Acuna, Daniel E

Research

research overview

My research aims to understand historical relationships, mechanisms, and optimization opportunities of knowledge production. Daniel harnesses vast datasets about publications and citations 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 developing methods for detecting them. In addition, he has created tools to improve literature search, peer review, and detect scientific fraud. In addition to his research, Daniel enjoys building communities around science of science and research integrity. He co-organizes the Science of Science Summer School (S4), the Computational Research Integrity (CRI-CONF) conference, and the Computational Research Integrity competitions. In addition, he is part of the ACM’s Diversity, Equity, and Inclusion (DEI) council, contributing to the social justice initiative on publications, awards, and peer review.

keywords

Science of Science, AI for Science, Computational Research Integrity, Bias in AI

Publications

selected publications

chapter
- Predicting the Usage of Scientific Datasets Based on Article, Author, Institution, and Journal Bibliometrics. Lecture Notes in Artificial Intelligence. 42-52. 2022
- Dead Science: Most Resources Linked in Biomedical Articles Disappear in Eight Years. Lecture Notes in Artificial Intelligence. 170-176. 2019
conference proceeding
- Are AI Ethics Conferences Different and More Diverse Compared to Traditional Computer Science Conferences?. 307-315. 2021
- Artificial mental phenomena: Psychophysics as a framework to detect perception biases in AI models. 403-412. 2020
- Cardiac Sarcoidosis In World Trade Center (wtc) Exposed Fire Department Of The City Of New York (fdny) Firefighters. American Journal of Respiratory and Critical Care Medicine. 2017
- Show Me Your App Usage and I Will Tell Who Your Close Friends Are 2017
- Modeling expert players' behavior through data mining. 55-61. 2005
journal article
- The impact of heterogeneous shared leadership in scientific teams. Information Processing and Management. 2024
- A computational analysis of accessibility, readability, and explainability of figures in open access publications. EPJ Data Science. 2023
- Author-suggested reviewers rate manuscripts much more favorably: A cross-sectional analysis of the neuroscience section of PLOS ONE. PLoS One. 2022
- Team formation and team impact: The balance between team freshness and repeat collaboration. Journal of Informetrics. 2022
- A dataset of mentorship in bioscience with semantic and demographic estimations. Scientific Data. 2022
- Graphical integrity issues in open access publications: Detection and patterns of proportional ink violations.. PLoS Computational Biology. e1009650. 2021
- Are AI ethics conferences different and more diverse compared to traditional computer science conferences? 2021
- Some considerations for studying gender, mentorship, and scientific impact: commentary on AlShebli, Makovi, and Rahwan (2020) 2020
- Modeling citation worthiness by using attention-based bidirectional long short-term memory networks and interpretable models. Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy. 399-428. 2020
- Assigning credit to scientific datasets using article citation networks. Journal of Informetrics. 2020
- Pyglmnet: Python implementation of elastic-net regularized generalized linear models. Journal of Open Source Software. 1959-1959. 2020
- Pubmed Parser: A Python Parser for PubMed Open-Access XML Subset and MEDLINE XML Dataset XML Dataset. Journal of Open Source Software. 1979-1979. 2020
- Scientific Image Tampering Detection Based On Noise Inconsistencies: A Method And Datasets 2020
- Limiting motor skill knowledge via incidental training protects against choking under pressure. Psychonomic Bulletin and Review. 279-290. 2019
- Intellectual synthesis in mentorship determines success in academic careers. Nature Communications. 2018
- The sociology of scientific validity: How professional networks shape judgement in peer review. Research Policy. 1825-1841. 2018
- Using psychophysics to ask if the brain samples or maximizes (vol 15, pg 1, 2015). Journal of Vision. 2016
- Adaptive neuron-to-EMG decoder training for FES neuroprostheses. Journal of Neural Engineering. 2016
- Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications. PLoS One. 2016
- Chunking as the result of an efficiency computation trade-off. Nature Communications. 2016
- High-Reproducibility and High-Accuracy Method for Automated Topic Classification. Physical Review X. 2015
- Using psychophysics to ask if the brain samples or maximizes. Journal of Vision. 2015
- Multifaceted aspects of chunking enable robust algorithms. Journal of Neurophysiology. 1849-1856. 2014
- The future h-index is an excellent way to predict scientists' future impact. Medical Physics. 2013
- Predicting scientific success. Nature. 201-202. 2012
- Toward Perceiving Robots as Humans: Three Handshake Models Face the Turing-Like Handshake Test. IEEE Transactions on Haptics. 196-207. 2012
- Structure Learning in Human Sequential Decision-Making. PLoS Computational Biology. 2010
- People Efficiently Explore the Solution Space of the Computationally Intractable Traveling Salesman Problem to Find Near-Optimal Tours. PLoS One. 2010

Teaching

courses taught

CSCI 5434 - Probability for Computer Science
Primary Instructor - Spring 2023 / Spring 2024
This course will introduce computer science students to topics in probability and statistics that will be useful in other computer science courses. Basic concepts in probability will be taught from an algorithmic and computational point of view, with examples drawn from computer science.
CSCI 5622 - Machine Learning
Primary Instructor - Fall 2023
Trains students to build computer systems that learn from experience. Includes the three main subfields: supervised learning, reinforcement learning and unsupervised learning. Emphasizes practical and theoretical understanding of the most widely used algorithms (neural networks, decision trees, support vector machines, Q-learning). Covers connections to data mining and statistical modeling. A strong foundation in probability, statistics, multivariate calculus, and linear algebra is highly recommended.
CSCI 7000 - Current Topics in Computer Science
Primary Instructor - Fall 2022 / Spring 2023 / Spring 2024
Covers research topics of current interest in computer science that do not fall into a standard subarea. May be repeated up to 8 total credit hours.

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Research Areas

Research

research overview

keywords

Publications

selected publications

chapter

conference proceeding

journal article

Teaching

courses taught

Background

education and training

International Activities

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