- 2021: Ensembling with deep generative views (CVPR 2021)
- 2021: Using latent space regression to analyze and leverage compositionality in GANs (ICLR 2021)
- 2020: What makes fake images detectable? Understanding properties that generalize (ECCV 2020)
- 2020: On the 'steerability' of generative adversarial networks (ICLR 2020)
- 2019: Evolution of semantic networks in biomedical texts (Journal of Complex Networks, 2019)
- 2018: Uncertainty Estimation in Bayesian Neural Networks and Links to Interpretability (Department of Engineering, University of Cambridge, 2018)
- 2018: Name and Face Matching (MITRE Corporation; US. Patent App. 16/042,958)
- 2018: Development of a Next Generation Tomosynthesis System (SPIE Medical Imaging Conference, 2018)
- 2017: Evolution of brain network dynamics in neurodevelopment (Network Neuroscience, 2017)
- 2016: Functional network dynamics of the language system
2. Awards and Fellowships:
- NSF Graduate Research Fellowship
- Adobe Research Fellowship
- Meta Research PhD Fellowship
- Churchill Scholarship
Research Experience
1. Adobe Research: Worked with Richard Zhang, Jun-Yan Zhu, Michael Gharbi, and Eli Shechtman
2. Google Research (NYC): Worked with Noah Snavely, Zhengqi Li, and Richard Tucker
3. Facebook: Collaborated with Ser-Nam Lim
Education
1. Massachusetts Institute of Technology (MIT): Graduate student in Electrical Engineering and Computer Science, advised by Phillip Isola
2. Churchill College, University of Cambridge: MPhil in Machine Learning, focusing on uncertainty and interpretability in Bayesian neural networks
3. University of Pennsylvania: Bachelor's degree in Computer Science and Bioengineering, worked with Dr. Danielle S. Bassett on computational neuroscience, focusing on modeling neural processes as dynamic networked systems
Background
A graduate student in EECS at MIT CSAIL, advised by Phillip Isola. Current interests are in computer vision and controllable image synthesis.