Students

I have had the pleasure of mentoring and collaborating with several talented graduate students in the past:

• Tyler LaBonte (Georgia Tech), 2022 -

• Jiaheng Wei (UC Santa Cruz), 2022

• Yatong Chen (UC Santa Cruz), 2022
  Fast Implicit Constrained Optimization of Non-decomposable Objectives for Deep Networks

• Kushagra Pandey (IIT Kanpur / UC Irvine), 2021 - DiffuseVAE: Efficient, controllable and high-fidelity generation from low-dimensional latents

• Yatin Dandi (IIT Kanpur), 2020
  Generalized adversarially learned inference, AAAI 2021

• Yang Song (Stanford), 2020
  Score-based generative modeling through stochastic differential equations, ICLR 2021 (Outstanding paper)

• Min Jin Chong (UIUC), 2020
  Retrieve in style: Unsupervised facial feature transfer and retrieval, CVPR 2021

• Giannis Daras (UT Austin), 2020
  Solving Inverse Problems with NerfGANs

• Rui Shu (Stanford), Summer 2019
  Weakly supervised disentanglement with guarantees, ICLR 2020

• Esther Robb (Virginia Tech), Summer 2019
  Few-shot adaptation of generative adversarial networks

• Akshay Rangamani (JHU), 2018
  A scale invariant measure of flatness for deep network minima

• Yunhui Guo (UCSD), Summer 2018
  SpotTune: Transfer Learning through Adaptive Fine-tuning, CVPR 2019

• Tushar Nagarajan (UT Austin) and Zuxuan Wu (UMD), Summer 2017
  BlockDrop: Dynamic Inference Paths in Residual Network, CVPR 2018 (Spotlight)

• Anant Raj (MPI Tübingen), Summer 2016
  Local Group Invariant Representations via Orbit Embeddings, AISTATS 2017

• Yongxi Lu (UCSD), Summer 2016
  Automating the design of efficient multi-task deep architectures, CVPR 2017 (Spotlight)

• Shuangfei Zhai (SUNY Binghamton), Summer 2016
  A novel stochastic pooling/subsampling approach for CNNs, CVPR 2017

• Jun Araki (CMU), Summer 2015
  Improving word representations using relational knowledge, ACL 2016 (Oral, short paper)

• Ian E.H. Yen (CMU), Summer 2015
  Scalable exemplar selection for data summarization and facility location, AISTATS 2016

Please feel free to drop me a note if you are interested in an internship or in collaborating with me.