I am a Research Fellow at Harvard University working on developing trustworthy machine learning that go beyond training models for specific downstream tasks and ensure they satisfy other desirable properties, such as explainability, fairness, and robustness. What inspires me to do what I do is the feeling of helping the community through my work! I am one of the co-founders of the Trustworthy ML Initiative, a forum and seminar series related to Trustworthy ML, and an active member of the MLC research group that focuses on democratizing research by supporting open collaboration in machine learning (ML) research. I am always looking for new and exciting discussions as they are stepping stones for scientific research. Feel free to reach out to me here if you are excited about core eXplainable Artificial Intelligence (XAI) or its applications.
For more details about my research, please check out my CV.