Ali Hatamizadeh

Ali Hatamizadeh is a research scientist at NVIDIA as of 2020. He has earned his PhD at the University of California, Los Angeles (UCLA) in Computer Science and advised by Demetri Terzopoulos.

His research interests include self-supervised learning, novel architectures for data and hardware-efficient deep learning and security and fairness in federated learning.

Email  /  Google Scholar  /  LinkedIn  /  Researchgate  /  Twitter  /  GitHub

Selected Publications

• Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
  Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang, Holger Roth, Daguang Xu
  BRATS 21 Challenge, MICCAI Brainlesion Workshop, January 2022
  arXiv / Code

• UNETR: Transformers for 3D Medical Image Segmentation
  Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger Roth, Daguang Xu
  Winter Conference on Applications of Computer Vision (WACV), January 2022
  arXiv / Code

• Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis
  Yucheng Tang, Dong Yang, Wenqi Li, Holger Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, Ali Hatamizadeh
  Tech report, November 2021
  arXiv / Code

• Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
  Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam, Ziyue Xu, Xiaosong Wang, Evrim Turkbey, Daguang Xu
  International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), September 2021
  arXiv

• The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization in Medical Image Segmentation
  Vishwesh Nath, Dong Yang, Ali Hatamizadeh, Anas Abidin, Andriy Myronenko, Holger Roth, Daguang Xu
  International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), September 2021
  arXiv

• End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery
  Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos
  European Conference on Computer Vision (ECCV), August 2020
  arXiv / Slides

• End-to-End Boundary Aware Networks for Medical Image Segmentation
  Ali Hatamizadeh, Demetri Terzopoulos, Andriy Myronenko
  MICCAI Machine Learning in Medical Imaging (MLMI), October 2019
  arXiv

• Deep Active Lesion Segmentation
  Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel Rubin, Demetri Terzopoulos
  MICCAI Machine Learning in Medical Imaging (MLMI), October 2019
  arXiv / Code / Poster

Activities

I have had the pleasure to serve in the program committee or a reviewer for the following conferences and journals:
• Computer Vision and Pattern Recognition (CVPR) 2019, 2020, 2021, 2022
• European Conference on Computer Vision (ECCV) 2020
• International Conference on Computer Vision (ICCV) 2019, 2021
• Medical Image Computing and Computer Assisted Intervention (MICCAI) 2019, 2021, 2022
• IEEE Winter Conference on Applications of Computer Vision (WACV) 2020
• IEEE Transaction on Medical Imaging (TMI)
• IEEE Journal of Biomedical and Health Informatics (J-BHI)
• International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)
• Journal of Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization (CMBBE)

Teaching

• UCLA CS 168 : Computational Medical Image Analysis - Spring 2020
• UCLA CS 174 : Introduction to Computer Graphics - Winter 2020
• UCLA CS 269 : Topics in Artificial Intelligence - Fall 2019
• UCLA CS 188-2 : Introduction to Computer Vision - Fall 2019
• UCLA CS 168 : Computational Medical Image Analysis - Spring 2019
• UCLA CS 32 : Introduction to Computer Science II - Winter 2019

Mentored Students

• Yucheng Tang, NVIDIA Research Intern, 2021
• Debleena Sengupta, UCLA CS Graduate Student (Masters-Thesis Track), 2019
• Zhengyuan Liu, UCLA CS Graduate Student (Masters-Capstone Track), 2019
• Wuyue Lu, UCLA CSST International Exchange Student, 2018
• Jie Mei, UCLA CSST International Exchange Student, 2018