Hi! I am a postdoctoral associate at Yale University, working at the intersection of interpretable multi-modal deep learning, time series analysis, large language models, and representation learning, with applications in neuroscience, biology, and computer vision.
Prior to Yale, I received my Ph.D. from Université Laval and Mila (Montreal-based AI Institute), advised by Jean-François Lalonde and Christian Gagné, where my research focused on representation learning and meta-learning in limited data situations. My last Ph.D. project was a collaboration with Hugo Larochelle.
Prior to my Ph.D. in Canada, I was with the Image Lab and obtained my M.S. from METU, where I worked on brain decoding.
arı ©
Contact: arman.afrasiyabi@yale[dot]edu
Publications
-
ICASSP
Latent representation learning for multimodal brain activity translation
International Conference on Acoustics, Speech and Signal Processing, 2025
-
CCAM
Looking through the mind's eye via multimodal encoder-decoder networks
Center for Collaborative Arts and Media Journal, 2024
-
ICCV
DarSwin: distortion aware radial swin transformer
International Conference on Computer Vision, 2023
-
CVPR
Matching feature sets for few-shot image classification
International Conference on Computer Vision and Pattern Recognition, 2022
-
ICCV
Mixture-based feature space learning for few-shot image classification
International Conference on Computer Vision, 2021
-
ECCV Spotlight
Associative alignment for few-shot image classification
European Conference on Computer Vision, 2020
-
ICASSP
Non-euclidean vector product for neural networks
International Conference on Acoustics, Speech and Signal Processing, 2018
-
ICCI*CC
A sparse temporal mesh model for brain decoding
15th International Conference on Cognitive Informatics & Cognitive, 2016
Reviewer
- NeurIPS-2023, ICLR-2023, TIP-2023, TNN-2023, CVPR-2023, NeurIPS-2022, CVPR-2022, ECCV-2022, ICLR-2022, ICCV-2021, 3DV-2021, and MAIS-2021.
Talks and presentations
- In Aug. 2023 I gave a talk on my Postdoc projects to Brain Dynamics Lab at Stanford University.
- In Feb. 2022, I gave a talk on my PHD projects to Prof. Smita Krishnaswamy's research group at Yale.
- At CVPR 2022, we are presenting Matching feature sets for few-shot image classification.
- In 12th Feb. 2022, upon the invitation (invitation link) of Computer Vision Talks, I presented our MixtFSL.
- At ICCV 2021, I am presenting Mixture-based feature space learning for few-shot... [video]
- On 26, Feb 2021, I presented Transformers to Prof. Jean-François Lalonde's research group. [my slides]
- In Feb 2021, I gave a presentation on PMM and Ass. Alignment at IID, Université Laval. [my slides]
- At ECCV 2020, I presented our work “Associative Alignment for Few-shot Classification”. [video]
- In July 2020, I gave a talk on "Advances in few-shot learning" at the IFT 6501 course. [my slides]
- In March 2020, I gave a talk on my last research project at IID
Reports and proposal
- At the end of the first year of the M.S. (under the initial supervision of Prof. Ilkay Ulusoy), I prepared three reports on dynamic causal modeling (DCM) of the human brain: [Report I], [Report II], and [Report III].
- At the second year of my Ph.D., I successfully passed my PhD. exams: [presentation] and [proposal].