Go to Polygence Scholars page
Milind Upadhyay's cover illustration
Polygence Scholar2022
Milind Upadhyay's profile

Milind Upadhyay

Mountain View High SchoolClass of 2023Mountain View, CALIFORNIA


Hi! I'm Milind and my project is on applying Quantum Machine Learning to Image Classification. I chose this project because I wanted to learn more about the cutting-edge field of Quantum Computing. After this project is complete, I would like to continue doing more research in Quantum Machine Learning, with more advanced applications.


  • "Quantum Machine Learning for Image Classification" with mentor Ina (Sept. 8, 2022)

Project Portfolio

Quantum Machine Learning for Image Classification

Started Apr. 7, 2022

Portfolio item's cover image

Abstract or project description

From self-driving cars to medical diagnoses, machine learning (ML) has revolutionized our world in the last few decades. Additionally, Quantum Computing has considerable promise for the future, with superposition and entanglement making quantum algorithms much more efficient and effective than their classical counterparts. Quantum ML aims to apply these quantum principles to the groundbreaking field of ML, such as for image classification. Convolutional Neural Networks (CNNs) are very effective for classification, so we study a Quantum Convolutional Neural Network (QCNN) that is trained to distinguish between handwritten numbers in the MNIST dataset and compared to a similar-sized classical network. After tuning the QCNN and quantum encoding, the QCNN achieved comparable accuracy to the classical network.