Human-Centered AI for Foundational Societal Systems
I am a researcher associate in the Computer Science Department at Carnegie Mellon University. I develop methods to control and align language models through interpretable natural-language specifications as a data-efficient, auditable alternative to opaque, gradient-based preference optimization. Operationally, my research is organized around two interconnected themes:
- AI for supporting professionals - This line of work focuses on augmenting the capabilities of professionals (e.g., in legal or education) and making systems function more effectively. This includes performing complex semantic analysis of legal documents at a level comparable to trained human experts, or developing methods for empirical legal analysis. I have been exploring the use of AI by educators to create content.
- AI for fairness and access - This thrust is dedicated to empowering individuals. In the legal sphere, this means building tools that help ordinary people navigate complex legal issues. In education, I have been leveriging generative AI to enable adaptive and more accessible learning environments.
About Me
- Researcher Associate (Faculty), Technology for Effective and Efficient Learning (TEEL) Lab, Computer Science Department at Carnegie Mellon University, 2022.9 - Present
- Post-doctoral Researcher, Computer Science Department at Carnegie Mellon University, 2020.9 - 2022.8
- Ph.D., Intelligent Systems Program at University of Pittsburgh, 2013 - 2020
Teaching
- 11-667 Large Language Models Methods and Applications is a graduate-level course that aims to provide a holistic view of the current state of LLMs. The course is designed to give graduate-level students an overview of the techniques behind LLMs and a thorough grounding on the fundamentals and cutting-edge developments of LLMs, to prepare them for further research or applied endeavors in this domain.
Recent Projects
- Carnegie Mellon Accenture Center of Excellence for AI (ACE-AI) - A collaboration between Accenture and Carnegie Mellon University focused on addressing critical challenges in workforce development. The center is built on three pillars: AI for coaching and tutoring, AI for training content development, and AI for learning analytics. My role is a co-PI.
- AI Technicians - A collaboration between the U.S. Army’s Artificial Intelligence Integration Center (AI2C) and Carnegie Mellon University to design, implement and evaluate novel rapid occupational training methods to create a competitive AI workforce at the technicians level. My role is a co-PI.
- AI Institute for Societal Decision Making (AI-SDM) - The institute brings together AI and social sciences researchers to develop human-centric AI for societal good that harnesses the power of data and an improved understanding of human decisions to create better and more trusted choices. The TEEL lab’s role in AI-SDM is to develop and deliver an AI Literacy curriculum targeted towards non-STEM learners with a high school education.