Markelle Rösti

I’m Markelle Rösti (née Kelly), a (soon-to-graduate!) computer science Ph.D. candidate in the DataLab group at the University of California, Irvine, advised by Dr. Padhraic Smyth. I’m interested in understanding and improving how machine learning models are used in practice—going beyond standard evaluation metrics. In particular, I’m excited about:

• Human-AI interaction: This line of research aims to understand and facilitate collaboration between humans and AI agents, a joint effort with researchers from cognitive science. One project investigated humans’ mental models of their AI teammates, leveraging human-subjects experiments. I’ve also developed methodology for modeling expert predictions in a human-AI setting.
• Holistic model evaluation: In my internships, I’ve created specialized processes and tools to help detect and characterize undesirable LLM behaviors. I’ve also published work on methods for more fine-grained assessment of model calibration, with an eye towards fairness, and on evaluating LLMs’ abilities to interpret linguistic uncertainty.
• Data practices in ML: Drawing from my experience as a curator for the UCI ML Repository, I’m working to push back against the under-valuing of “data work” in machine learning. This includes an upcoming ICLR workshop on improving data and benchmarking practices in ML, with an emphasis on the role of data repositories.

I’m a member of the Steckler Center for Responsible, Ethical, and Accessible Technology, the Irvine Initiative in AI, Law, and Society, and the HPI Research Center in Machine Learning and Data Science at UCI. I have previously interned with eBay and Apple, working broadly on tools and processes for evaluating LLMs, and at Project Jupyter, where I was involved in the development and design of JupyterLab. I received my Bachelor’s degree in statistics from California Polytechnic State University, San Luis Obispo in 2020 and my Master’s degree in computer science from UCI in 2022.