Chandan Dwivedi is a Senior Machine Learning Engineer with 10 years of experience building production-grade AI systems, currently focused on cybersecurity and fraud detection at Zupee. He blends deep learning, computer vision and graph technologies—moving systems from prototype to scalable deployment using PyTorch/TensorFlow, OpenCV, Flink, Kafka and AWS EKS. His recent work applies Graph Neural Networks to multi-accounting and community-detection problems, having already integrated GraphDBs like Neptune and Neo4j into real-time pipelines. Earlier roles span edge AI (face recognition on SOCs), AR/C++ performance engineering, and end-to-end ML productization for e-gaming and healthcare platforms. Comfortable across Python, C++ and embedded devices (Raspberry Pi hobbyist-level fluency), he combines hands-on optimization with CI/CD and Kubeflow-driven deployments. Based in Gurugram, he pairs a solid NIT computer science background with a practical knack for squeezing performance out of constrained systems.
10 years of coding experience
4 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Motilal Nehru National Institute Of Technology
High School, High School at jawahar navodaya vidyalaya
Intermediate, Mathematics, Intermediate, Mathematics at Little flower house
Traffic Sign Classification using Deep Learning. The model architecture is LeNet based Convolutional Neural Network using tensorflow framework, inspired from Udacity's self driving car project.
Contributions:29 commits, 2 PRs, 28 pushes in 1 year 7 months
Contributions:33 pushes, 3 branches, 2 issues in 2 years 8 months
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Chandan Dwivedi - Senior Machine Learning Engineer at Zupee