Research

Publications

Under review

  • Achakulvisut, T, Acuna, DE, Bassett. DS, Kording, KP, Unique subfields of neuroscience exhibit more diverse language Link
  • Líenard, JF, Achakulvisut, T, Acuna, DE, David, SV, Intellectual Synthesis in Mentorship Determines Success in Academic Careers Link
  • Harandi, M, Acuna, DE, Differences in productivity patterns for junior and senior NSF grantees
  • Shema, A, Acuna, DE, Unprivate privacy: revealing people’s behavioral patterns through simple mobile app usage
  • Teplitskiy, M, Acuna, DE, Elamrani-Raoult, A, Körding, K, Evans, J The Social Structure of Consensus in Scientific Review Link

Published

Preprints

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

2018

  • Taraz G. Lee, Acuna, DE, K. P., Grafton, S. T. (2018) Limiting motor skill knowledge via incidental training protects against choking under pressure, Psychonomic Bulletin & Review Link

2017

  • 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

2016

  • 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

2015

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

2014

  • 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

2013

  • 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)

2012

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

2011

  • 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

2010

  • 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

2009

  • 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

2008

  • 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

Talks

  • 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

Media