Recent Publications

(2022). How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?. NeurIPS 2022 Datasets and Benchmarks Track.

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(2021). Conditional Negative Sampling for Contrastive Learning of Visual Representations.. ICLR 2021.

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(2021). Unsupervised neural network models of the ventral visual stream. PNAS.

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(2020). Unsupervised Learning from Video with Deep Neural Embeddings. CVPR 2020.

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(2019). Local Aggregation for Unsupervised Learning of Visual Embeddings. ICCV 2019, Oral presentation, Best Paper Award Nomination.

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(2018). Flexible Neural Representation for Physics Prediction. NeurIPS 2018.

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(2017). Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System. NIPS 2017, Oral presentation.

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(2017). Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons. Frontiers in Computational Neuroscience.



I was a teaching assistant for the following courses at Stanford:

  • PSYCH252: Statistical Methods for Behavioral and Social Sciences, Winter 2021
  • PSYCH251: Experimental Methods, Autumn 2019
  • PSYCH249 / CS375: Large-Scale Neural Network Models for Neuroscience, Autumn 2018
  • PSYCH253: High-Dimensional Methods for Behavioral and Neural Data, Spring 2018, Spring 2019, Spring 2021