Ajla Sacic

My name is Ajla Šačić and I am a Senior studying Computer Science and Applied Maths at NYUAD. I was born and raised in Sarajevo, Bosnia and Herzegovina. My main interests are Quantum Computing and Machine Learning with a special focus on Quantum Error Mitigation and Correction and the intersection of Classical Machine Learning with Quantum Computing. Due to my interest in both fields, my capstone project at NYUAD in the Quantum Exploration Lab will delve into the optimization of Clifford Data Regression (CDR) for NISQ Quantum Computers.

During the summers of 2024 I started working on "Deep Learning for DNP: Predictive Models for Enhanced MRI and NMR Performance". Dynamic Nuclear Polarization (DNP) is a transformative technique utilized to enhance the sensitivity and contrast of Magnetic Resonance Imaging (MRI) and Nuclear Magnetic Resonance (NMR) spectroscopy. However, the efficiency of DNP is highly dependent on a multitude of factors, necessitating a predictive model to optimize experimental setups for maximal sensitivity improvements. This research investigates the predictive capabilities of three neural network-based solutions, two TabNet and one Fully Connected Neural Network implementation, to forecast DNP enhancement. Each model was evaluated using two data preparation methods, matrix and tabular data, to determine the most effective approach. The comparative results showed that PyTorch TabNet implementation performs the best, exhibiting an improvement by half an order of magnitude. The project has not reached its completion yet, hence I will continue to work on it even after the summers.