Ankur Shukla is a Lead Data Scientist with nine years of experience building scalable ML systems for quick commerce, retail, manufacturing and pharma, currently driving end-to-end AI across Blinkit’s supply chain and consumer apps. He has delivered production demand-forecasting pipelines, location-intelligence for better delivery SLAs, and rider-focused recommendation engines that directly impact operations and earnings. His background blends deep learning, computer vision and NLP with strong engineering instincts—evidenced by core back-end contributions to the pgRouting library improving Dijkstra implementations and turn-restriction logic. Trained at IIT Bombay (CSRE) and a Udacity deep learning alumnus, he has moved from research and teaching in satellite image processing to production ML at scale. Outside data science he builds React Native apps tailored to Indian users, including a Hindu scriptural reader and a Hanuman Chalisa app in development, reflecting a habit of shipping user-facing software. Practical, product-minded and cross-disciplinary, he combines algorithmic rigor with hands-on engineering to translate complex data problems into measurable business outcomes.
9 years of coding experience
7 years of employment as a software developer
Intermediate Science, Intermediate Science at Vidyatree Modern World College
Indian Institute of Technology Bombay
Deep Learning Nanodegree Artificial Intelligence, Deep Learning Nanodegree Artificial Intelligence at Udacity
Bachelor of Technology (B.Tech.) Electrical Engineering, Bachelor of Technology (B.Tech.) Electrical Engineering at Kamla Nehru Institute of Technology, Sultanpur
Repository contains pgRouting library. Development branch is "develop", stable branch is "master"
Role in this project:
Back-end Developer
Contributions:62 commits, 24 PRs, 6 pushes in 3 months
Contributions summary:Ankur primarily contributed to the `pgrouting` library, focusing on improving the `GraphDefinition` class and the Dijkstra's algorithm implementation. Their work involved fixing bugs, refactoring code, and optimizing loops to improve performance. They also added features related to turn restriction, and refactored code to incorporate range-based for loops. The contributions are within the core routing logic of the library.
Contributions:110 commits, 26 PRs, 73 pushes in 3 months
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