Fengrun Liu

I go by Fengrun or Freya.
My Chinese name, Fengrun, is pronounced approximately as /fəŋ rʊn/.

About

I am a third-year master's student at USTC. My research interests lie broadly in cryptography, especially zero-knowledge proofs (ZKP) and secure multi-party computation (MPC). I am a research intern at Shanghai Qi Zhi Institute, where I have the privilege of being advised by Prof. Yu Yu.

I am applying for a PhD program this fall :)

In 09/2023, my first lead-authored paper on MPC protocols tailored for privacy-preserving machine learning (PPML) was accepted at USENIX Security 2024.
In 11/2024, I submitted as lead author a paper on generating SNARG for FHE bootstrapping submitted to Security and Privacy 2025.
I’ve greatly enjoyed being supervised by Prof. Yuncong Hu and Dr. Xiang Xie.

I enjoy writing as it helps me deepen my understanding of the topics I'm exploring.
As of 10/2024, I have written 67 posts on my blog and attracted over 30k visitors.

In addition to my academic work, I enjoy cooking. The autonomy of the cooking process and the ownership of the final outcomes (aka delicious food) bring me a lot of joy.

Here is my curriculum vitae (CV), updated 2024/11/05. You can reach me by email.

Email: or fengrun.liu@gmail.com or fredliu@mail.ustc.edu.cn

Blog Series

Foundations of Cryptography (MIT 6.875)	[blog link]	en	Lecture 1 - Lecture 17	[course link]	by Vinod Vaikuntanathan
Zero Knowledge Proofs MOOC	[blog link]	en	Lecture 4 - Lecture 7	[course link]	by Dan Boneh, Shafi Goldwasser, Dawn Song, Justin Thaler and Yupeng Zhang
Cryptography Course (on Coursera)	[blog link]	zh-CN	Lecture 1 - Lecture 8	[course link]	by Dan Boneh
MPC Lectures	[blog link]	zh-CN	Lecture 1 - Lecture 3	[course link]	by Mike Rosulek
Machine Learning	[blog link]	zh-CN	Lecture 1 - Lecture 14	[course link]	by Hung-yi Lee

Some Past Presentations

2024-10	[slides]	zh-CN	(Ant Group’s SecretFlow Live) Topic: Scalable and Efficient MPC for ML	ref: paper
2024-08	[slides]	en	(USENIX Security '24') Topic: Scalable Multi-Party Computation Protocols for Machine Learning in the Honest-Majority Setting	ref: paper
2024-06	[slides]	en	(J.P. Morgan's AlgoCRYPT Seminar) Topic: Scalable and Efficient MPC for ML	ref: paper
2023-09	[slides]	en	Topic: Spartan's sparse PCS and Lookup Singularity with Lasso	ref: Lasso
2023-09	[slides]	en	Topic: Plookup and Batch-column Lookup (logUp)	ref: plookup, logUp
2023-08	[slides]	en	Topic: Sumcheck for FFT	ref: zkCNN
2022-05	[slides]	zh-CN	Undergraduate Graduation Defense
2021-04	[slides]	en	Topic: Fuzzing Technologies (AFL++)	ref: AFL++

University of Science and Technology of China (USTC)	M.S. in Cyberspace Security	[transcript]	Sep. 2022 – Expected Jun. 2025
University of Electronic Science and Technology of China (UESTC)	B.Eng. in Software Engineering	[transcript]	Sep. 2018 – Jun. 2022

1. MPC Protocols Tailored for Privacy-preserving Machine Learning (PPML)	2022 - Jun. 2023

2. Generate SNARKs for FHE Operations	Oct. 2023 – Present
This project is currently ongoing. Please stay tuned for further updates.

Féngrùn Liú