Profile picture of David Haolong Lee

David Haolong Lee 李昊龙

Software Engineer @

I'm currently working as a software engineer at . I obtained my bachelor's (with honors) and master's degree in computer science from USC. During my studies, I was a member of the ICAROS lab at USC and the USC CS Theory Group. I am fortunate to have the opportunity to work closely with and learn from Stefanos Nikolaidis and David Kempe. I'm also grateful for my collaborators and close friends Aditya Prasad, Ramiro Deo-Campo Vuong, Jenny Kim, Bryon Tjanaka, and Matthew Fontaine.

My research interests are continuous optimization, interpretability in machine learning, robust and adaptive agents, and quality diversity optimization. I am excited about deriving practically useful algorithms from theoretical computer science.

Aug 18th
Started working as a software engineer at Apple in the simulation team
May 16th
Graduated from University of Southern California with my master's in computer science
Feb 28th
My co-author Aditya presented dpvis at SIGCSE 2025 in Pittsburg, Pennsylvania
2024
Oct 31st
Presented dpvis at USC Theory Lunch
Jul 16th
Presented Density Descent Search for Diversity Optimization at GECCO 2024 in Melbourne, Australia
2023
Dec 6th
Released dpvis, a simple Python library for interactive visualizations of dynamic programming algorithms

Software

Publications

dpvis: A Visual and Interactive Learning Tool for Dynamic Programming
David H. Lee, Aditya Prasad, Ramiro Deo-Campo Vuong, Tianyu Wang, Eric Han, David Kempe
Technical Symposium on Computer Science Education (SIGCSE TS), Feb. 2025
arXiv Slides
Density Descent Search for Diversity Optimization
David H. Lee, Anishalakshmi V. Palaparthi, Matthew C. Fontaine, Bryon Tjanaka, Stefanos Nikolaidis
Genetic and Evolutionary Computation Conference (GECCO), Jul. 2024
arXiv Slides
Training Diverse High-Dimensional Controllers by Scaling Covariance Matrix Adaptation MAP-Annealing
Bryon Tjanaka, Matthew C. Fontaine, David H. Lee, Aniruddha Kalkar, Stefanos Nikolaidis
IEEE Robotics and Automation Letters (RA-L), vol. 8, no. 10, pp. 6771-6778, Oct. 2023
arXiv GitHub Website
pyribs: A Bare-Bones Python Library for Quality Diversity Optimization
Bryon Tjanaka, Matthew C. Fontaine, David H. Lee, Yulun Zhang, Nivedit Reddy Balam, Nathaniel Dennler, Sujay S. Garlanka, Nikitas Dimitri Klapsis, Stefanos Nikolaidis
Genetic and Evolutionary Computation Conference (GECCO), Jul. 2023
arXiv GitHub Website

Manuscripts

Quality Diversity Optimization: A Modular Framework and Continuous Density Estimation
David H. Lee
PDF Slides
May 2024
Upgrading CMA-ME to CMA-MAE on the Sphere Benchmark
David H. Lee, Bryon Tjanaka, Nivedit Reddy Balam, Matthew C. Fontaine, Stefanos Nikolaidis
Website
Mar. 2023
An Overview of Low-Rank Matrix Completion using Convex Optimization Techniques
Ramiro Deo-Campo Vuong, David H. Lee, Aditya Prasad, Yibo Wen
PDF GitHub
May 2022

Teachings

Introduction to Algorithms and the Theory of Computing

CSCI 270 @ USC, Teaching Assistant

Spring 2024
Discrete Methods in Computer Science

CSCI 170 @ USC, Teaching Assistant

Spring 2023, Summer 2023, Fall 2024

Other

In my free time, I play volleyball (indoor and beach). I also enjoy cooking (mostly Chinese cuisine).