In Fall 2022, I will join the Computer Science Department at Colorado University, Boulder as a Associate Professor. I will be looking for postdoctoral researchers, Ph.D. students, master students, and pre-doctoral students to work on a broad range of projects on science of science, computational research integrity, and fairness in AI. Deadline to apply to the Ph.D. is December 15, 2022. If you are interested, please send an email to deacuna@syr.edu.

Daniel Acuña is an Associate Professor in the School of Information Studies at Syracuse University, Syracuse, NY. The goal of his current research is to understand decision-making in science—from helping hiring committees to predict future academic success to removing the potential biases that scientists and funding agencies commit during peer review. To achieve these tasks, Dr. Acuna harnesses vast datasets about scientific activities and applies Machine Learning and A.I. to uncover rules that make publication, collaboration, and funding decisions more successful. Recently, he has been interested in biases in artificial intelligence and in developing methods for detecting it. Simultaneously, he has created tools to improve literature search, peer review, and detect scientific fraud. He has grants from NSF, DDHS, Sloan Foundation, and DARPA and his work has been featured in Nature News, Nature Podcast, The Chronicle of Higher Education, NPR, and the Scientist.

Before joining Syracuse University, Acuña studied a Ph.D. in Computer Science at the University of Minnesota - Twin Cities and was a postdoctoral researcher at Northwestern University and the Rehabilitation Institute of Chicago. During his graduate studies, he received a NIH Neuro-physical-computational Sciences (NPCS) Graduate Training Fellowship, NIPS Travel Award, and a CONICYT-World Bank Fellowship

Selected publications

Recently funded projects

  • PI: Daniel E. Acuna, DDHS: Office of Research Integrity: (Conference grant) Computational Research Integrity Conference (CRI-CONF 2022), 9/1/2021 - 8/31/2022
  • PI: Daniel E. Acuna: US’s Office of Research Integrity: Large-scale High-Quality Labeled Datasets and Competitions to Advance Artificial Intelligence for Computational Research Integrity, 10/01/2020 - 09/01/2022
  • co-PI: Daniel E. Acuna, PI: David Popp (Maxwell School) Sloan Foundation: Does government funding change what you do? The effects of funding on the direction and impact of academic energy research, 6/1/2020 - 5/30/2022
  • co-PI: Daniel E. Acuna, co-PI: Stephen David (Oregon) NSF-SciSIP: Collaborative Research: Social Dynamics of Knowledge Transfer Through Scientific Mentorship and Publication, 10/1/2019 - 9/30/2022
  • PI: Daniel E. Acuna, DDHS: Office of Research Integrity: (Conference grant) Computational Research Integrity Conference (CRI-CONF), 9/1/2019 - 8/31/2020
  • PI: Daniel E. Acuna, DDHS: Office of Research Integrity: Human-centered automatic tracing, detection, and evaluation of image and data tampering, 9/1/2019 - 8/31/2021
  • PI: Daniel E. Acuna, DDHS: Office of Research Integrity: Methods and tools for scalable figure reuse detection with statistical certainty, Award ORI2018000296, 8/1/2018 - 7/31/2020
  • PI: Daniel E. Acuna, co-PIs: Konrad Kording (UPenn), James Evans (U of Chicago) NSF-SciSIP: Optimizing Scientific Peer Review, Award #1800956, 7/1/2018 - 6/30/2022




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