Under review

  • Wu, L., Bratt, S., Zeng, T., Acuna, DE, Assigning credit to scientific datasets using article citation networks
  • Achakulvisut, T, Bhagavatula, C, Acuna, DE, Kording, K, Claim extraction in biomedical publications using deep discourse model and transfer learning, Link
  • Zeng, T, Acuna, DE, The detection of sentences that need citations using natural language models trained on scientific articles



  • Zeng, T., Acuna, DE, (2020) Dataset mention extraction in scientific articles using a BiLSTM-CRF model Chapter 11 in Julia I. Lane, Ian Mulvany, and Paco Nathan (Ed.), Rich Search and Discovery for Research Datasets: Building the next generation of scholarly infrastructure, New York


  • Zeng, T, Acuna, DE, (2019) Dead science: most resources linked in scientific articles disappear in eight years, iConference 2019 (to appear in Lecture Notes of Computer Science)

  • Taraz G. Lee, Acuna, DE, K. P., Grafton, S. T. (2019) Limiting motor skill knowledge via incidental training protects against choking under pressure, Psychonomic Bulletin & Review Link


  • Líenard, JF, Achakulvisut, T, Acuna, DE, David, SV, Intellectual Synthesis in Mentorship Determines Success in Academic Careers, Nature Communications, Link (press release in Nature Asia)

  • Teplitskiy, M, Acuna, DE, Elamrani-Raoult, A, Körding, K, Evans, J (2018) The sociology of scientific validity: How professional networks shape judgement in peer review, Research Policy Link

  • Acuna, DE, Brooks, P, Kording, P (2018) Bioscience-scale automated detection of figure element reuse (2018) BioArXiv, Link Preprint


  • Shema, A, Acuna, DE (2017) Show Me Your App Usage and I Will Tell Who Your Close Friends Are: Predicting User’s Context from Simple Cellphone Activity, CHI 2017, Pages 2929-2935, Denver, Colorado Link


  • Achakulvisut T, Acuna DE, Ruangrong T, Kording K (2016) Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications. PLoS ONE 11(7): e0158423. doi:10.1371/journal.pone.0158423 Link
  • Ethier, C, Acuna, DE, Solla, S, Miller, L (2016)Adaptive neuron-to-EMG decoder training for FES neuroprostheses, Journal of Neural Engineering Link
  • Ramkumar P, Acuna DE, Berniker M, Grafton S, Turner RS, Körding KP (2016) Chunking as the result of an efficiency–computation tradeoff. Nature Communications Link


  • Acuna, DE, Berniker, M, Fernandes, H, Kording, K, (2015) Using psychophysics to ask if the brain samples or maximizes, Journal of Vision Link


  • Acuna, DE, Wymbs, Nicholas F., Reynolds, Chelsea A., Picard, Nathalie, Turner, Robert S., Strick, Peter L., Grafton, Scott T., Kording, Konrad P. (2014) Multi-faceted aspects of chunking enable robust algorithms, Journal of Neurophysiology, Link, code


  • Acuna, DE, Penner, Orion, Orton CG, (2013) The future h-index is an excellent way to predict scientists’ future impact, Med. Phys. 40, 110601 (Link)


  • Acuna, DE, Allesina, S., Kording, KP, (2012) Future impact: Predicting scientific success, Nature, Volume 489, Number 7415, 201-202


  • Avraham G, Nisky I, Fernandes HL, Acuna DE, Kording KP, Loeb GE, Karniel A, (2011) Towards Perceiving Robots as Humans – Three handshake models face the Turing-like Handshake Test, IEEE Transactions on Haptics
  • Acuna, DE, (2011) Rational Bayesian Analysis of Sequential Decision-Making Under Uncertainty In Humans and Machines, Ph.D. Thesis, University of Minnesota-Twin Cities


  • Acuna, DE & Schrater, P. (2010). Structure Learning in Human Sequential Decision-Making, PLoS Computational Biology 6(12): e1001003
  • Acuna, DE & Parada, V. (2010). People Efficiently Explore the Solution Space of the Computationally Intractable Traveling Salesman Problem to Find Near-Optimal Tours, PLoS ONE 5(7):e11685


  • Acuna, DE & Schrater, P. (2009). Improving Bayesian Reinforcement Learning using Transition Abstraction. ICML/UAI/CLT Workshop on Abstraction in Reinforcement Learning 2009
  • Acuna, DE & Schrater, P. (2009). Structure Learning in Human Sequential Decision-Making. NIPS 2009


  • Acuna, DE & Schrater, P. (2008). Bayesian Modeling of Human Sequential Decision-Making on the Multi-Armed Bandit Problem. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Washington, DC: Cognitive Science


  • June 12, 2019 - Invited talk, International Conference on Science of Science at the University of Chicago Beijing Center, Beijing, China - Science of bad science
  • May 10, 2019 - Invited speaker, 8th Annual Ethics in Biomedical Research Lecture, University of Rochester School of Medicine and Dentistry - To catch a scientific figure falsifier
  • March 20, 2019 - Invited talk at Symposium of Yotta Informatics, Tohoku University, Sendai, Japan - Artificial Psychophysics
  • July, 2018 - Invited Talk, iSchool - Biases in AI models
  • November, 2017 - Invited Talk, Computer Science, Syracuse University - Data Science of Data Science: Should you improve your Hadoop skills or learn time series analytics?
  • October, 2017 - Invited Talk, Rochester Institute of Technology - Data Science of Data Science: Should you improve your Hadoop skills or learn time series analytics?
  • October, 2016 - Research Computing colloquium - Improving Scientific Innovation: A Data Science Perspective
  • April, 2016 - Plenary talk - Tools to improve peer review and scholarly research, University of Wisconsin, Madison
  • March, 2016 - Lighting talk - Predicting who will agree to review, International Symposium on Science of Science, Washington, DC
  • March, 2016 - Plenary talk - Data science to understand knowledge discovery and expertise, ChiPy, International Symposium on Science of Science, Chicago, IL
  • October, 2015 - Lightning talk - Should we allow authors to suggest reviewers?, Quantifying Science, NetSci 2015 Satellite conference, Tempe, AZ
  • July, 2015 - Tools and software to accelerate science, Metaknowledge Network Summer Retreat, Asilomar, California
  • March, 2015 - Science of science, Metaknowledge Network Spring Retreat, University of Chicago
  • November, 2014 - Plenary talk - Big data science of science, Science Week 2014, Loyola University, Chicago
  • August 2014, Automatic detection of figure element reuse in biological science articles, Science of Team Science Conference, Austin, TX
  • May 2014, Big data machine learning for prediction and classification (invited academic speaker, plenary), The Tenth Workshop on the Development of Advanced Algorithms for Security Applications (ADSA10)
  • March 2013, An investigation of how prior beliefs influence decision-making under uncertainty in a 2AFC task, (plenary) COSYNE 2013

Web applications & software