| Home | People | Research | Publications | Demos |
| News | Jobs |
Prospective
Students |
About | Internal |
|
|
|
||||||
Brief Bio
I graduated in April 2022 with a Masters at UC San Diego, where I used machine learning to solve computer vision problems. I joined SVCL as a sophomore in 2017 working on the OOWL dataset. I have a computer science background, and earned a B.Sc in this field from UC San Diego in 2019. Currently I'm working on Tesla Autopilot. For more information about me, please visit my personal website.
Research
In my research, I have focused on various topics including 2D/3D detection, domain adaptation, autonomous vehicle navigation, GANs, 3D reconstruction, embeddings, self-supervised learning, and explainable neural networks.
Publications
|
|
Understanding Learned Visual Invariances Through Hierarchical Dataset Design and Collection |
|
|
Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction |
|
|
Catastrophic Child’s Play: Easy to Perform, Hard to Defend Adversarial Attacks |
|
|
Domain Adaptation for Real-World Single View 3D Reconstruction |
|
|
OOWL500: Overcoming Dataset Collection Bias in the Wild |
Education
|
|
||
|
|
|
Awards
|
|
||
|
|
||
|
|
|
||
|
|
|
||
|
|
|
©
SVCL