- This series of projects was originally established as the assignments and capstone projects for elite class students, the research projects for master students or honours students, in some top Australiasia universities, including Deakin University, Manipal Institute of Technology, Indian Institute of Technology Kharagpur, Southeast University, University of Chinese Academy of Sciences, Nanjing University of Science and Technology, Vellor Institute of Technology, SRM Institute of Science & Technology etc. (since 2012).
- Without explicit agreement, you are not allowed to distribute this package.
- If you found any issue/bug for this site, please submit an issue at tulip-lab/open-projects:
- Pull requests are welcome:
- Point of Contact 👉 : Prof. Gang Li
Prepared by 🌷 TULIP Lab
The purpose of this series of open projects is to help solve a real-world AI project using (but not limited to) modern AI methods. Each project is designed to:
- help you get experience in following cutting edge research and writing academic report;
- help you gain hands-on experience in solving real projects.
The following projects are recommended as:
- assignments of coursework units/subjects for elite class students
- capstone projects (SIT374 and SIT378) for Bachelor and Master by coursework students
You are free to choose any project from the recommended lists. Most of those can be considered as assignments, typically, for which you are required to:
- implement the project as required, maintain your own GitHub repository.
- complete a report on your method (with adequate justification), your discovery, empirical evaluation and analysis.
- deliver and publish (via services such as YouTube) a demonstration on your project.
More detailed requirements for assignments, please follow their corresponding units/subjects' requirements.
| 🔬 ID |
📒 Project Name |
🎯 Technical Challenges |
👨🏫 Research Challenges |
|---|---|---|---|
| 1️⃣ | 📖 Tourism Demand Forecasting Web Service | ⭐⭐⭐⭐ | ⭐⭐ |
| 2️⃣ | 📖 Photo-based Attendance System | ⭐⭐⭐⭐ | ⭐⭐⭐ |
| 3️⃣ | 📖 Fur-seal Face Recognition | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| 4️⃣ | 📖 Abnormal DNS Traffic Detection | ⭐ | ⭐⭐⭐⭐ |
| 5️⃣ | 📖 ZTA Architecture | ⭐⭐⭐ | ⭐⭐⭐⭐ |
NEXUS projects are established for the NEXUS research training program, supervised by TULIP-Lab members. The following projects are recommended as:
- Stage 1️⃣ - research projects compatible with Deakin's SIT723 unit
- Stage 2️⃣ - research projects compatible with Deakin's SIT724 unit
- Stage 3️⃣ - research projects compatible with Honours projects
Every project has its own specific requirements, which can be accessed from the corresponding project pages.
| 🔬 ID |
📒 Project Name |
🎯 Technical Challenges |
👨🏫 Research Challenges |
|---|---|---|---|
| 1️⃣ | 📖 Tourism Demand Forecasting | ⭐⭐ | ⭐⭐ |
| 2️⃣ | 📖 Tabular Data Generation | ⭐⭐ | ⭐⭐⭐⭐ |
| 3️⃣ | 📖 Privacy Attack in Reinforcement Learning | ⭐⭐⭐ | ⭐⭐⭐ |
| 4️⃣ | 📖 Security of Deep Learning Models | ⭐⭐⭐ | ⭐⭐ |
| 5️⃣ | 📖 Data Distillation | ⭐⭐⭐ | ⭐⭐⭐⭐ |
| 6️⃣ | 📖 Optimal Transportation | ⭐⭐ | ⭐⭐⭐ |
| 7️⃣ | 📖 Topological Data Analysis | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| 8️⃣ | 📖 Time Series Anomaly Detection | ⭐⭐⭐ | ⭐⭐⭐⭐ |
| 9️⃣ | 📖 Trajectory Planning of UAVs | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| 🔟 | 📖 Quantum Machine Learning | ⭐⭐⭐ | ⭐⭐⭐⭐ |
