Rishit Dagli
Research Intern at NVIDIA
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolRishit Dagli is a machine learning and computer vision researcher and University of Toronto CS undergrad with eight years of experience contributing to both industry research programs and open-source ML documentation. He has held research internships at NVIDIA and Qualcomm and worked on vision, robotics, graphics, and video understanding projects, while also contributing ML examples and advanced models (e.g., Swin Transformer, contrastive learning) to the Keras ecosystem. At Civo he focused on inference optimization, and his technical writing on the Kubernetes website shows attention to clarity and cross-audience communication. Comfortable bridging research and engineering, he combines academic rigor from UofT and selective programs (Stanford summer, JWST student program) with practical contributions that make complex deep-learning techniques accessible.
8 years of coding experience
High School, High School at Narayana SchoolMathematics, Mathematics at Raising a Mathematician FoundationComputer Science, Computer Science at University of TorontoSummer School, Computer Science, Summer School, Computer Science at Stanford University
English, Hindi, Gujarati
Stackoverflow
998reputation
58kreached
59answers
5questions
Github Skills (21)
kubernetes10
python10
image-classification10
machine-learning10
keras10
deep-learning10
tensorflow10
kubernetes-pods10
html10
computer-vision10
data-augmentation10
documentation10
transformers9
content-management-system9
self-supervised-learning9
Programming languages (21)
Github contributions (5)
kubernetes/website
May 2022 - Oct 2022
Kubernetes website and documentation repo:
Role in this project:
Technical Writer
Technical WriterContributions:1 release, 74 reviews, 25 commits in 4 months
Contributions summary:Rishit primarily contributed to the Kubernetes website documentation. Their work included correcting references, removing outdated warnings, and merging content from different branches. The changes involved editing HTML files, updating documentation structure, and making language-specific adjustments. The commits demonstrate a focus on maintaining the clarity and accuracy of the documentation.
kubernetes
keras-team/keras-io
Jun 2021 - Sep 2021
Keras documentation, hosted live at keras.io
Role in this project:ML Engineer
ML EngineerContributions:41 reviews, 5 commits, 5 PRs in 3 months
Contributions summary:Rishit primarily contributes to implementing and documenting machine-learning examples within the Keras framework. Their work includes building a Gradient Centralization example, introducing a Swin Transformer model for image classification, and creating an example for self-supervised contrastive learning with NNCLR. These contributions involve coding model architectures, data preparation, and model training, demonstrating a focus on applying and explaining advanced deep-learning techniques within the Keras ecosystem.
keras
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