I am a PhD candidate in Computer Science at UC Berkeley working on Computer Vision and Machine Learning. I am part of Berkeley AI Research Lab (BAIR) advised by Prof. Trevor Darrell.
I am interested in learning complex data manifolds by Generative Adversarial Networks (GANs). I develop algorithms to improve the performance of such networks specifically in learning the distribution of structural and compositional visual domains. Besides pushing for theoretical advancements in GANs, I am also excited about its artistic applications leading to new collaborative tools across art and computer science.
During my PhD, I have spent time at Google Brain (with Ian Goodfellow and Augustus Odena ) and Adobe Research (with Matthew Fisher ). Earlier, I had the pleasure to work with Pieter Abbeel and Suvrit Sra while I was a visiting researcher at UC Berkeley.
News
- I am co-organizing the 4th Workshop on Machine Learning for Creativity and Design at NeurIPS 2020.
- Our recent work joint with Google Brain, Zurich on Semantic Bottleneck Scene Generation is on arXiv. Code is released here.
- Our Compositional GAN paper has been published at the International Journal of Computer Vision (IJCV) 2020. Code is released here.
- I am selected as one of the 2019 Rising Stars in EECS hosted by the University of Illinois Urbana-Champaign.
- Our paper on Discriminator Rejection Sampling joint with the Google Brain team has been accepted at ICLR 2019.
- A summary of my research has been reflected in this Facebook Research blog post.
- I spent summer 2018 as a research intern at Google Brain.
- Our paper on Multi-Content GAN for Few-Shot Font Style Transfer has been accepted as spotlight talk at CVPR 2018. I wrote a blog post on font style transfer here.
- I am awarded the 2018 Facebook PhD Fellowship. Thanks Facebook. Full list is here.
- I spent summer 2017 as a research intern at Adobe Creative Intelligence Lab. Our Multi-Content GAN algorithm led to FontPhoria presented on the Adobe MAX 2018 stage.
- We organized the workshop for Women in Computer Vision (WiCV) at CVPR 2017. Check out this NVIDIA blog covering WiCV 2017 mentoring dinner. Read more about the workshop in the Computer Vision News.
- Our paper on Learning Detection with Diverse Proposals got accepted at CVPR 2017.
- We organized the Workshop for Women in Computer Vision (WiCV) at CVPR 2016.
- Our paper on Auxiliary Image Regularization for Deep CNNs with Noisy Labels got accepted at ICLR 2016.