• Completed Basic Combat Training and Advanced Individual Training (AIT) with specialization in medical administration (MOS 68G)

• Trained in military discipline, leadership, patient records management, and healthcare operations support

• Gained experience in high-pressure environments, data accuracy, and mission readiness

• Construct and deploy machine learning solutions, enhancing the combined accuracy of ASR+NLU models from 70% to 99%.

• Establish a synthetic data pipeline for the language model, reducing data generation time from weeks to hours using a distributive computing approach.

• Build and maintain the end-to-end data collection workflow that allows fast-track data from annotator to model training and testing in a timely manner to prevent content drifting.

• Build gate-keeping golden test data for all models deployed in the speech org.

As the Student Volunteer Chair for Supercomputing Conference 2023 (SC23), my role is crucial in managing and supporting our team of student volunteers (~150). I'm responsible for recruiting and training these volunteers, ensuring they're well-prepared to assist in various aspects of the conference. My duties include organizing their schedules, assigning specific tasks, and being the primary point of contact for any issues or queries they might have. Additionally, I liaise with the conference organizers to integrate our volunteers seamlessly into the event. Post-conference, I also take care of recognizing the volunteers' contributions and gathering feedback to improve future events. My goal is to ensure a smooth and successful conference experience for everyone involved.

• Deliver training to developers and data scientists and facilitate research on using artificial intelligence and GPU-accelerated computing to solve real work problems across various domains.

• Recent course highlight: conversational AI workshop and NLP workshop

• Built drug-screening machine-learning models using human embryonic protein cocktails.

• Developed image segmentation ML model for H&E hi-re microscopic slides.

• Leaded project of therapeutical feature embedding through unsupervised learning.

• Built e2e data portal for data ingestion and visualization.