I am a computational neuroscientist with a passion for using data science techniques to study the brain and its diseases. I have experience in Python, R, and statistics, and I am always looking for new challenges and opportunities to apply my skills.
- Python: I have experience in using Python for data analysis, machine learning, and scientific computing. I am proficient in libraries such as NumPy, Pandas, Tensorflow, and Scikit-learn.
- R: I have experience in using R for data analysis, visualization, and statistical modeling. I am proficient in packages such as ggplot2, dplyr, and lme4.
- Statistics: I have a strong background in statistics, with a focus on statistical modeling, hypothesis testing, and data analysis. I have experience in using statistical methods for neuroscience research.
A selection of projects.
Project | Description | Implementation | Dataset | Date |
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Alzheimer's Disease Pathology (IDSC Fellowship) | Utilization of supervised and unsupervised machine learning for Alzheimer's Disease research. Launch Event & Capstone Presentation | Python | Neuropathology dataset | 05/2022 |
Blood Biomarker Assessment | I developed a machine learning models to determine the importanace of blood biomarkers following traumatic brain injury. I used Python and Scikit-learn to preprocess the data, train the model, and evaluate its performance. | Python | Blood Antibody dataset | 02/2019 |
Project | Description | Implementation | Dataset | Date |
---|---|---|---|---|
Stock Samurai | I developed a WebApp to visualize stock market data. Includes sustainability measures, stock charts with bollinger bands, and investment bank recommendations. | Python, HTML, Markdown | Stock Financial data | 11/2022 |
Project | Description | Implementation | Dataset | Date |
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Digital Biomarker Generation and Analysis | I developed an app to record stimulus and self paced movements and performed pattern analysis to generate digital biomarkers for Parkinson's disease. I used java to create the front end and back end of the android app and Matlab and Python to analyze the data and evaluate scientific significance. | Java & Matlab | App generated data | 06/2018 |
- Software Carpentry Instructor (October 2022 - python, bash, git)
- Applied Machine Learning in Python (May 2019 - University of Michigan - Kevyn Collins-Thompson - Coursera)
- E-mail: [email protected]