About Me

I’m a PhD student at University of British Columbia working on applications of Deep Learning and Machine Learning. More specifically, I’m using self-supervised learning and graph neural networks to solve challenging problems on large-scale datasets such as gigapixel(!) histopathology images while reducing the human supervision. My research interests lie in machine learning, computer vision, and recently, generative AI.
Prior to my PhD, I studied my master’s in computer science at University of Tehran and got my bachelor’s degree in electrical engineering from Sharif University of Technology.

Publications

• CoPilot: Dynamic Top-Down Point Cloud with Conditional Neighborhood Aggregation for Multi-Gigapixel Histopathology Image Representation new!
  R. Nakhli, et al.
  ICCV, 2023
  paper / oral
  fun fact! there’s another paper published at ICCV 2023 under the name CoPilot! link
  
  
• AMIGO! Sparse Multi-modal Graph Transformer with Shared-Context Processing for Representation Learning of Gigapixel Images
  R. Nakhli, et al.
  CVPR, 2023
  paper / oral
  
  
• CCRL: Contrastive Cell Representation Learning
  R. Nakhli, et al.
  ECCVW, 2022
  Best paper award
  paper / oral
  
  
• Movie Recommender System Based on Percentage of View
  R. Nakhli, H. Moradi, M. A. Sadeghi
  5th Conference on Knowledge-Based Engineering and Innovation (KBEI), 2019
  paper
  
  
• Gastrointestinal symptoms and the severity of COVID-19: Disorders of gut–brain interaction are an outcome
  R. Nakhli, et al.
  Journal of Neurogastroenterology and Motility (JNM), 2022
  paper
  
  

Experiences

• Machine Learning Research Intern, Qualcomm
  (May 2023 - September 2023)
  
  
• Senior Software Engineer (Golang), Pasargad Electronic Payment
  (March 2019 - September 2020)
  
  
• Software Engineer (C), Fanap Payment
  (August 2016 - March 2019)
  
  
• Software Engineer Intern (C/Lua), Fanap Payment
  (May 2016 - August 2016)