Personal profile


Dr. Hamid Rezatofighi, presently a lecturer at the Faculty of Information Technology, Monash University, Australia, has focused his research on computer vision, machine learning, and robotics. His work has particularly advanced robot visual perception in dynamic environments.

Formerly an Endeavour Research Fellow at Stanford Vision Learning (SVL), Stanford University and a Senior Research Fellow at the Australian Institute for Machine Learning (AIML),  the University of Adelaide, he completed his Ph.D. at the Australian National University in 2015. With a body of work exceeding 70 papers, encompassing over 20 high-quality journal articles and 40+ contributions to prominent conferences, including IEEE TPAMI, IEEE TIP, IEEE RA-L, CVPR, ICCV, ECCV, NeurIPS, AAAI, IJCAI, ICRA, and IROS, Dr. Rezatofighi has significantly influenced these fields. Since 2020, he is involved as an area chair in top-tier AI conferences like CVPR, NeurIPS, ECCV, IJCAI, and WACV, showcasing his commitment to the academic community. Having secured over $17 million in research funding, including substantial grants from three DARPA projects and an ARC Discovery Project, he continues to contribute meaningfully to the research landscape.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Computer Science, PhD, Bayesian Multi-Target Tracking in Time-Lapse Fluorescence Microscopy Sequences, Australian National University (ANU)

18 Mar 20111 Jul 2014

Award Date: 17 Jul 2015

Electrical Engineering - Biomedical Engineering, Master, Automatic Recognition of White Blood Cells in Hematological Images, University of Tehran

30 Sept 200628 Feb 2009

Award Date: 28 Feb 2009

Research area keywords

  • Computer Vision
  • Robot Vision
  • Robot Perception
  • Robotics
  • Deep Learning
  • Machine Learning

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or