Alireza Dizaji
Montreal, Quebec, Canada
Summary
🤩
Rockstar🎓
Top SchoolAlireza Dizaji is an AI researcher and machine learning engineer with six years of experience bridging academic research and product-focused ML systems, currently based in Montreal. He has worked on temporal graph learning, model interpretability, and medical imaging, and recently led development of T-GRAB, a benchmark exposing weaknesses in temporal reasoning across 11 state-of-the-art TGNNs. His industry work spans building multi-modal, agent-aware RAG systems and productionized ingestion pipelines at Autodesk, and aligning text-to-image diffusion models with human preferences during a MILA residency that extended the ImageReward project. He combines deep technical chops (tensor decomposition for KV-cache compression, LibTorch C++ optimizations) with practical deployment experience on AWS and Hugging Face Accelerate. Notably, his contributions include hands-on educational content around sequence models and an open-source T-GRAB codebase, reflecting both teaching and tool-building instincts. He is actively seeking collaborations at the intersection of generative AI, safety/alignment, and temporal graph learning.
6 years of coding experience
5 years of employment as a software developer
Master's degree Artificial Intelligence, Master's degree Artificial Intelligence at Mila - Quebec Artificial Intelligence InstituteMaster's degree Computer Science, Master's degree Computer Science at Université de MontréalBachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Sharif University of Technology
English, Persian, French
Stackoverflow
11reputation
583reached
1answer
2questions
Github Skills (15)
python-course10
keras10
machine-learning10
jupyter-notebook10
lstm10
artificial-intelligence10
gru10
tensorflow10
python10
ai10
pytorch6
javascript6
regex6
react6
ubuntu6
Programming languages (3)
Github contributions (5)
SharifiZarchi/Introduction_to_Machine_Learning
Sep 2022 - Dec 2022
Machine Learning Course, Sharif University of Technology
Role in this project:
ML Engineer
ML EngineerContributions:15 commits, 10 pushes in 2 months
Contributions summary:Alireza's commits primarily involve modifying and adding content to a Jupyter Notebook related to sequence processing models, specifically LSTM, GRU, and bidirectional LSTM. The commits include changes to slides, images, and the addition of parameters, suggesting a focus on the practical application and explanation of these models for time series data, likely related to stock market data as inferred from the context. Furthermore, the commits are demonstrating the implementation of models to solve a real-world problem.
pythonmachine-learningdepartmentengineeringsharif-university
sudoparsa/OS-pintos
Mar 2022 - May 2022
Pintos - Operating Systems Group Project
Contributions:39 commits in 2 months
ce424operating-systemscs162operating-systemkernel-panic
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