I am a Master student at University of Massachusetts Amherts. I am broadly interested in Deep Learning and Machine Learning.

Description:

In this project, we investigate the performance of DL/ML on estrogen receptor enhancers. Specifically, we train the models to identify MegaTrans-containing enhancers. We are interested in understanding which features/DNA segments are most important for the models and if DL models can identify useful DNA motifs.

Method:

We train the models on classification and regression tasks. For classification, we train the models to predict between different classes of MegaTrans dataset. For regression, we train the model to predict the values of markers’ signals. After which, we analyze the models to extract which segments of DNA sequence that the models focus on the most.

Description:

The goal of this project is to develop a deep learning model to predict the progress of Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD). We are interested in the capability of Deep Learning models to distinguish between MCI and AD and whether they can predict the progress of MCI to AD.

Method:

From clinical features and PET images of MCI and AD patients, we want to extract features that best distinguish between MCI and AD using DL/ML. From these features, we find a dimension that best separates the two classes and map the data on this dimension. Our goal is to find some dimensions that can represent AD-MCI progressivity the best.

Description:

In this project, I want to analyze if the Transformers model can capture linguistic proximity: Is it easier for the models to translate between languages with similar properties/origins.

Method:

For this project, multiple models are trained to translate other languages to Vietnamese and their proximity are analyzed by measuring translation accuracy and other analysis.

Some of mine other skills include:

• Programming Languages: Java, C/C++, Python, Matlab
• Framework: Keras, TensorFlow, Pytorch