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followers: 4.0 following: 9.0 repos: 18.0 gists: 0.0

Name: Kaiming Zhu

Type: User

Company: Sun Yat-sen University, P.R. China.

Bio: Research Assistance(RA) in Sun Yat-Sen University, P.R. China.

Location: China

👋 Hi, I am KaiMing Zhu, Nice to meet you :)

You could visit my personal website, where I've provided a brief self-introduction.

👨‍🔬 Who am I?

Research Assistance(RA), in School of Intelligent Systems Engineering, Sun Yat-Sen University, supervised by Prof. Junbo Wang.
I am interested in Robust and Privacy-Preserving Federated Learning and Machine Learning. You could find more details here.

💻 Programming Preference

Python, C/C++.
I also have experience in Front-End Development, including Windows(UWP, QT), iOS(Objective-C & Swift).

📫 How to reach me

[email protected].
I can communicate with both Madarin and English.

Kaiming Zhu's Projects

appmodelsamples

Sample code for AppModel features

aspnetcore.docs

Documentation for ASP.NET Core

breaching

(fork from: JonasGeiping/breaching) Breaching privacy in federated learning scenarios for vision and text

connecttest

cs229-2018-autumn

All notes and materials for the CS229: Machine Learning course by Stanford University

easychat

SYSU分布式2019 : 分布式聊天系统的实现

h-judge

H::Judge using .NET Core + React + Semantic UI

kaimingzhu

A Brief Discription of Me.

kaimingzhu.github.io

repo of my Academic Personal Homepage, fork from acad-homepage.github.io

lovelymother

A small software for your focusing-work, take it and have a nice trip!

lumina-t2x

Lumina-T2X is a unified framework for Text to Any Modality Generation

ml_privacy_meter

Machine Learning Privacy Meter: A tool to quantify the privacy risks of machine learning models with respect to inference attacks

naivemediaplayer

This is a homework for my uwp course, with C#, XML and VisualStudio Community 2017

naivemediaplayer2

A simple Extension of NaiveMediaPlayer

pbuvp

plug-and-play-attacks

Source code for our papers "Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks" (ICML 2022) and "Be Careful What You Smooth For" (ICLR 2024).

surprise

The demo of the project.

uwphelper

an asp.net project for uwp learning, supporting by ccfinderx.

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