, formulating a preference-theoretic reward function analogous to RLHF feedback modeling; implemented training loop in PyTorch and TensorFlow with vectorized batch updates to improve convergence efficiency.
- Modeled the influence maximization problem as an online combinatorial MAB over a stochastic graph.
-
2022 - 2022 Shenzhen, Guangdong
Machine Learning Engineering Intern
HAOCHENG TECH HOLDING
- Engineered end-to-end ML training pipeline integrating Random Forest and Logistic Regression for material classification on large-scale tabular data, achieving 87.3% accuracy; applied TF-IDF vectorization and NLP preprocessing via NLTK and scikit-learn.
- Designed PostgreSQL schema with B-tree and composite indexes on high-cardinality video metadata fields, achieving a 15× latency reduction (30 min → 2 min).
Education
-
2025 - 2027 Seattle, Washington
Master of Science
Northeastern University
Computer Science
- Machine Learning Systems
- Deep Learning Networks
-
2021 - 2025 Shenzhen, Guangdong
Bachelor of Science
Southern University of Science and Technology
Applied Mathematics
- Linear Algebra
- Statistics
- Probability Theory
Skills
Languages
Interests
Certificates
- ICLR 2026 Publication - International Conference on Learning Representations (2026)
- arXiv Preprint - arXiv:2512.21925 (2025)
Projects
-
AI-Powered Job Search Agent with Ollama
Developed autonomous job search agent using Ollama with Llama 3.2 model running locally, implementing RAG architecture with ChromaDB vector store for personalized job matching.
- Engineered multi-agent system for resume tailoring, cover letter generation, and application tracking using LangChain and Python, reducing application preparation time from 2 hours to 15 minutes per job.
- Built web scraping pipeline using Selenium and BeautifulSoup to aggregate job postings, integrated with SQLite database and Celery task queue, collecting 2K+ daily job listings.
-
Astronomical Image Classifier: ViT Fine-Tuning & LLM Agent
Fine-tuned a Vision Transformer (ViT) for multi-class astronomical image classification using LoRA on a remote GPU server via SSH, achieving 90.4% accuracy while reducing trainable parameters by over 90%.
- Built a supervised few-shot learning corpus of 500+ prompt-completion pairs with interpolation curve ground-truth labels via a prompt engineering pipeline.
- Benchmarked against LeNet-5 trained on MNIST (60K images, 80.3% accuracy) as baseline.
-
Cloud-Native Microservices for Distributed System
Architected cloud-native microservices on AWS ECS with Docker containerization, Application Load Balancer for traffic routing, and auto-scaling policies.
- Integrated RabbitMQ message queues with Apache Commons Pool for connection pooling, implementing manual acknowledgements and retry logic to ensure reliable asynchronous processing.
-
SpringBoot FullStack Book Management Web Application
Architected full-stack application using React 19 with TypeScript and Tailwind CSS for the frontend, Spring Boot with PostgreSQL for the backend.
- Developed RESTful APIs with Spring MVC supporting full CRUD operations, including multipart file uploads for book covers with client-side image preview using the FileReader API.