Krishna Iyer

Analyzing quantum decoherence by modeling it

Started July 28, 2025

Abstract or project description

Quantum decoherence is the biggest barrier in widespread operational quantum computers, and the sources of it are many. The project will take data either from research, or computer generated on coherent quantum systems in lab. A modeling system will be chosen and a model of the system made in python. The data will be analyzed for characteristics, and compared to he model. Lastly, the model will be compared to textbook and perturbed models of analytic quantum solutions.

Identifying biomarkers in different demographics of Alzheimer patients

Started Mar. 4, 2024

Abstract or project description

The demographics of Alzheimer's patients have been greatly studied to better understand risk in different populations. For example, Alzheimer's is usually associated with patients above the age of 65 and twice as prevalent in women compared to men. While these studies help diagnose Alzheimer's, patients with Alzheimer's outside of typical patient demographics may be overlooked. Additionally, while the underlying causes of Alzheimer's is still currently unknown, the underlying pathology may differ in different patient populations. For example, patients with down syndrome are likelier to develop Alzheimer's in their 40s and 50s, a much younger age than the 65+ usually associated with Alzheimer's. As a result, it is important to identify more specific biomarkers for different patient populations. Using machine learning, this project focuses on exploring how feature importance varies in different patient populations leading to improved accuracy of Alzheimer's detection.