Christian Yongwhan Lim
Selected work

Systems that work. People who grow.

The résumé records roles and results. This page connects current technical proof with the longer arc: systems, research, learning environments, and programs designed to hold up under pressure.

01

Systems · Current

Probook

Chief Architect at Probook

Probook publicly describes itself as the AI operating system for home services, built around dispatch. I serve as Chief Architect. Product capabilities and customer outcomes belong to Probook’s public record; no unpublished company result appears here.

Company
AI operating system for home services
Public focus
One connected system for the front-office customer experience
Source boundary
Company facts and outcomes are published by Probook
Visit Probook →Read a general note on voice-agent reliability →
New · September 2026

Current technical proof

Five public views of reusable methods, research, engineering practice, and institutional work. Unpublished employer and customer results are excluded.

Decisions

Operations research

Explicit tradeoffs across quality, cost, risk, delivery time, and future flexibility.

Use the decision framework → Stewardship

Responsible closeout

Cost visibility, deliberate retirement, clear ownership, and retained knowledge.

Use the closeout checklist → Research

Cascade centrality

Exact hardness, structural results, network augmentation, and checked computation.

View overview → Engineering

Contest reliability

Validators, adversarial solutions, generated data, CI, and independent sign-off.

Use the release field guide → Institutions

Learning infrastructure

Internship systems, public learning products, governance, measurement, and succession.

Read the case study →
02

People · 2016–Now

Columbia University

A competitive-programming community

Courses are only one part of a learning system. At Columbia, the work spans curriculum, practice, coaching, feedback, and community—creating an environment where students can steadily turn unfamiliar problems into tractable ones.

Problem
Turn episodic contest preparation into a durable learning environment
Approach
Courses, weekly practice, coaching, feedback, and leadership succession
Outcome
429+ members, 14 offerings, and a 2024 NAC silver medal
Courses and evaluations →Team record →Mentorship record →
03

Institutions · Global

ICPC Foundation

A distributed technical-talent pipeline

The internship program connects students, mentors, universities, and technical projects across borders. The work is not merely placement; it is the operating system around selection, contribution, mentorship, measurable outcomes, continuity, and public accountability.

Problem
Connect global technical talent to durable open projects
Operating system
Selection, mentorship, contribution, measurement, and succession
Outcome
136 completed, 14 active, and a searchable public record
9.6 / 10 average intern experience across 86 responses160+ weekly problem sets released4 streams web, journal, archive, and training/mobile work
Program overview →Explore the directory →ICPC University ↗
04

Learning at scale

Google

Google Kick Start

During six years at Google, I worked in applied AI research and large-scale machine-learning infrastructure, and served as tech lead for Kick Start as it grew from a regional contest into a global competition. It was an early lesson in turning expert practice into an accessible, repeatable experience.

Role
Tech lead
Reach
110K+ participants worldwide
Thread
Technical education at global scale
Career record →Problem-solving profile →
05

Craft · In progress

With Josh Alman

Competitive Programming: Beyond the Basics

A practical book about the space between knowing standard algorithms and solving unfamiliar problems fluently: modeling, pattern recognition, experimentation, proof, implementation, and the review habits that make practice compound.

Audience
Problem solvers beyond the introductory level
Subject
The craft behind consistent progress
Status
20 chapters · test-lecture edition in classroom use
Book project →Essay on deliberate practice →
06

Research · Foundations

Stanford · MIT · Google

Research across vision, networks, and programming systems

The domains changed, but the questions stayed recognizable: how to make complex computational systems more capable, observable, and useful. The publication record spans computer vision, networks, and programming languages.

Impact
637+ research citations
Venues
CVPR, IJCV, OOPSLA, and others
Training
Stanford and MIT
Selected publications →Google Scholar ↗