Russell Richie headshot

Russell Richie

Associate Director
Cognitive Science and MindCORE
University of Pennsylvania
Penn e-mail:
Office: Goddard 203
Personal e-mail:

COGS matters

If you are trying to enroll in COGS1001 but the class is full, please read this before emailing me or Dr. Yang!

If you are a COGS major/minor or a student in COGS1001 trying to meet with me, and my office hours below do not work for you (please try these first!), you can find a time to meet with me here.

Fall 2022 COGS 1001 office hours

In person: Tuesday 9:30am to 11am in Goddard 203.
Virtual: Wednesday 9:30am to 11am on Zoom.

Fall 2022 COGS undergraduate advising office hours

In person: Tuesday 11:00am to 12pm in Goddard 203.
Virtual: Wednesday 2:30pm to 4pm on Zoom.


I am the Associate Director of Cognitive Science and MindCORE at the University of Pennsylvania. Previously (2021-2022), I was a a data scientist in the Tsui Lab at the Children's Hospital of Philadelphia. Before that, (2018-2021) I was a post-doc with Sudeep Bhatia in the Computational Behavioral Science Lab of the Department of Psychology at the University of Pennsylvania. In 2017, I received my PhD in Developmental Psychology at the  University of Connecticut. There I primarily worked in the  Language Creation Lab under the mentorship of  Marie Coppola, and in the SoLab under Whit Tabor. I was also a fellow in the  Language Plasticity -- Genes, Brain, Cognition, & Computation IGERT (which is now the Neurobiology of Language program), and an affiliate of the CT Institute for the Brain and Cognitive Sciences.

My interests and work have changed a lot over the years, but the common thread is using data science, machine learning, and natural language processing tools for social, cognitive, behavioral, and biomedical problems. See my papers below for more!

Here's a link to my vita.


Giovannone, N., Fitzroy, A. B., Richie, R., Jasińska, K., Wood, S., Landi, N., Coppola, M. & Breen, M. (in prep). Prosodic phrase boundary processing in native signers of American Sign Language. Slides from ETAP 2019.

Richie, R., Ruiz, V., Han, S., Shi, L., Tsui, F.R. (in prep). Using dual transformers for multi-task, multi-label token classification (MTML-BERT) to extract social determinants of health from clinical notes. This work was done as part of the 2022 n2c2 Track 2 shared task. We ranked in the top 25% for all subtasks, no more than .02 F1 from 1st place.

Richie, R., & Verheyen, S. (in prep). Using cross-validation to select dimensionality in multidimensional scaling. ICCM extended abstract.

He, L.*, Richie, R.*, & Bhatia, S. (under review). Limitations to optimal search in naturalistic active learning. *Equal contribution

Richie, R., Aka, A., & Bhatia, S. (revise/resubmit). Free association in bidirectional memory networks.

Han, S., Shi, L., Richie, R., Tsui, F.R. (under review). Building Siamese attention-augmented-recurrent convolutional neural networks for document similarity scoring.

Bhatia, S., & Richie, R. (in press). Transformer networks of human concept knowledge. Psychological Review. PsyArXiv preprint.

Richie., R., Grover, S., Tsui, F.R. (2022). Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations. In Proceedings of the 21st Workshop on Biomedical Language Processing (pp. 275–284). Association for Computational Linguistics. Preprint

Han, S., Zhang, R.F., Shi, L., Richie, R., Liu, H., Tseng, A., Quan, W., Ryan, N., Brent, D., & Tsui, F.R. (2022). Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing. Journal of Biomedical Informatics, 103984.

Singh, M.*, Richie, R.*, & Bhatia, S. (2022). Representing and predicting everyday behavior. Computational Brain & Behavior, 5.(1), 1-21.PsyArXiv preprint. *Equal contribution

Zhao, W.J., Richie, R., & Bhatia, S. (2022). Process and content in decisions from memory. Psychological Review, 129(1), 73–106. PsyArXiv preprint

Richie, R., & Bhatia, S. (2022). Knowledge in everyday judgment and decision making: An introduction to the distributed semantics approach. In R. Boyd & M. Dehghani (Eds.) The Atlas of Language Analysis in Psychology. Guilford Press. PsyArXiv preprint.

Richie, R., & Bhatia, S. (2021). Similarity judgment within and across categories: A comprehensive model comparison. Cognitive Science, 45(8), e13030 PsyArXiv preprint.

Richie, R.*, Hall*, M., Cho, P.W., & Coppola, M. (2020). Converging evidence: Enhanced conventionalization of gestural referring expressions in richly-connected networks. Language Dynamics and Change, 10(2), 259-290.PsyArXiv preprint. *Equal contribution

Richie, R., White, B., Hout, M.C., & Bhatia, S. (2020). The spatial arrangement method of measuring similarity can capture high-dimensional, semantic structures. Behavior Research Methods, 52, 1906–1928. PsyArXiv preprint.

Richie, R., Zou, W., & Bhatia, S, (2019). Predicting High-Level Human Judgment Across Diverse Behavioral Domains. Collabra: Psychology, 5(1), 50. PsyArXiv preprint.

Bhatia, S., Richie, R., & Zou, W. (2019). Distributed semantic representations for modeling human judgment. Current Opinion in Behavioral Sciences, 29, 31-36.

Richie, R. (2016). Functionalism in the lexicon: Where is it, and how did it get there? In G. Jarema, G. Libben, & V. Kuperman (Eds.), Thematic Issue of The Mental Lexicon: New Questions for the Next Decade, 11(3), 429–466. Amsterdam: John Benjamins. doi 10.1075/ml.11.3.05ric. PsyArXiv preprint.

Richie, R., Yang, C., & Coppola, M. (2014). Modeling the emergence of natural language lexicons in homesign systemsTopics in Cognitive Science, 6(1), 183-195.

Roseberry, S., Richie, R., Hirsh-Pasek, K., Golinkoff, R.M., Shipley, T. (2011). Babies catch a break: 7- to 9-month-olds track transitional probabilities in continuous dynamic events. Psychological Science, 22(11), 1422-1424.

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