“During Azadeh's time at Data Aspects she passionately contributed to the team's development goals. She was responsible for reviewing existing customer matching logic and recommending improvements to increase efficiency. Her recommendations were clear, well thought through and largely adopted.”
Activity
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As we step into #2026, wishing everyone Q-larity in goals, Q-uality in work, and Q-onnections that truly matter. May the year ahead be filled with…
As we step into #2026, wishing everyone Q-larity in goals, Q-uality in work, and Q-onnections that truly matter. May the year ahead be filled with…
Liked by Azadeh Alavi
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I stand with the people of my home country, Iran, in their fight for freedom against the oppressive and savage regime of the Islamic Republic. It has…
I stand with the people of my home country, Iran, in their fight for freedom against the oppressive and savage regime of the Islamic Republic. It has…
Liked by Azadeh Alavi
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<<Awarded National Quantum Hardware Access Grant to Advance Computational Drug Discovery>> Excited and grateful to announce that I have been awarded…
<<Awarded National Quantum Hardware Access Grant to Advance Computational Drug Discovery>> Excited and grateful to announce that I have been awarded…
Liked by Azadeh Alavi
Experience & Education
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RMIT University
View Azadeh’s full experience
See their title, tenure and more.
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Licenses & Certifications
Publications
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Image Analysis on Symmetric Positive Definite Manifolds (PhD Thesis)
The University of Queensland
See publication
Available Via : https://espace.library.uq.edu.au/view/UQ:347559
In this work we propose three methods for analysing SPD matrices on Riemannian manifolds that unlike traditional methods respect the underlying structure of a given image, while considering the computational complexity of the learning algorithm. While all three methods offer strong solutions for the task of image analysis over SPD manifolds that outperform state-of-the-art methods, each of them tends to tackle one…
Available Via : https://espace.library.uq.edu.au/view/UQ:347559
In this work we propose three methods for analysing SPD matrices on Riemannian manifolds that unlike traditional methods respect the underlying structure of a given image, while considering the computational complexity of the learning algorithm. While all three methods offer strong solutions for the task of image analysis over SPD manifolds that outperform state-of-the-art methods, each of them tends to tackle one vision application better than the rest. This is owed to the existing differences between each vision application. Although all of these vision tasks can be categorised as a image classification problem, each application offers unique challenges, such as very limited training data, strong pose variation etc. -
Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns
Pattern Recognition Journal (PR)
The proposed method is a novel HEp-2 cell classification system inspired by biological vision, which applies similar patterns to the spontaneous neural activities of new born animals. This is a generative model of spontaneous activity patterns is proposed that mixes spontaneous activity patterns with cell images and leads to a more robust model.
Other authors -
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MULTI-SHOT PERSON RE-IDENTIFICATION VIA RELATIONAL STEIN DIVERGENCE
IEEE International Conference on Image Processing (ICIP)
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Relational divergence based classification on Riemannian manifolds
IEEE Winter Conference on Applications of Computer Vision (WACV)
See publicationThe proposed method first presents each image as a point over Riemann manifolds and then represent Riemannian points through their similarities to a set of reference points on the manifold. Classification problems on manifolds are then effectively converted into the problem of finding appropriate machinery over the space of similarities, which can be tackled by conventional Euclidean learning methods such as linear discriminant analysis.
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Classification of human epithelial type 2 cell images using independent component analysis
IEEE International Conference on Image Processing (ICIP)
Other authors -
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Clustering on Grassmann manifolds via kernel embedding with application to action analysis
IEEE International Conference on Image Processing (ICIP)
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Automated classification of dopaminergic neurons in the rodent brain
IEEE International Joint Conference on Neural Networks (IJCNN)
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NEURAL NETWORKS IN THE AUTOMATED CLASSIF ICATION OF NEURAL CELL
Focus On Microscopy
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Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns
Pattern Recognition
Honors & Awards
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CSIRO Next generation
CSIRO
AI for Next Generation Food & Waste Systems:
https://www.rmit.edu.au/news/all-news/2022/nov/critical-technology-training -
RHHRF Grant
Northern Health
Mask Fitting
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Malcolm Moor Industry Award
RMIT University
Deep Subspace Analysing for Semi-supervised Multi-label Diabetic foot Ulcer Identification
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Early Career Scientist (ECS) Miller Development Fund
Baker Heart and Diabetes Institute
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Five-Year Highest Impact Award (IJCB2020)
IEEE International Joint Conference on Biometrics (IJCB)
For paper: Triplet probabilistic embedding for face verification and clustering
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nVIDIA (Maryland, US) : best paper award at IEEE BTAS
nVIDIA
Triplet probabilistic embedding for face verification and clustering
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Australian Postgraduate Award
Australian Government
APA scholarship award 2011 / 2014
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Scholarship for Graduate Certification in Research Commercialization
University of Queensland
This program is designed for students in all fields of study to develop knowledge and skills in commercialisation of research. It examines the fundamentals of the commercialisation process including the innovation process and the contribution of commercialisation to economic and social development. These fundamentals, and the context of commercialisation (including the role of the University and the methods used to commercialise research) are explored.
The broad aim of the program is to…This program is designed for students in all fields of study to develop knowledge and skills in commercialisation of research. It examines the fundamentals of the commercialisation process including the innovation process and the contribution of commercialisation to economic and social development. These fundamentals, and the context of commercialisation (including the role of the University and the methods used to commercialise research) are explored.
The broad aim of the program is to understand and promote the commercialisation of research in industry, both in public and private sector organisations thereby improving business productivity and global competitiveness. Skills are developed to help students in all disciplines to access the power of commercialisation, research, technology and new product/service development. -
Attended Winter School in Mathematical and Computational Biology
UQ
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Summer semester scholarship Award
Eskitis Institute for Cell and Molecular Therapies
Summer semester scholarship for 2007
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Academic excellence award
Griffith University
Academic excellence awarded in 2005/2006 Griffith University
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Full Tuition Fee Scholarship
Hormozgan university
Full Tuition Fee Scholarship for bachelor of Applied Mathematics1998 - 2002
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National ICT Australia scholarship award
National ICT Australia (NICTA)
NICTA Research scholarship award 2011 / 2014
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Summer semester scholarship Award
IIIS Griffith University
Summer semester scholarship for 2006/2007
Languages
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English
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Organizations
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IEEE 22nd International Conference on Pattern Recognition
Local Committee Member for ICPR 2014 I3A workshop
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Computer visions group of UQ University
Organiser of reading sessions
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Australian Computer Society (ACS)
Committee Member of the ACS Gold Coast Chapter
-2006-2012 A Committee member of the ACS Gold Coast chapter
Recommendations received
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Join now to viewMore activity by Azadeh
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Right now, millions of people inside Iran are cut off from the world. No internet. No communication. For many Iranians living and working outside…
Right now, millions of people inside Iran are cut off from the world. No internet. No communication. For many Iranians living and working outside…
Liked by Azadeh Alavi
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Our team at the MLBC lab. I am so proud of you all. https://lnkd.in/eHUHQRVx
Our team at the MLBC lab. I am so proud of you all. https://lnkd.in/eHUHQRVx
Liked by Azadeh Alavi
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