Anuj Dutt

Machine Learning Engineer at Adobe

Cupertino, California, United States
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Summary

👤
Senior
🎓
Top School
Anuj Dutt is a Machine Learning Engineer with 9 years of experience building efficient on-device AI and computer vision solutions for consumer and enterprise products. Currently at Adobe and previously leading AI systems at Jabra and deep learning research at Bose, he specializes in model compression, quantization, distillation, and hardware-aware NAS to deliver low-memory, real-time inference on edge devices. He has a strong engineering toolkit spanning C/C++, Python, TensorFlow/PyTorch, CoreML/TFLite, and cloud platforms, and has shipped mobile/on-device DNNs and patented innovations focused on privacy-preserving and resource-constrained deployments. Based in Cupertino, he also advises UC Irvine’s Customer Experience Program and contributes to practical ML projects like symptom-based disease prediction, reflecting a blend of research, product delivery, and data-focused experimentation.
code10 years of coding experience
job4 years of employment as a software developer
bookC++ Nanodegree, Computer Science, C++ Nanodegree, Computer Science at Udacity
bookDecentralized AI Applications using Blockchain, Decentralized AI Applications using Blockchain at Theschool.ai
bookMaster of Science (MS), Computer Engineering, Master of Science (MS), Computer Engineering at University of Florida
bookStanford LEAD Professional Certificate, Executive Education, Stanford LEAD Professional Certificate, Executive Education at Stanford University Graduate School of Business
bookBachelor of Technology (B.Tech.), Electrical, Electronics and Communications Engineering, Bachelor of Technology (B.Tech.), Electrical, Electronics and Communications Engineering at Kurukshetra University
languagesEnglish, Hindi, Punjabi
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Github Skills (6)

scikit10
pandas10
machine-learning10
python10
numpy10
scikit-learn10

Programming languages (10)

TypeScriptC++ShellCSCSSJavaScriptHTMLSwift

Github contributions (5)

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Disease Prediction based on Symptoms.
Role in this project:
userData Scientist
Contributions:29 commits, 3 PRs, 26 pushes in 4 years 5 months
Contributions summary:Anuj primarily worked on the project's data processing and model training. Their commits demonstrate data loading and cleaning within a Jupyter Notebook, suggesting an initial exploration and preprocessing of the dataset. The code modifications involve importing libraries like `pandas` and `numpy`, and applying data transformation techniques, which are crucial steps in preparing the data for machine learning. The user also cleaned the dataset.
pythonsymptomspredictionknn-classificationclassification-algorithm
anujdutt9/AI-Chatbot

Apr 2017 - Aug 2017

AI Chatbot using Dynamic Memory Network in Keras.
Contributions:2 commits, 1 push, 1 branch in 4 months
aichatbotkeraskeras-neural-networkspython-3-5
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