Aadil Hayat
Senior Applied Scientist at Amazon
Bonn, North Rhine-Westphalia, United States
Summary
🤩
Rockstar🎓
Top SchoolAadil Hayat is a Senior Applied Scientist at Amazon with seven years of experience building production ML and data solutions, combining an MTech in Computer Science from IIT Kanpur with an aerospace engineering bachelor's background. He contributes to high-profile open-source AI projects such as Hugging Face Diffusers—adding Prompt2Prompt and ControlNet-XS support—and to DeFi/NFT data tooling by improving SQL views and pipelines for Dune’s spellbook. At Amazon he progressed from Applied Scientist I to Senior Applied Scientist, reflecting a track record of shipping robust models and data pipelines at scale. Based in Bonn, he pairs hands-on engineering with research-informed approaches and a knack for bridging data engineering and generative-model innovation.
7 years of coding experience
5 years of employment as a software developer
Indian Institute of Technology Kanpur12th PCM, 12th PCM at Delhi Public School Kalyanpur , Kanpur
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (23)
pytorch10
python10
data-warehouse10
testing10
diffusion-models10
stable-diffusion10
diffusers10
diffusion-probabilistic-models10
text2image10
data-transformation10
diffusion-probabilistic10
deep-learning10
image-generation10
f10
sql10
Programming languages (6)
Github contributions (5)
huggingface/diffusers
Jul 2023 - Dec 2024
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
Role in this project:
ML Engineer
ML EngineerContributions:80 reviews, 9 PRs, 158 comments in 1 year 5 months
Contributions summary:Aadil primarily contributed to the development and integration of a Prompt2Prompt pipeline, indicating involvement in advanced image generation techniques. They implemented new features, including the Prompt2Prompt pipeline, adding tests and documentation to support the new functionalities. The user also worked on ControlNet-XS support, and refined test collection, showcasing their ability to work with cutting-edge diffusion models for image generation.
pytorchartdeep-learningimage2imagestate-of-the-art
duneanalytics/spellbook
Oct 2022 - Jan 2023
SQL views for Dune
Role in this project:Data Engineer
Data EngineerContributions:4 reviews, 11 commits, 10 PRs in 3 months
Contributions summary:Aadil primarily contributes to data transformation and analysis within the `duneanalytics/spellbook` repository, which houses SQL views for Dune. Their work focuses on refining existing SQL queries for NFT data, specifically addressing issues related to token ID handling and data accuracy across various NFT platforms like OpenSea, Magic Eden, and Wombat. The user's contributions span creating new tables, updating existing ones, and integrating new data sources, reflecting a strong emphasis on data pipeline development and maintenance within the DeFi/NFT domain.
sqldatabasemysqldune
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