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
Jeremy Jacobson
Data Scientist and Developer in Atlanta, GA, United States
Member since December 13, 2021
Jeremy is a versatile data scientist with six years of experience that includes leading machine learning research projects and managing department teams. He has built data science and ML solutions used by faculty and external partners such as CareerBuilder and UPS. He was recognized by Google Education as a Google Cloud Faculty Expert and selected to the AWS Academy Cloud Council Faculty. Adept at picking up new skills quickly, Jeremy is committed to freelancing excellence.
Jeremy is now available for hire
Portfolio
- Emory UniversityPython, Bash, Jupyter, Neural Networks, NumPy, PyTorch, SQL, Pandas...
- Emory UniversityPyTorch, TensorFlow, SQL, NumPy, Pandas, Scikit-learn, R, AWS, Google Cloud...
- Emory UniversityTensorFlow, Deep Neural Networks, Linux, Mathematics, Jupyter, Bash, Python...
Experience
- Mathematics 9 years
- Statistics 6 years
- SQL 6 years
- Data Science 6 years
- Machine Learning 6 years
- AWS 6 years
- Google Cloud 6 years
- Python 6 years
Availability
Part-time
Preferred Environment
Jupyter Notebook
The most amazing...
...thing I've worked is a GAN model that generates elliptic curves. It required new techniques for overcoming mode collapse.
Employment
Experience
- Counting Real Roots Using Neural Networkshttps://github.com/jeremyallenjacobson/RealRootsReproduction
In a .ipynb notebook file in the GitHub repository, I explain how to reproduce results on Google's Cloud platform, demonstrating how to use neural networks to count the number of real solutions to polynomial systems.
For details, see the slides available at http://slides.com/jeremyjacobson/deep-learning. They are from an informal talk I gave as a part of the QTM chalk talk series. - Roman Urdu NLPhttps://github.com/jeremyallenjacobson/roman-urdu-nlp
A sentiment classifier that maximizes accuracy to provide a clear window into the social media conversations of the corporation's customer base. See the notebook (.ipynb file) in the included repo for details.
Skills
Tools
Amazon SageMaker, JupyterParadigms
Data ScienceOther
Mathematics, AWS Cloud Education, Statistics, Machine Learning, Deep Neural Networks, AWSLanguages
Python, Bash, SQL, RLibraries/APIs
NumPy, PyTorch, TensorFlow, Pandas, Scikit-learnPlatforms
Amazon Web Services (AWS), Linux, Jupyter NotebookStorage
Google Cloud
Education
- PhD in Mathematics and Computer Science2006 - 2012Louisiana State University - Baton Rouge, LA, USA
- Bachelor's Degree in Mathematics and Computer Science2001 - 2005University of Wisconsin – Madison - Madison, WI, USA
Certifications
- Google Cloud Faculty ExpertFEBRUARY 2020 - PRESENTGoogle Cloud Education
- AWS Certified Cloud PractitionerAUGUST 2019 - AUGUST 2022Amazon Web Services
- AWS Academy Accredited EducatorMARCH 2019 - PRESENTAmazon Web Services
