# PALM Group @ Korea University

**Source:** https://www.startuphub.ai/startups/palm-group-korea-university
**Profile type:** Startup

> Research group at Korea University focused on privacy-preserving machine learning and federated learning.

## About

The PALM Group at Korea University focuses on Software Engineering for AI (SE4AI) and AI for Software Engineering (AI4SE) challenges. They develop novel techniques in software testing, program mining, machine learning-based program analysis, automated program debugging, and program optimization, applying them to areas like video games, simulators, and web/mobile apps. The group serves researchers and students interested in these advanced software engineering and AI topics.

## Key facts

- **Slug:** palm-group-korea-university
- **Website:** https://darkrsw.github.io
- **Location:** Seoul, South Korea
- **Founded:** 2026-07-03
- **Operating status:** Active
- **Sectors / tags:** Federated Learning, Privacy-Preserving Machine Learning, Differential Privacy, Secure Multi-Party Computation, AI Safety, AI Governance, Research Lab
- **Social:**
  - GitHub: https://github.com/WegenenVerkeer

## Frequently asked

### What does PALM Group @ Korea University do?

The PALM Group at Korea University focuses on Software Engineering for AI (SE4AI) and AI for Software Engineering (AI4SE) challenges. They develop novel techniques in software testing, program mining, machine learning-based program analysis, automated program debugging, and program optimization, applying them to areas like video games, simulators, and web/mobile apps. The group serves researchers and students interested in these advanced software engineering and AI topics.

### Where is PALM Group @ Korea University headquartered?

PALM Group @ Korea University is headquartered in Seoul, South Korea.

### When was PALM Group @ Korea University founded?

PALM Group @ Korea University was founded in 2026.

### What industry does PALM Group @ Korea University operate in?

PALM Group @ Korea University operates in Federated Learning, Privacy-Preserving Machine Learning, Differential Privacy, Secure Multi-Party Computation, AI Safety, AI Governance.

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