About Me

  • Hi! I am a first year PhD student at Berkeley AI Research, advised by Prof. Alexei Efros, with interests in computer vision and machine learning. My research is supported by the DOE Computational Science Graduate Fellowship.
  • I recently graduated from Northwestern with a BS in Computer Science, advised by Prof. Aggelos Katsaggelos in the Image and Video Processing Lab (IVPL). I have also had the pleasure of working with: Prof. Pietro Perona (Caltech Vision Group), Jennifer J. Sun (Incoming Faculty at Cornell), Vibhav Vineet, Neel Joshi (MSR Computer Vision Group), Prof. Ollie Cossairt (Northwestern Computational Photography Lab), Boqing Gong (Google Research).


Idempotent Generative Network
Assaf Shocher, Amil Dravid, Yossi Gandelsman, Inbar Mosseri, Miki Rubinstein, Alexei A. Efros
ICLR, 2024
[pdf] / [website] / [code coming soon!]

Rosetta Neurons: Mining the Common Units in a Model Zoo
Amil Dravid*, Yossi Gandelsman*, Alexei A. Efros, Assaf Shocher.
ICCV, 2023
[pdf] / [website] / [code]

BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos
Jennifer J. Sun*, Pierre Karashchuk*, Amil Dravid*, et al.
CVPR, 2023.
[pdf] / [website] / [code]

medXGAN: Visual Explanations for Medical Classifiers through a Generative Latent Space
Amil Dravid, Florian Schiffers, Boqing Gong, Aggelos K. Katsaggelos
CVPR Trusted Computer Vision Workshop, 2022.
[pdf] / [project page]

Investigating the Potential of Auxiliary-Classifier GANs for Image Classification in Low Data Regimes
Amil Dravid, Florian Schiffers, Yunan Wu, Oliver Cossairt, Aggelos K. Katsaggelos
ICASSP, 2022.
[pdf] / [code]

Visual Explanations for Convolutional Neural Networks via Latent Traversal of Generative Adversarial Networks (Student Abstract)
Amil Dravid, Aggelos K. Katsaggelos
AAAI, 2022
[pdf] / [code]

Early Upper Aerodigestive Tract Cancer Detection Using Electron Microscopy to Reveal Chromatin Packing Alterations in Buccal Mucosa Cells
Oisín Bugter, Yue Li, Anouk H.G. Wolters, Vasundhara Agrawal, Amil Dravid, et al.
Microscopy and Microanalysis, 2021.

DeepCOVID-XR: an artificial intelligence algorithm to detect COVID-19 on chest radiographs trained and tested on a large US clinical data set
Ramsey M. Wehbe, Jiayue Sheng, Shinjan Dutta, Siyuan Chai, Amil Dravid, et al.
Radiology, 2021.
[pdf] / [code]

Interpretation of brain morphology in association to alzheimer’s disease dementia classification using graph convolutional networks on triangulated meshes
Emanuel Azcona, Pierre Besson, Yunan Wu, Arjun Punjabi, Adam Martersteck, Amil Dravid, et al.
MICCAI ShapeMI Workshop, 2020.

Employing deep networks for image processing on small research datasets
Amil Dravid
Microscopy Today, 2019.
[pdf] / [code]