Sia Precision Education – Director of Recruitment

August 2021 – Current

• Leverage technical knowledge to interview potential employees for various roles within the organization, including software engineers and data scientists to develop software customized for incarcerated students
• Create various internship programs for undergraduate and graduate students
• Design and supervise all recruitment initiatives (i.e. LinkedIn, university outreach, etc.)

Research Intern – Summers Lab, NIH Clinical Center (Supervised by Dr. Ronald Summers)

June 2021 – August 2021

• Designed and implemented adversarial ResNet-18 architectures where the discriminator is trained to distinguish post-contrast images from synthetic scans meant to mimic specific tissue structures
• Successfully generated realistic synthetic data that was inseparable from real post-contrast images
• Implemented a pipeline for data preprocessing and synthetic data generation that will be used for dataset augmentation prior to pre-training large neural networks (e.g., vision transformer) for downstream tasks

NLP Research Assistant – Case Western Reserve University (Supervised by Yanfang Ye and Long Phan)

January 2021 – August 2021

• Developed CoTexT, a transformer model for multi-task learning on natural language and programming language data that achieved state-of-the-art results on the Microsoft xGLUE benchmark datasets
• Designed multiple learning objectives for self-supervised learning on both unimodal (only PL) and bimodal inputs (NL and PL)
• Modified encoder-only models (e.g., PhoBERT) to behave as a decoder block by changing self-attention layers from bidirectional into left-context-only and randomly initializing a cross-attention mechanism
• Developed the PhoBERT2PhoBERT and ViBERT2ViBERT encoder-decoder models and achieved state- of-the-art performances on summarization tasks (VietNews dataset)
• Developed SciFive, a transformer model for generative tasks in the biomedical domain (e.g., question- answering, summarization)

Volunteer Research Assistant – National Cancer Institute (Supervised by Dr. Grégoire Altan-Bonnet)

 December 2020 – June 2021

• Performed data collection and preprocessing in order to pre-train a transformer model on approximately 1-billion single-cells with different sets of features
• Assisted with design, testing, and validation of HAL-x, an extremely scalable hierarchical clustering algorithm that trains supervised classifiers to learn the hierarchy on raw, unprocessed data
• Achieved state-of-the art runtimes on datasets with >10 million data points (i.e., mass cytometry datasets)

Science Team Intern – Predictuv Technologies Inc., Austin, Texas (Supervised by D. Christopher Keil)

May 2019 – December 2019

• Assisted with mass data collection and data quality assurance to prepare training data for machine learning algorithms applied to image-driven sentiment analysis used in casino software
• Developed an LSTM-CNN for predicting emotions from facial movements in longitudinal imaging data
• Developed a detect-and-track program that predicts human action related to various sports (e.g., wide receivers running routes) to provide athletes with real-time feedback on technique/performance