Christian Yongwhan Lim
Selected work

Systems that work. People who grow.

The résumé records roles and results. This page is the shorter story: six bodies of work that show how I approach difficult technical problems, build learning environments, and create programs that last.

01

Systems · Current

Probook

Reliable AI voice agents

As Chief Architect, I work on the full system around real-time AI: speech, model orchestration, tools, workflow state, observability, evaluation, and recovery. The central idea is simple: reliability is an architectural property, not a model feature.

Problem
Move from plausible responses to completed customer tasks
Approach
Design and evaluate six interacting reliability boundaries
Evidence
Architecture, evaluation, and recovery field note
Read the full field note →Current focus →Probook ↗
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, continuity, and public accountability.

Problem
Connect global technical talent to durable open projects
Operating system
Selection, mentorship, contribution, continuity, and accountability
Outcome
136 completed, 14 active, and a searchable public record
Program overview →Explore the directory →
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
In development
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 ↗