Overview

Publications

Public Presentations

Panel: Staff+ IC Data Careers. (2022) Locally Optimistic Meetup. With Paige Berry and Terry Joyce.

A/B Testing and Decision-Making. (2022) Quant UX Conf 2022.

The Software Architecture of WayUp’s Job Recommender System. (2018) DataEngConf NYC 2018.

Cold-Start Recommendations to Users With Rich Profiles. (2018) RecSys NYC Meetup.

Collecting and Making Sense of Diverse Data at WayUp. (2017) DataEngConf 2017, New York City.

APIs and DSLs for Building and Integrating Many Models. (2017) PAPIs 2017, Boston.

Forecasting Repeated Accumulating Processes with Semiparametric Regression Models and Bayesian Updates. (2017-2018) NY Open Statistical Programming Meetup; International Society for Business and Industrial Statistics Conference 2017, Westchester, NY; Conference on Statistical Practice 2018, Portland, OR.

Big Data, Public Policy, Higher Ed, & Industry: Statistics, Challenges, & Opportunities. (2016) WSS Big Data in the Public Sector Mini-Conference.

Shiny Apps for Repeated Modeling Workflows. (2016) Shiny Developers Conference.

Predicting Student Success at Scale — APIs and DSLs for Building and Integrating Many Models. (2015) EARL Conference.

dplyr and Databases. (2015) Data Wranglers DC Meetup.

Software Architecture & Predictive Models in R. (2015) NYC R Conference.

Julia: applying language design lessons to technical computing. (2014) Polyglot Programming DC Meetup.

How to Put Your Meetup on the Map (Literally). (2013-2014) INFORMS MD, Statistical Programming DC, New York Open Statistical Programming. Predictive Analytics World – Government (invited). With Alan Briggs.

Why a Data Community is like a Music Scene. (2013) Strata NYC Ignite talk.

Panel: Creating and Sustaining a Data Community. (2013) DataGotham. With Matt Turck and Noah Hidalgo.

Growing Pains: Talking About Data Scientists. (2012) DataGotham.

Annotating Enterprise Data from an R Server. (2012) DC UseR Group.

What is “Data Science” Anyway? (2011) Data Science DC Meetup.

An Introduction to Multilevel Regression Modeling for Prediction. (2010) NYC Predictive Analytics Meetup. With Jared Lander

How to Speak ggplot2 Like a Native. (2010) DC UseR Group.

Demystifying error messages and debugging in R — Advanced topics. (2010) New York R Statistical Programming Meetup.

The R Rosetta Stone — Matlab. (2010) New York R Statistical Programming Meetup. With Marck Vaisman.

Introduction to the Grammar of Graphics with ggplot2 in R. (2009) New York R Statistical Programming Meetup.

Non-technical Articles

Harris, H. D., Murphy, S. P., & Vaisman, M. (2013). Analyzing the Analyzers: An Introspective Survey of Data Scientists and Their Work. O’Reilly Media.

Papers in Refereed Journals

Magnuson, J. S., Mirman, D., Luthra, S., Strauss, T., & Harris., H. D. (2018). Interaction in spoken word recognition models: Feedback helps. Frontiers in Psychology.

Harris, H. D., Murphy, G. L., & Rehder, B. (2008). Prior knowledge and exemplar frequency. Memory & Cognition, 36, 1335-1350.

Hoffman, A. B., Harris, H. D., & Murphy, G. L. (2008). Prior knowledge enhances the category dimensionality effect. Memory & Cognition, 36, 256-270.

Strauss, T., Harris, H. D., & Magnuson, J. S. (2007). jTRACE : A reimplementation and extension of the TRACE model of speech perception and spoken word recognition. Behavior Research Methods, 39, 13-30.

Dell, G. S., Lawler, E., Harris, H. D., & Gordon, J. K. (2003). Models of errors of omission in aphasic naming. Cognitive Neuropsychology, 21, 125-145.

Dell, G. S., Harris, H. D., & Guest, D. J. (2001). Erreurs de production, contraintes phonotactiques, et expérience récente (Speech errors, phonotactic constraints, and recent experience). Psychologie Français, 46, 55-64.

Papers Under Submission

Harris, E. S., Harris, H. D., & Malkovsky, M. (submitted). Blood Type Distribution in Autoimmune Diseases: An Anonymous, Large-Scale, Self-Report Pilot Study.

Book Chapters

Magnuson, J. S., Mirman, D., & Harris, H. D. (2012). Computational models of spoken word recognition. M. Spivey, K. McRae & M. Joanisse (Eds.), Cambridge Handbook of Psycholinguistics, 76-103.

Harris, H. D. & Rehder, B. (2011). Knowledge and resonance in models of category learning and categorization. E. Pothos & A. Wills (Eds.), Formal Approaches to Categorization, 274-298.

Papers in Refereed Conference Proceedings

Harris, H. D. (2018). An Architecture and Domain Specific Language Framework for Repeated Domain-Specific Predictive Modeling. In The Proceedings of Machine Learning Research, 4th International Conference on Predictive Applications and APIs.

Harris, H. D. (2008). Categorizing Fragments of Exemplars: Experimental and Computational Results. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), The Proceedings of the 30th Annual Meeting of the Cognitive Science Society (pp. 409-414). Austin, TX: Cognitive Science Society.

Harris, H. D. & Minda, J. P. (2006). An attention-based model of learning a function and a category in parallel. In The Proceedings of the 28th Annual Meeting of the Cognitive Science Society.

Harris, H. D. & Rehder, B. (2006). Modeling category learning with exemplars and prior knowledge. In The Proceedings of the 28th Annual Meeting of the Cognitive Science Society.

Magnuson, J. S., Strauss, T., & Harris, H. D. (2005). Interaction in spoken word recognition models: Feedback helps. In The Proceedings of the 27th Annual Meeting of the Cognitive Science Society.

Strauss, T., Magnuson, J. S., Pelosof, R., & Harris, H. D. (2005). jTRACE: A reimplementation and extension of TRACE for research and education. In The Proceedings of the 27th Annual Meeting of the Cognitive Science Society.

Harris, H. D., & Minda, J. P. (2005). Function learning with an ensemble of linear experts and off-the-shelf category-learning models. In The Proceedings of the 27th Annual Meeting of the Cognitive Science Society.

Reichler, J. A., Harris, H. D, & Savchenko, M. A. (2004). Online parallel boosting. In The Proceedings of AAAI-2004.

Harris, H. D., & Kiefer, S. M (2004). A survey of instructors of Introductory Artificial Intelligence. In The Proceedings of FLAIRS-2004.

Harris, H. D. (2002). Holographic reduced representations for oscillator recall: A model of phonological production. In The Proceedings of the 24th Annual Meeting of the Cognitive Science Society.

Harris, H. D. (2002). Evidence that Incremental Delta-Bar-Delta is an attribute-efficient linear learner. In Machine Learning: ECML 2002, 135-147, Springer.

Harris, H. D. & Reichler, J. A. (2001). Learning in the cerebellum with sparse conjunctions and linear separator algorithms. In The Proceedings of the International Joint Conference on Neural Networks 2001.

Workshop Papers, Technical Reports, and Posters

Harris, H. D., Hoffman, A. B., & Murphy, G. L. (2007). Prior Knowledge and Non-minimal Category Learning: Experimental and Modeling Results. Poster presented at The 48th Annual Meeting of the Psychonomic Society.

Magnuson, J. S., Strauss, T., & Harris, H. D. (2005) On the role of interaction in models of spoken word recognition: Feedback helps. Poster presented at The 18th Annual CUNY Sentence Processing Conference.

Harris, H. D., & Magnuson, J. S. (2004) Proper names, common nouns, and category learning. Poster presented at The 45th Annual Meeting of the Psychonomic Society.

Harris, H. D., & Magnuson, J. S. (2004) A cross-disiplinary look at statistics and grounding in human lexical learning. In The Working Notes of the AAAI-2004 Spring Symposium on Interdisciplinary Approaches to Language Learning.

Harris, H. D., & Kiefer, S. M. (2003). A survey of instructors of Introductory Artificial Intelligence. UIUC Department of Computer Science Technical Report UIUCDCS-R-2002-2313.

Harris, H. D. (2003). New Algorithms for Attribute-Efficient On-Line Linear Learning. UIUC Department of Computer Science Technical Report UIUCDCS-R-2003-2352.

Reichler, J. A., & Harris, H. D. (2001). Parallel Online Continuous Arcing and a new framework for wrapping parallel ensembles. In The Working Notes of the IJCAI-01 Workshop on Wrappers for Performance Enhancement in KDD.