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 centers on the intersection of graph machine learning and large language models.
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 | LinkedIn | GitHub | Twitter | Email: amir.eskandari@queensu.ca
[May 2025] Two papers got accepted in IEEE COMPSAC.
[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!
[March 2023] I defended my master's thesis on GNNs for multivariate time series with an excellent grade!
Preprint
SDA-GRIN for Adaptive Spatial-Temporal Multivariate Time Series Imputation
A. Eskandari, A. Aanad, D. Sharma, F. Zulkernine.
Preprint
Survey: Transformer-based Models in Multimodal Data Processing
E. Rashno, A. Eskandari, A. Aanad, F. Zulkernine
IEEE FMLDS 2024
GN2DI: A Scalable Graph Neural Network Framework for Spatial Missing Data Imputation in Sensor Networks
A. Eskandari, S. Jamshidiha, V. Pourahmadi.
