Trustworthy AI

Trustworthy AI requires governance and regulatory compliance throughout its AI lifecycle from initial ideation to design, development, and deployment of AI technologies. Our Trustworthy AI framework encompasses— explainability, robustness and reliability, while being respectful of privacy, safety & security, and social and environmental well-being.

FATE in AI

Along with the rapid and impressive development of AI algorithms, their untrustworthy sides have also been exposed—often producing biased and non-interpretable results. Our aim is to facilitate computational techniques that are both innovative and responsible, while prioritizing issues of Fairness, Accountability, Transparency, and Ethics (FATE) as they relate to AI, ML, and NLP to adequately address complex societal implications of AI.

Data Science for Social Good

Data Science for Social Good seeks to answer fundamental questions of human well-being via machine learning, data science, and AI projects that prioritizes social impact. Our aim is to working closely with governments and nonprofits to tackle real-world problems in health, criminal justice, political science, and more.

AI+X

Similiarly to Data Science for Social Good, AI+X consists of interdisciplinary projects across a diverse range of STEM and Non-STEM fields. Our aim is to conduct cross-disciplinary research in areas such as Education, Biology, Psychology, Linguistics, Social Science, Healthcare, and more.