Vy Ai Vo, Ph.D.

Abbreviated CV (complete CV here)



Google Scholar

Semantic Scholar



Hillsboro, Oregon USA


AI/ML Research Scientist, Intel Labs, Intel Corporation

Senior staff scientist in the Brain-Inspired Computing Lab

2019 - Present


University of California, San Diego, La Jolla, CA

Ph.D., M.S., Neurosciences with Computational specialization

Thesis commitee: John T. Serences (advisor), Ed Vul, Timothy Gentner, Ed Callaway, Douglas Nitz

2013 - 2019

Swarthmore College, Swarthmore, PA

B.A. with High Honors, Biology, Cognitive Science double major

Neuroscience research: Kathleen K. Siwicki; Psychology research: Frank Durgin

2007 - 2011


Memory in humans and deep language models: Linking hypotheses for model augmentation. Raccah, O., Chen, P., Willke, T., Poeppel, D., Vo, V.A., Memory in Artificial and Real Intelligence (MemARI) workshop, NeurIPS, 2022 [link]

Cache-memory gated graph neural networks. Ma, G., Vo, V.A., Ahmed, N., Willke, T., Memory in Artificial and Real Intelligence (MemARI) workshop, NeurIPS, 2022 [link]

Shared representational formats for information maintained in working memory and information retrieved from long-term memory. Vo, V.A., Sutterer, D.W., Foster, J.J., Sprague, T.C., Awh, E., Serences, J.T., Cerebral Cortex, 2022 [link]

Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses. Antonello, R., Turek, J.S., Vo, V.A., Huth, A., NeurIPS, 2021 [link]

BrainIAK: The Brain Imaging Analysis Kit. Kumar, M., Anderson, M., Antony, J.W., Baldassano, C., Brooks, P., Cai, M., Chen, P-H.C., Ellis, C., Henselman-Petrusek, G., Huberdeau, D., Hutchinson, J.B., Li, Y.P., Lu, Q., Manning, J., Mennen, A., Nastase, S., Richard, H., Shapiro, A.C., Schuck, N., Shvartsman, M., Sundaram, N., Suo, D., Turek, J.S., Vo, V., Wallace, G., Wang, Y., Zhang, H., Zhu, X., Capotă, M., Cohen, J., Hasson, U., Li, K., Ramadge, P.J., Turk-Browne, N., Willke, T., Norman, K.A. , Aperture, 2021 [link]

Long short-term memory with slower information decay. Chien, H-Y.S., Beckage, N.M., Vo, V.A., Turek, J.S., Honey, C., Willke, T.L., LatinX in AI workshop, International Conference on Learning Representations (ICLR), 2021 [link]

Multi-timescale representation learning in LSTM language models. Mahto, S., Vo, V.A., Turek, J.S., Huth, A.G., International Conference on Learning Representations (ICLR), 2021 [link]

Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech. Jain, S., Vo, V., Mahto, S., LeBel, A., Turek, J., Huth, A., Neural Information Processing Systems (NeurIPS), 2020 [link]

Approximating stacked and bidirectional recurrent architectures with the delayed recurrent neural network. Turek, J., Jain, S., Vo, V., Capotă, M., Huth, A., Willke, T., International Conference on Machine Learning (ICML), 2020 [link]

Value-driven attentional capture enhances distractor representations in early visual cortex. Itthipuripat, S.I.*, Vo, V.A.*, Sprague, T.C., Serences, J.T., PLOS Biology, 2019 [link]

Multivariate analysis of BOLD activation patterns recovers graded depth representations in human visual and parietal cortex. Henderson, M.H.*, Vo, V.A.*, Chunharas, C., Sprague, T.C., Serences, J.T., eNeuro, 2019 [link]

Inverted encoding models assay population-level stimulus representations, not single-unit neural tuning. Sprague, T.C.*, Adam, K.C.S.*, Foster, J.J.*, Rahmati, M.*, Sutterer, D.W.*, Vo, V.A.*, eNeuro, 2018 [link]

Dissociable signatures of visual salience and behavioral relevance across attentional priority maps in human cortex. Sprague, T.C., Itthipuripat, S., Vo, V.A., and Serences, J.T., Journal of Neurophysiology, 2018 [link]

Spatial tuning shifts increase the discriminability and fidelity of population codes in visual cortex. Vo, V.A., Sprague, T.C., and Serences, J.T., Journal of Neuroscience, 2017 [link]

Young children bet on their numerical skills: Metacognition in the numerical domain.. Vo, V.A., Li, R., Kornell, N., Pouget, A., Cantlon, J.F., Psychological Science, 2014 [link]

Professional Activities & Service

Project mentor, NeuroMatch Academy - computational neuroscience (2021)

Workshop co-organizer, ICLR ''How can findings about the brain improve AI systems?'' (2021)

Workshop committee, NeurIPS ''Context and compositionality in biological and artificial systems'' (2019)

Ad-hoc reviewer, PLOS Computational Biology, Cerebral Cortex, eNeuro, Journal of Cognitive Neuroscience, NeuroImage, PNAS, NeurIPS

Guest lecturer, Fundamentals in Statistics and Computation for Neuroscientists (graduate), Data Analysis in MATLAB (graduate), Sensation & Perception (undergraduate) (2015-2016)

Teaching assistant, Computational neuroscience workshops/labs for Neurosciences Graduate Program boot camp, Data Analysis in MATLAB (2014-2015)

This is an abbreviated CV. A more complete document is available here