Mehrtash Harandi
Associate Professor
Department of Electrical and Computer Systems Eng., Monash University
Address: 232, Eng. Building 72, 14 Alliance lane, Clayton, Melbourne, VIC, Australia
e-mail: mehrtash (döt) harandi (ät) monash (döt) edu
About me
I joined Monash’s Department of Electrical and Computer Systems Engineering (ECSE) in August 2018. Before joining Monash University, I spent five wonderful years at Canberra Research Laboratory-NICTA, working with Prof. Richard Hartley and Prof. Fatih Porikli. Before that, I worked at Queensland Research Laboratory-NICTA with Prof. Brian Lovell.
I am interested in various aspects of learning, especially with a flavor of visual data (see my google scholar page). I am an associate editor of the IET-CV, Frontiers In Imaging, and Journal of Imaging and regularly review papers for top conferences and journals in ML/CV, including CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, IEEE TPAMI, IEEE TNNLS, IEEE TIP.
Teaching
Neural Networks and Deep Learning, Monash University, 2019↝
Probability and AI for Engineers, Monash University, 2024↝
Computer Vision, Monash University, 2022↝2023
Advanced Engineering Data Analysis, Monash University, 2019-2022
Engineering Data Analytics, Australian National University, 2016-2018
Signal and Image Processing II, The University of Queensland, 2010-2012
Grants and Awards
ARC, Exploiting Geometries of Learning for Fast, Adaptive and Robust AI (with Prof. Hartley, Prof. Phung and Dr. Le), A$420k, 2023-2025
DARPA, Learning to Learn and Adapt with Less Labels, A$3,260k, 2019-2023
Data61-CSIRO, Trustworthy Learning from Limited Data, A$555k, 2018-2022
NFRFE, AI architectures for reliable prediction and optimization of advanced manufacturing processes (with Prof. A. Milani (UBC)), A$275k, 2020-2021
ARC, Semantic Vectorisation: From Bitmaps to Intelligent Representations (with Prof. Porikli), A$385k, 2015-2019
News
Four papers accepted to CVPR'24, congratulations to Henry, Yihang, Yanshuo and the team.
Our work on robust MRI reconstruction is accepted to ISBI'24; congratulations to Mevan.
Two papers accepted to AAAI'24, congratulations to Nilakshan and Jing.
Will serve as an AC for ACM-MM'24 and SPC for IJCAI'24.
Our work on robust MRI reconstruction is accepted to Computers in Biology and Medicine; congratulations to Mevan.
Our work on subspace distillation for continual learning is accepted by Neural Networks, congratulations to Kaushik.
Two papers accepted to ICCV'23, congratulations to Jie and Samitha.
Our work on segmenting volumetric medical data is accepted to Nature Machine Intelligence, huge congratulations to Himashi.
Our work on vector quantized auto-encoders is accepted to ICML'23. Congratulations to Vuong and Le.
Mevan won first place at the Visualize Your Thesis (VYT) competition and will be competing internationally. You can watch Mevan's winning video here.
Will serve as an AC for NeurIPS'23 and ICLR'23.
Our work on Learning to Optimize on Riemannian Manifolds is accepted to TPAMI. Congratulations to Zhi.
Three papers accepted to NeurIPS'22, congratulations to Markus, Rongkai, Zhi.
Our work on Meta-Learning for manifold data is accepted to TPAMI. Congratulations to Zhi.
Outstanding reviewer, CVPR'21