Mohammed Suhail
Senior ML Researcher at RBC Borealis
Vancouver, British Columbia, Canada
Summary
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Senior🎓
Top SchoolMohammed Suhail is a Senior ML Researcher and PhD candidate at UBC, affiliated with Vector Institute, with 11 years of experience building and shipping research-driven machine learning systems. His work spans graph neural networks, attention mechanisms, generative models, few-shot learning and probabilistic programming, with a focus on situation recognition and graph generation. He has held research roles at Google (including contributions to high-profile Google Research projects like light field and patch-based neural rendering) and RBC Borealis, moving models from prototype to code releases. Mohammed combines deep academic training with practical engineering—implementing transformers, projectors and feature extractors in production-oriented repositories—and has a track record of internships and collaborations across academia and industry. Based in Vancouver, he blends rigorous PhD research with hands-on model development that targets real-world applications.
11 years of coding experience
7 years of employment as a software developer
Bachelor’s Degree, Electrical and Electronics Engineering, Bachelor’s Degree, Electrical and Electronics Engineering at Indian Institute of Technology, GuwahatiDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of British Columbia
English, Malayalam, Hindi
Github Skills (7)
transformer-models10
machine-learning10
jax10
python10
flax10
computer-vision9
pytorch8
Programming languages (4)
Github contributions (5)
google-research/google-research
Dec 2021 - Aug 2022
Google Research
Role in this project:
ML Engineer
ML EngineerContributions:5 commits in 7 months
Contributions summary:Mohammed contributed to the Light Field Neural Rendering and Generalizable Patch-Based Neural Rendering projects within the Google Research repository. Their commits involved code releases and updates to model configurations and documentation. The user implemented and modified core model components, including transformers, projectors, and feature extraction layers, indicating an involvement in the model development process.
googlemachine-learningai
mods333/energy-based-scene-graph
Jun 2020 - Apr 2022
Code release for Energy-Based Learning for Scene Graph Genertaion
Contributions:82 commits, 1 PR, 4 pushes in 1 year 10 months
graph-neural-networksscenegraphscene-graphenergy
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