Director of Technology
2021 - PRESENTEmory University- Created a data science environment for the Quantitative Theory and Methods (QTM) department's new GPU server.
- Wrote and tested machine learning (ML) training scripts and built a hosted notebook solution supporting ML workflows. We already had nine active users from 18 faculties in the first month.
- Mentored four student researchers and two faculty advisors in partnership with UPS on using Google Cloud Platform for modeling and data engineering. The project led to UPS cutting costs and saving on labor.
- Progressed to director of technology after building a data science environment on AWS for two faculties and five researchers running large-scale linear job-matching models, ordered by CareerBuilder that wanted a transparent job matching model.
Technologies: Python, Bash, Jupyter, Neural Networks, NumPy, PyTorch, SQL, Pandas, Scikit-learn, R, Deep Neural Networks, Linux, AWS, AWS Cloud Education, Google Cloud, Machine Learning, Statistics, Data Science, Amazon SageMaker, Amazon Web Services (AWS)Lecturer
2017 - PRESENTEmory University- Recognized in 2020 by Google Education as one of thirty-four Google Cloud Faculty Experts. Selected in 2019 as one of eighteen AWS Academy Cloud Council Faculty, including members from MIT, Harvard, and Georgia Tech.
- Supervised research, including an honors thesis that trains Generative Adversarial Networks (GAN) models on a novel dataset. Unlike typical GAN applications, this model generates mathematical objects.
- Developed new techniques to overcome GAN problems such as mode collapse.
- Designed highly lauded data science classes, QTM 250 and 350. Led over 500 students in building ML models on AWS and Google Cloud Platform (GCP) from conception through deployment.
Technologies: PyTorch, TensorFlow, SQL, NumPy, Pandas, Scikit-learn, R, AWS, Google Cloud, Jupyter, Bash, Python, Neural Networks, Deep Neural Networks, Linux, AWS Cloud Education, Machine Learning, Statistics, Data Science, Amazon SageMaker, Amazon Web Services (AWS)Visiting Assistant Professor
2013 - 2017Emory University- Developed and managed multiple research projects, two of which delivered publications in high-ranking journals.
- Lectured as an invited speaker at scientific conferences in England, Germany, and the USA.
- Investigated the use of TensorFlow and deep learning on a classification problem in algebraic geometry. Ported code to TensorFlow, benchmarked models and presented this work at the Meeting on Applied Algebraic Geometry, GaTech, 2018.
- Led a team of three postdoctoral researchers in teaching Linear Algebra and Multivariable Calculus.
- Managed curriculum development and evaluation and was recognized for teaching excellence, progressing to Lecturer.
Technologies: TensorFlow, Deep Neural Networks, Linux, Mathematics, Jupyter, Bash, Python, Neural Networks, NumPy, Probability Theory, Markov Model, Data Science