Research · products · teaching

Human-centric AI and software.

I am Boxi Yu, a software engineering researcher at Lero. I study how to test and evaluate coding agents and AI systems so that people can decide when to trust them, then turn those lessons into tools people can use and courses people can learn from.

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Portrait of Boxi Yu
Boxi YuSenior Research Fellow at Lero, Ireland University of Limerick

Teaching · interactive lecture notes

Five courses, every lecture you can run

All teaching

For five courses, I build one interactive page per lecture: from AI literacy for everyone, through a first Python program, data structures and linear algebra, to building software with coding agents. Every program has been run, and every output shown is the real one.

  1. 1
    Step throughWatch each idea unfold one step at a time, from code to AI answers.
  2. 2
    PredictCommit to an answer before the page shows you what really happens.
  3. 3
    CheckEnd every lecture with a self-check and exercises.
Open course · No coding8 modules

AI 通识课: AI Literacy for Everyone

Open course in Chinese and English · Designer: Boxi Yu · English version

Eight shared modules on using AI, checking what it says, and knowing when not to use it, with tracks for K12, university, working adults, seniors, and teachers. The core module, C4, teaches how to check AI: it makes mistakes, so learn to catch them.

  1. C1What AI is and isn't
  2. C2Data, models and hallucination
  3. C3Describing and delegating
  4. C4Checking AI's answers
  5. C5Safety, privacy, scams and deepfakes
  6. C6Fairness, ethics, society and work
  7. C7Agents: delegation and oversight
  8. C8When not to use AI
Introductory · Python11 lectures

AIE1001: Introduction to AI Programming

CUHK–Shenzhen · Instructor: Prof. Pinjia He

From number systems to recursion, classes, and data structures, ending with how large language models work. Step through what Python does in memory, predict each output before it appears, and finish every lecture with a self-check.

  1. 01Computers and Number Systems
  2. 02Python Basics
  3. 03Flow Control
  4. 04Functions, Strings and Files
  5. 05Lists, Dictionaries and Tuples
  6. 06Recursion
  7. 07Objects and Classes
  8. 08Inheritance and Polymorphism
  9. 09Algorithm Analysis
  10. 10Stacks, Queues, Lists and Trees
  11. 11Large Language Models
Core · Python & Java9 chapters

Data Structures

Python and Java versions · Instructors: Boxi Yu and Yintong Huo

The structures behind every program, from arrays and linked lists to search trees, hash tables, heaps, and graphs, with complexity and proof methods as the common language. Pick Python or Java: the concepts are shared, the code is in your language.

  1. 01Complexity and Proof Methods
  2. 02Arrays and Linked Lists
  3. 03Linear Data Structures
  4. 04Recursion
  5. 05Trees and Binary Search Trees
  6. 06Sorted Maps and Balanced Search Trees
  7. 07Unsorted Maps and Hashing
  8. 08Heaps and Priority Queues
  9. 09Graphs and Graph Algorithms
Core · Math with code30 lectures

LA101: Linear Algebra

Open course in English · Designer: Boxi Yu · Inspired by MIT 18.06

From three pictures of a linear system to the singular value decomposition and computing with matrices. Every number in the notes is computed by running code, and every unit ends with a machine-learning example and a section on working with AI: what to ask, and how to check the answer.

  1. L01–05Equations and elimination
  2. L06–11The four subspaces
  3. L12–15Orthogonality and least squares
  4. L16–17Determinants
  5. L18–21Eigenvalues and dynamics
  6. L22–25Symmetric, complex and similar matrices
  7. L26–28The SVD and its uses
  8. L29–30Computing with matrices
Advanced · Coding agents11 lectures

CSC4801: AI-assisted Software Engineering

CUHK–Shenzhen · Fall 2026 · Instructor: Jinsheng Ba · Official course site

How LLMs and agents work, then how to use them across the software lifecycle: prompts, MCP and skills, requirements, coding, and team collaboration. Step through the agent loop, prompts, and tool calls, then try each step with a coding agent of your own.

  1. 00Introduction
  2. 01The Principles of Large Language Models
  3. 02Principles of Agents
  4. 03Advanced Agents
  5. 04MCP & Skills
  6. 05How to Write a Prompt
  7. 06Requirements
  8. 07Requirements Exercise
  9. 08Coding I
  10. 09Coding II
  11. 10Team Collaboration

Interactive notes and videos built with 培玉智能. I designed AI for All and LA101, teach Data Structures with Yintong Huo, and co-designed the AIE1001 and CSC4801 notes; their slides and course content belong to each instructor.

How do we establish that software and AI behave correctly?
AIOps & empirical evaluation

LightAD, OpenRCA 2.0, and CLEANet examine model efficiency, causal diagnosis, and robustness to contaminated data.

Connected research themes, with links to individual works. The grouping describes shared questions rather than a chronological sequence.

Co-founder

Products

All products

Alongside my research I co-founded OneAI and Pacific Studio, where we build AI products that keep people in the decision seat.

Co-founder · In use · AI education

ONEAI

Assessment Studio

Turn a learning objective into a question set, rubric, and student-level feedback loop. Teachers stay in the decision seat; AI handles the first pass.

In use at four schools in Guangzhou and Shenzhen, including olympiad training in mathematics, physics, chemistry, biology, and informatics at The Affiliated High School of South China Normal University and Guangzhou University Affiliated Middle School.

GenerateReviewExplain
See the workflow
Demo · student guidance, assessment generation, teacher review · 1:33

Co-founder · build, prove, understand

Pacific Studio

See the studio

Three products from Pacific Studio, which I co-founded, show how AI can support the software lifecycle: ship the work, check the proof, and read the ideas that shape it.

01Released

Build

OpenASE

Issue-driven orchestration for the full software lifecycle, with Claude Code, Codex, and Gemini CLI working across design, development, testing, and deployment.

02Released

Prove

VeriFormal

AI-assisted formal verification that turns plain code into machine-checked proof goals, with an offline workflow for C, Java, Dafny, and Rust.

03Beta

Understand

KeyLight

An interactive paper reader that combines layout-aware parsing, sentence-level highlights, bilingual reading, and answers that point back to the source.

AI education · free and open

Education equity

Visit Boxi Math

A good tutor is still a luxury. I want every child to understand why maths works, whatever their family can pay and whichever language they speak. So I make teaching, starting with maths, that is free to watch and free to reuse, with AI tools I release as open source.

0139 videos published

Learn

Boxi Math

Short K–12 maths videos in English and Chinese. Each answers one “why” and draws it so you can see it. Organised by stage rather than school year, with the matching year in China, the US, the UK, and Singapore.

0265 lessons in 9 subjects

Try

Boxi Learn

The same stage-based approach for the other K–12 subjects, from Chinese and English to physics, history, and computing. Each subject starts from a few core ideas, and every lesson is something to try with your own hands.

03Open source

Make

animind

The tools behind the videos: a format for describing a teaching scene and a vector animation engine, so any teacher can make videos like these without a studio.

Teaching · open course · Fall 2026

Agentic Software Engineering

Agents generate. You verify, decide and explain.

A practical twelve-week course for building with coding agents while keeping specifications, tests, review, security, and judgment in the loop.

I have also mentored ten students, eight of whom are now Ph.D. students. See where they went.

News & writing

  • I started Boxi Learn, which takes the stage-based approach of Boxi Math to other K–12 subjects. It has 65 hands-on lessons across nine subjects so far, from Chinese and English to physics, history, and computing, in English and Chinese. See education equity.

  • We released CXBench, a benchmark built with Genesys that scores LLM agents in regulated customer-experience workflows on both the business outcome and the required process. Across seven models, 80.1% of outcome-passing runs failed a process check. The paper is now on arXiv; see the research summary.

  • I started Boxi Math, free K–12 maths videos in English and Chinese that show why maths works, organised by stage rather than school year. The videos and text are CC BY 4.0, and the tools behind them are open source at animind-ai. See education equity.

  • BlogMore time for coaching, a tutor that is always there

    What changes when olympiad coaches and students work with AI: better preparation and problem selection for teachers, and help that is available whenever a student is stuck.