Preferred.AI is a research undertaking at the Singapore Management University (SMU) – School of Computing and Information Systems (SCIS) led by Hady W. Lauw.

Our mission is to 'push the envelope' on learning user preferences from data to improve the effectiveness and efficiency of recommendations using data mining, machine learning, and artificial intelligence. This encompasses designing algorithms for mining user-generated data of various modalities (e.g., ratings, text, images, social networks) for understanding the behaviours and preferences of users (individually and collectively), and applying the mined knowledge to develop user-centric intelligent applications.

Our goals are multi-fold: scientific, impact-oriented, and educational.

• We push the boundaries of science by conducting high-quality research with an eye towards publishing them in the top-tier conferences and journals.
• We seek broader impact, by developing knowledge bases, libraries, or systems and sharing them for the benefit of the community. We are also interested in pursuing fruitful collaborations of mutual interest with industry partners if an opportune synergy in research focus arises.
• We contribute towards the furtherance of training and education, through our research activities within the university environment, as well as information sharing and dissemination to the broader community.

We welcome contributions from the global AI community. Whether you’re a researcher, developer, or industry professional, there are many ways to engage with our projects:

• Explore Our Repositories: Dive into our code and documentation to understand how our tools work.
• Contribute: Submit issues, suggest features, or submit pull requests to help improve our projects.
• Collaborate: Partner with us on new initiatives or adapt our tools to your needs.

If you are a prospective candidate, explore ten reasons why you should join Preferred.AI.

Stay updated on our latest projects and announcements:

• Website: Preferred.AI
• GitHub: PreferredAI

Together with the community, we aim to advance research and build impactful AI systems for understanding and serving user preferences.