Curriculum Vitae
Research Interests
- Computational Cognitive Neuroscience. Biologically plausible neural network models of cognitive systems
- Visual Working Memory. Visual short-term memory, and its interaction with other visual systems
- Perceptual Learning. Neurophysiological mechanisms of visual perceptual learning
- Object Recognition. Visual object recognition in human observers and computer models
- Data Science & Predictive Analytics. Statistical modeling approaches to large and complex sources of data
Education
- Ph.D., Cognitive Psychology, The Ohio State University, 2014
- M.A., Cognitive Psychology, The Ohio State University, 2011
- B.A., Japanese Language, The Ohio State University, 2007
Grant Support
Grants Awarded
MassMine Advancement Grant for Sustainable Humanities Data-Driven Research. Role: PI. National Endowment for the Humanities (NEH). September 2019. $324,865 direct costs.
MassMine: Collecting and Archiving Big Data for Social Media Humanities Researchers. Role: Co-Investigator. National Endowment for the Humanities (NEH). May 2015. $60,000 direct costs.
MassMine Development and Training Project. Role: Lead software developer. University of Florida Informatics Institute. May 2015. $49,837 direct costs.
Grants Submitted
Epidemiological investigation of underage drinking on social media, Co-investigator on
proposed National Institutes of Health (NIH) grant, $405,950 requested.
Scholarly Work
Peer-Reviewed Publications
Beveridge, A. Van Horn, N. M., (2022). Mining Hope: Preserving and Exploring Twitter Data for Digital Visual Studies. In L. E. Gries & B. Hallinan (Eds.), Doing Digital Visual Studies: One Image, Multiple Methodologies. Computers and Composition Digital Press/Utah State University Press.
Beveridge, A. Van Horn, N. M., (2022). Big data, tiny computers: Making data-driven methods accessible with a raspberry pi. In M. Faris & S. Holmes (Eds.), Reprogrammable Rhetoric: Critical Making Theories and Methods in Rhetoric and Composition. Logan, UT: Utah State University Press.
Van Horn, N. M., & Beveridge, A. (2016). MassMine: Your Access to Data. The Journal of Open Source Software, 1(8).
Van Horn, N. M., Beveridge, A., & Morey, S. (2016). Attention Ecology: Trend Circulation and the Virality Threshold. Digital Humanities Quarterly, 10(4)
Petrov, A., & Van Horn, N. M. (2012). Motion aftereffect duration is not changed by perceptual learning: Evidence against the representation modification hypothesis. Vision Research, 61, 4-14.
Petrov, A. A., Van Horn, N. M., & Ratcliff, R. (2011). Dissociable perceptual learning mechanisms revealed by diffusion-model analysis of the patterns of specificity. Psychonomic Bulletin & Review, 18(3), 490–497.
Petrov, A. A., Van Horn, N. M., & Todd, J. (2011). The visual identification of relational categories. Journal of Vision, 11(12), 1–11.
Abstracts, Talks, and Posters
Coleman, Nicole and Van Horn, N. M. (2021). Musical Effects on Individual Time Perception. In Proceedings from the national conference on undergraduate scholarship.
Coleman, Nicole and Van Horn, N. M. (2021). Effects of Presentation Styles and Personality Traits on Cyberbullying. In Proceedings from the national conference on undergraduate scholarship.
Szabo, Valerie and Van Horn, N. M. (2018). Fake news: Identifying misinformation in widespread media. In Proceedings from the national conference on undergraduate scholarship.
Van Horn, N. M. & Petrov, A. A. (2015). An equivalent noise method for measuring delay-induced degradation in VSTM. Journal of Vision, 15(12), 660.
Van Horn, N. M. & Beveridge, A. (2015). Writing eScience: Using Data Science Tools to Study Networked Writing Ecologies. College, Conference on Composition and Communication.
Van Horn, N. M., & Petrov, A. A. (2014). Practice abolishes similarity’s influence on VSTM-induced interference on perception. In Proceedings of the 2014 annual meeting of the vision sciences society.
Petrov, A. A., & Van Horn, N. M. (2014). Training on orientation recall improves the precision of visual short-term memory under high and low levels of memory masking. In Proceedings of the 2014 annual meeting of the vision sciences society.
Beveridge, A., & Van Horn, N. M. (2014). Humanities Software Development: Data Mining and Writing Studies. The humanities and technology camp (THATCamp) conference.
Van Horn, N. M., & Petrov, A. A. (2013). Cross-talk between visual short-term memory and low-level vision: Evidence for interactions across shared neural resources. In Proceedings of the 2013 annual meeting of the vision sciences society.
Van Horn, N. M., Petrov, A. A., & Todd, J. T. (2011). Can configural relations be encoded by image histograms of higher-order filters? [abstract and a talk at the session on models of perceptual learning]. In Proceedings of the 2011 annual meeting of the vision sciences society.
Petrov, A. A., Van Horn, N. M., & Ratcliff, R. (2011). Dissociable perceptual learning mechanisms revealed by diffusion-model analysis. In Proceedings of the 2011 annual meeting of the vision sciences society.
Petrov, A. A., Van Horn, N. M., & Ratcliff, R. (2010). Dissociable perceptual learning mechanisms revealed by diffusion-model analysis. In Abstracts of the psychonomic society (Vol. 15, p. 218).
Petrov, A. A., & Van Horn, N. M. (2009a). Motion aftereffect duration is not changed by perceptual learning: Evidence against the representation-modification hypothesis. In Abstracts of the psychonomic society (Vol. 14, p. 5094).
Petrov, A. A., & Van Horn, N. M. (2009b). Perceptual learning of visual motion: The role of the spatial frequency of the carrier. Journal of Vision, 9(8), 886a.
Awards
Research
Summer Research Excellence Fellowship (2014), The Ohio State University. Research fellowship awarded to top 5 graduate students in Psychology.
Presidential Fellowship (2013), The Ohio State University. Merit-based scholarship rewarding outstanding scholarly accomplishments (~17 recipients across all departments at OSU).
Graduate Student Research Excellence Award (2012), The Ohio State University. Summer research fellowship awarded to top 15 graduate students for outstanding research ability
OSU Graduate Student Conference Presentation Award (2011). Travel award to present research at the 11th annual meeting of the Vision Sciences Society
Graduate Student Research Excellence Award (2011), The Ohio State University. Summer research fellowship awarded to top 15 graduate students for outstanding research ability
OSU Graduate Student Conference Presentation Award (2010). Travel award to present research at the 50th annual meeting of the Psychonomic Society
OSU Graduate Student Conference Presentation Award (2009). Travel award to present research at the 9th annual meeting of the Vision Sciences Society
University Fellowship (2008-2009), The Ohio State University, Department of Psychology. Merit-based departmental scholarship
Teaching
Meritorious Teaching Award, The Ohio State University, Department of Psychology. Award winner for the 2011-2012 academic year.
Nominated for the College of Arts and Sciences Outstanding Graduate Teaching Associate Award, The Ohio State University. Nominated for the 2010-2011 academic year.
Teaching Experience
- Computational Psychology and Neuroscience (2018-present), Capital University
- Experimental Psychology (2017-present), Capital University
- Cognitive Psychology (2016-present), Capital University
- Advanced Social Media and Big Data Research (2016), Capital University
- Social Media and Self-Surveillance (2016), Capital University
- Social Sciences Statistics (2015), Capital University
- Biological Psychology (2015-present), Capital University
- Research Methods (2014-present), Capital University
- Introduction to Psychology (2016-present), Capital University
- Principles of Psychology (2014), Capital University
- Introduction to Psychology (2011-2014), The Ohio State University. (3 sections total)
- Memory & Cognition (2012), The Ohio State University. (guest lecturer for 3 weeks)
- Introduction to Psychology (2009-2011), The Ohio State University. (9 sections total under quarter system)
Computer and Technical Experience
Languages
R: Extensive experience (15+ years) in statistical analysis, mathematical and computational modeling, social media analysis, and neural networks
Matlab/Octave: Many carefully controlled experimental protocols (using the Psychophysics Toolbox) including a strictly controlled fMRI experiment, as well as mathematical modeling and machine learning algorithms on linux clusters (at the Ohio Supercomputer Center)
Python: Work on computational models of memory and stochastic Bayesian diffusion modeling of human reaction time data
Lisp: Many open source contributions in various lisp dialects, including primarily Racket, Emacs lisp, Scheme, and Clojure
Various: Advanced familiarity with many tools commonly used in managing Linux systems and web applications
Research Technology
- EyeLink 1000 eye tracking
Operating Systems and Administrative Experience
- 18+ years of active maintenance of Linux, MacOS, and Windows environments.
Publishing and Productivity
- Advanced knowledge of Emacs and Emacs Lisp, including reproducible research techniques via org-babel, LaTeX, and markdown (including CommonMark and RMarkdown). This site is generated from markup using the Racket programming language.
Professional Activities
Scientific Memberships
- Vision Sciences Society
- Psychonomic Society
Conferences and Workshops
- Vision Sciences Society Proceedings
- Mathematical Biosciences Institute, Cognitive Neuroscience Workshop: 2012
- Psychonomic Society Proceedings