Learn how we develop research ideas, support students, and work toward scientific independence at the Science of Science & Computational Discovery Lab at CU Boulder.
Daniel Acuna’s mentoring approach combines a structured start with increasing ownership of research. Students receive close guidance early on and continued support as they develop their own direction. The stages below describe a typical progression; the pace depends on each student’s experience and the needs of the research.
Students usually begin with a project Daniel has already thought through and selected to fit their skills and learning goals. They also contribute to ongoing lab projects. This provides early experience with the research process: reading critically, designing studies, analyzing data, and communicating findings.
We discuss which questions, methods, and experiences the student found most interesting. Together, we define a follow-up study that builds on this experience. The student takes greater responsibility for framing the question, choosing methods, and planning the work, with feedback throughout.
Students are increasingly expected to develop their own questions and lead the research. They make and justify decisions about study design, interpretation, and collaboration. Daniel’s role shifts toward discussing ideas, challenging assumptions, and helping resolve obstacles as students develop an independent research agenda.
Mentoring continues as students bring their work into a coherent dissertation and prepare for their next role. Support includes feedback on writing, research talks, and career plans, along with introductions and recommendations relevant to the student’s goals.
Across these stages, Daniel helps students build professional relationships, encourages conference presentations, and provides opportunities to practice talks and respond to questions. Students learn to explain their work to specialists and broader audiences, and to build recognition for their contributions across disciplines, professions, and backgrounds.
These commitments draw on the National Academies’ synthesis of mentoring research, Cornell’s guidance for graduate mentors, and CU Boulder’s mentoring and development resources.
Our recent work uses an AI-first approach to developing ideas and prototypes. We start by identifying a scientific direction and the question we want to answer, then spend substantial time challenging the idea before committing to a full study.
Students remain responsible for understanding and explaining the work. We check sources, inspect and test generated code, and evaluate claims against data. AI critiques help us identify questions to investigate; agreement among AI outputs does not establish that an idea is correct. We document consequential changes so that rapid iteration remains traceable.
Our research covers the science of science, research integrity, peer review, and computational discovery. Prospective Ph.D. students apply through the Department of Computer Science.
Please do not email the principal investigator about individual Ph.D. applications. We are unable to respond to these inquiries individually.
For questions about the application process, contact Computer Science graduate admissions. Information about financial support is available on the department’s funding opportunities page.
The lab is not currently recruiting master’s students.
The lab is not currently recruiting undergraduate students.
Prospective visiting scholars with independent funding and availability for at least six months may contact Daniel Acuna. Previous visiting scholars have received support from the China Scholarship Council.
