Vi K. Ly, Ph.D. Email & Phone Number

Houston, Tx, Us

• Developed data cleaning pipeline and perform analytics and visualization of the data.• Integrated statistical methods, machine learning models and state-of-the-art deep learning models in an interactive dashboard application.• Produced efficient and reproducible code with clarity in a peer-reviewed environment following the company’s MLOps and DevOps guideline.• Presented the results to both technical and non-technical stakeholders in project meetings.

Multimodal of vision and language for the task of object detection from voice command given to a vehicle.

Houston, Texas, United States

Research Topics: “Parametric contrast-based model for delineated uncertainties contouring of organs in cervix region”• Project is partially funded by Varian Medical Systems• Extracted and prepared the raw CT scan data.• Built a Variational Autoencoders (VAE) and Conditional GAN model for uncertainty contouring• Export edthe final DU contours and deploy it the Raystation system for evaluation. • Design blind review session with clinicians to collect the clinical usability scores for quantitative analysis.

San Francisco Bay Area

Topic: Facial Emotion Recognition (FER)Summary:Using computer vision and deep learning methods for the task of user-engagement analysis on live video stream.

Houston, Texas Area

• Collaborated with database managers, data analysts, physicians and senior researchers in the team to tackle challenging research problems.• Extracted and cleaned an EHR dataset of 3.6 millions diabetes patients from Cerner database. • Developed a novel hybrid phenotyping method from existing rule-based and machine learning algorithms.• Assisted the research team on writing several chapters in a published EHR analysis book.

Houston, Texas Area

Research topic: “Developing a Search Engine for Precision Medicine” • Final paper is accepted for publication at AMIA Conference.• Developed machine learning and learning-to-rank components of the search engine. This search engine is evntually developed into front-facing website allows for easy access to oncologists.• Tools used: SQL; Caret package in R; Keras, Tensorflow, Scikit-learn, Numpy and Pandas in Python.

Houston, Texas Area

Research topic: “Accurate prediction of boundaries of high resolution topologically associated domains (TADs) in fruit flies using deep learning.”· Conducted bioinformatics research project using machine learning methods with R & Python platforms.· Performed a quantitative study on genetic motif prediction in the chromosome boundaries of fruit fly.· The research was chosen to be presented at 30th HENAAC Conference in Pasadena, California.· Our paper was published on Nucleic Acids Research journal.

Houston, Texas Area

Research topic: "Deep Neural Network Learning of Video Stream for Elderly Fall Detection".• Provided research support for a project integrating novel statistical computing tools like Julia and Python with deep learning methods. • Effort resulted in a video-classification model that predicts human actions with more than 80% accuracy. The research’s outcome was chosen to be presented in the Gulf Coast Undergraduate Research Symposium (GCURS) hosted by Rice University

Doctor Of Philosophy - Phd, Biostatistics

Activities and Societies: Recognitions: Julius and Suzan Glickman Endowned Scholarship in Innovation

Bachelor In Data Science, With Minor In Healthcare, Mathematics And Statistics, 3.86

Activities and Societies: Recipient of Scholars Academy Merit scholarship. Member of National Society of Leadership and Success.• GPA.