Shivaram Yellamilli
Data Scientist Focused on Machine Learning, Knowledge Discovery, and Changemaking
Experience
UC San Francisco, Biological Data Scientist November 2022 - Present
November 2022 - Present- Assisting in data processing and pipeline development for a larger collaboration
- Conducting initial exploratory analysis for a Pilot Project
Palo Alto Insight, Junior Data Scientist April 2021 - September 2022
April 2021 - September 2022- Developed customized ML solutions for clients in varied domains including time series analysis, object detection, and recommendation systems
- Conducted exploratory analysis and building solutions around findings
- Constructed data pipelines for multiple projects
Palo Alto Insight, Data Science Intern January 2021 - March 2021
January 2021 - March 2021- Built data pipelines and ML models for two different projects
Feather Health, Data Science Intern July 2020 - August 2020
July 2020 - August 2020- Performed in-depth exploratory analysis of time series feature detection
- Determined benchmarking protocol and developed associated Python package
Auransa, Data Science Intern January 2020 - June 2020
January 2020 - June 2020- Developed statistical analysis pipeline which is now being used for quality assurance analysis and knowledge discovery
- Benchmarked, debugged, and improved performance of core engine
Aspire Education Project, Academic Tutor October 2017 - December 2019
October 2017 - December 2019- Tutored high school and college students in computer science, mathematics, and physics
- Provided guidance and mentoring to high school students from disadvantaged backgrounds
Education
Georgia Institute of Technology 2021 - 2023
2021 - 2023 M.S. in Computer Science 3.75/4.00Concentration in Machine Learning 3.75/4.00
UC Berkeley 2015 - 2019
2015 - 2019 B.A. in Applied Mathematics 3.66/4.00Concentration in Quantum Computing 3.66/4.00
Skills
- Python
- SQL
- SQL
- Git
- AWS
- Databricks
- Docker
- LaTeX
- Numpy
- Scipy
- Pandas
- Matplotlib
- Seaborn
- Sklearn
- Gensim
- Pytorch
- Tensorflow
- Keras
- Seurat
- Developed CNN model capable of identifying the most common Hawaiian fish species with 80%+ accuracy and 90%+ top 3 accuracy
- Scraped google images using Selenium and filtered for relevant results utilizing a different custom CNN
- Built product to analyze forestry documents for World Resources Institute
- Led development of Topic Modeling aspect (using Latent Dirichlet Allocation)
- Independently investigated magnetic properties of ultra-thin amorphous films
- Developed code library for lab, streamlining data analysis process
- Built a sensor to detect false positive signals marked by Cherenkov Radiation in search of Neutrinoless Double Beta Decay
- Used ROOT data analysis framework to do preliminary data analysis
- Developed a more accurate model of the interior of Uranus using C++
- Coauthored a research paper on our findings
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