Amir Eskandari

Blog

I am a PhD student in the School of Computing at Queen's University in Ontario, Canada. I am supervised by Dr. Farhana Zulkernine and Dr. Jordan Poppenk. I am also a PhD trainee at Connected Minds CFREF. My research focuses on Graph Machine Learning for text and time-series data, with applications mainly in AI-Reasoning, Multi-Variate Time-Series Imputation, Automated Diagnosis Systems, and Dialogue Systems.

Prior to my PhD, I was a graduate research assistant at AUT. I proudly hold an M.Sc. degree from AmirKabir University of Technology and a B.Sc. degree from IKIU, both in the field of Electrical Engineering. During my master's, I worked on multi-variate time-series imputation using GNNs. At AUT, I was supervised by Dr. Vahid Pourahmadi.

I love talking about science and technology. Shoot me an email if you'd like to discuss!

Google Scholar | CV | LinkedIn | GitHub | Twitter | Email: amir.eskandari@queensu.ca

News
[Oct 2024] Two papers submitted to ICASSP 2024!
[Aug 2024] Submitted our survey on Transformer-based Models to ACM Computing Surveys
[Aug 2024] Our paper on GN2DI accepted to IEEE FMLDS 2024
[May 2024] I won prestigious Connected Minds PhD Award
[September 2023] I started my PhD in School of Computing, Queen's University
Publications
Submitted (ICASSP)
SDA-GRIN for Adaptive Spatial-Temporal Multivariate Time Series Imputation
A. Eskandari, A. Aanad, D. Sharma, F. Zulkernine.
Code (Comming Soon!) Website arXiv
Submitted (ICASSP)
Self-Supervised Keypoint Detection with Distilled Depth Keypoint Representation
A. Aanad, E. Rashno, A. Eskandari, F. Zulkernine.
Code (Comming Soon!) Website arXiv
Submitted (ACM Survey)
Survey: Transformer-based Models in Multimodal Data Processing
E. Rashno, A. Eskandari, A. Aanad, F. Zulkernine
arXiv
IEEE FMLDS 2024
GN2DI: A Scalable Graph Neural Network Framework for Spatial Missing Data Imputation in Sensor Networks
A. Eskandari, S. Jamshidiha, V. Pourahmadi.
Code arXiv ((Comming Soon!)