Jasmine Collins

I am a PhD student at UC Berkeley and a member of Berkeley AI Research advised by Jitendra Malik and funded by the NSF GRFP. Previously I was part of the inaugural group of AI Residents at Google Brain.

I did my undergraduate at the University of Pittsburgh where I double-majored in neuroscience and computer science, and minored in chemistry. During my time there I had the pleasure of working with David Koes on computational drug discovery.

email  /  CV  /  google scholar  /  twitter  /  github

profile photo

My current research interests include computer vision and human perception. I'm interested in how we can teach computers to see and perceive the world as a collection of objects in 3D without requiring hundreds of thousands of annotations. Plus, how can computational tools be used in novel ways to help us better understand and uncover insights about human perception?

ABO: Dataset and Benchmarks for Real-World 3D Object Understanding
Jasmine Collins, Shubham Goel, Achleshwar Luthra, Leon Xu, Kenan Deng, Xi Zhang, Thomas F. Yago Vicente, Himanshu Arora, Thomas Dideriksen, Matthieu Guillaumin, Jitendra Malik
arXiv, 2021
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GANmouflage: 3D Object Nondetection with Texture Fields
Rui Guo, Jasmine Collins, Oscar de Lima, Andrew Owens
arXiv, 2021
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Exploring Exploration: Comparing Children with RL Agents in Unified Environments
Eliza Kosoy, Jasmine Collins, David M Chan, Sandy Huang, Deepak Pathak, Pulkit Agarwal, John Canny, Alison Gopnik, Jessica B. Hamrick
International Conference on Learning Representations (ICLR) Workshop, 2020
(Oral Presentation)
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Automatically Inferring Task Context for Continual Learning
Jasmine Collins, Kelvin Xu, Bruno Olshausen, Brian Cheung
Cognitive Computational Neuroscience (CCN), 2019   (Oral Presentation)
paper / bibtex / talk (recording)
Accelerating Training of Deep Neural Networks with a Standardization Loss
Jasmine Collins, Johannes Balle, Jonathon Shlens
arXiv, 2019
paper / bibtex
Inferring Single-trial Neural Population Dynamics Using Sequential Auto-encoders
Chethan Pandarinath, Daniel J O'Shea, Jasmine Collins, Rafal Jozefowicz, Sergey D. Stavisky, Jonathan C. Kao, Eric M. Trautmann, Matthew T. Kaufman, Stephen I. Ryu, Leigh R. Hochberg, Jaimie M. Henderson, Krishna V. Shenoy, Larry F. Abbott, David Sussillo
Nature Methods, 2018
paper / bibtex / code

Capacity and Trainability in Recurrent Neural Networks
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
International Conference on Learning Representations (ICLR), 2017
paper / bibtex / data

A D3R Prospective Evaluation of Machine Learning for Protein-ligand Scoring
Jocelyn Sunseri, Matthew Ragoza, Jasmine Collins, David Koes
Journal of Computer-Aided Molecular Design, 2016
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cs188 Graduate Student Instructor, CS 188 Spring 2020

Thanks to Jon Barron for this iconic website template.