Yang Zhao's Resume

Yang Zhao

Master's graduate in computer science, with 3 years of foundational software development experience. Strong command of C/C++/Rust, enjoys learning new technologies, and has hands-on research experience in large models and deep learning.

Qingdao

YZ
Yang Zhao's profile picture

About

Primary working languages are C/C++ and Rust, with solid Python and TypeScript.

Practical experience with multithreading, asynchronous programming, fork/poll and related network programming, cross-compilation, performance tuning, and memory-leak troubleshooting.

A systematic understanding of large language models, covering concepts such as context window, token, and embedding, and familiarity with pre-training and post-training methods.

Comfortable with containerization technologies such as Docker and Kubernetes: Docker for containerized development environments at work, and Kubernetes for containerized CI deployment.

Familiar with agile development, CI/CD, and GitHub collaboration; good at boosting productivity with new tools, with a track record of pull requests and issues on open-source projects.

Reads English documentation without difficulty, with working spoken and written English (CET-6 561).

Work Experience

Qingdao Haier Washing Machine Co., Ltd.

2025.08 - Present

Washing Machine Voice Assistant · Embedded (LLM Application) Development Engineer

Integrating LLM with a voice assistant; responsible for the embedded development and maintenance of the intelligent voice assistant.
  • Contributed to RTOS-based camera management and audio task scheduling: camera power-up/power-down management and photo capture management, plus audio focus management.
  • Contributed to voice-assistant troubleshooting: cutting wake-up latency (0.6s→0.3s) and investigating memory leaks.
  • Contributed to the design of the team's internal CI setup: managing the CI task lifecycle with Kubernetes.
  • C/C++
  • Embedded
  • Intelligent voice assistant
  • Linux/RTOS

Nanjing ZTE Software Co., Ltd.

2023.06 - 2025.08

Core Network Platform · C/C++ Development Engineer

Linux systems programming for the core-network platform, covering an intelligent operations service, an FTP-like file transfer protocol, and a stretch of CSV processing done in Java. Toolchain: GCC 4.8.5 and 12.2; version control with Git/Gerrit.
  • Intelligent O&M (C/C++, CMake, Docker, Kubernetes): collects network status across 5G services and detects anomalies, helping operations find problems in time and avoid serious network incidents.
  • FTP-like file transfer (Rust, shipped as a .so): rewrote inter-node file transfer (TIPC protocol) from C to Rust. Implemented chunked sending; for failed sends, a sliding window supports timeout retransmission and out-of-order delivery, and handling of mixed C and Rust programming.
  • CSV processing (Java): as an extension of intelligent O&M, joins the produced CSVs. Had no prior Java experience, got up to speed quickly and improved throughput with multithreading.
  • Responsible for cross-compilation and CMake builds on arm64, x86, and riscv64; strong command of CMake and the compile-and-link process.
  • C/C++
  • Rust
  • Linux
  • Microservices

Side projects

oven

A coding harness written in Rust. Supports Windows, macOS, and Linux, and provides capabilities such as MCP, skills, memory, and subagents.

  • Rust
  • Harness
  • TUI
  • MCP
  • Skill
  • Memory
  • Subagent

cargo-q

A small Cargo tool that runs several Cargo commands at once: cargo q fmt test build, to speed up development.

  • Rust
  • Cargo
  • CLI

tab archive

A VSCode extension that closes long-open tabs on a schedule to reduce mental overhead.

  • VSCode
  • Extension
  • Tab
  • TypeScript

numbers

A C++ component for handling integer addition and subtraction overflow. Implements Rust's four semantics — checked, overflowing, saturating, and wrapping — and works with GCC, Clang, and MSVC.

  • C++
  • GCC
  • Clang
  • MSVC

Education

Nanjing University of Science and Technology

2020.09 - 2023.04
M.Eng. in Software Engineering (full-time). Research focused on deep-learning video understanding. Awarded a first-class graduate scholarship and published one conference paper and one journal paper.

Hunan University of Science and Technology

2016.09 - 2020.05
B.S. in Information and Computing Science (regular admission). Served as class monitor and was named an outstanding student cadre; won second prize in the Hunan division of the Mathematical Contest in Modeling.

Blog posts

How Large Models Are Trained

WeChat
  • LLM
  • Pre-training

The training pipeline of large models: what pre-training learns, and what post-training (SFT and RLHF) sets out to solve.

How a Large Model Predicts Its Answers

WeChat
  • LLM
  • Inference

How a large model predicts the next token from the context one at a time, and how sampling strategies and temperature influence the final output.

Publications

Turning to a Teacher for Timestamp Supervised Action Segmentation

IEEE ICME · First author · Oral

Introduces a teacher model that acts as an "ensemble version" of the segmentation model during training, stabilizing pseudo labels and suppressing noise. Also designs a "segment-smoothness loss" that constrains more specifically how predicted probabilities transition smoothly within a single action segment.

Dilation-Erosion for Single-Frame Supervised Temporal Action Localization

Multimedia Tools and Applications · Fourth author

Designs a snippet-classification model and a dilation-erosion module: a dilation strategy first loosely expands candidate action segments to ease incomplete actions, then an erosion-like step removes background from those segments to reduce false detections.

Skills

  • Microservices
  • Multithreading
  • Network programming
  • Embedded
  • Asynchronous programming
  • C/C++
  • Rust
  • TypeScript
  • Python
  • SQLite
  • CMake
  • Make
  • GDB
  • Docker
  • Kubernetes
  • Git
  • Ninja/n2
  • Cargo
  • Linux