Chang Liu - PhD student

CST 3-118, 111 College Pl, Syracuse, NY 13244

cliu57@syr.edu

a PhD student in the Department of Electrical Engineering and Computer Science at Syracuse University. It’s my fortune to be advised by Kristopher Micinski.

My research explores the core principles of secure and verifiable programming, focusing on compilers and reverse engineering. I am working on a common assumption in the field: that compilation is an inherently information-lossy and irreversible process, and my research develops methods to recover high-level abstractions directly from binary code.

I have developed scalable systems for curating large datasets of machine executables and benchmarked machine learning algorithms on a range of binary analysis tasks. These work have been published in NeurIPS DB Track and are being actively used by the research community.

I’m actively looking for a 2026 summer internship, feel free to reach out if you see a fit! If you’re at Google, I’m currently in the team match phase for a PhD SWE Intern role for Summer 2026.

Publications

NeurIPS

Assemblage: Automatic Binary Dataset Construction for Machine Learning

Chang Liu*, Rebecca Saul*, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, and Kristopher Micinski

In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2024

Code PDF
NeurIPS

Is Function Similarity Over-Engineered? Building a Benchmark

Rebecca Saul, Chang Liu, Noah Fleischmann, Richard J Zak, Kristopher Micinski, Edward Raff, and James Holt

In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2024

Code PDF

Services

Reviewer

2025: AAAI AICS Workshop
2026: NeurIPS Datasets & Benchmarks Track, AAAI AICS Workshop