Dylan Bragdon

951-***-**** -- adhs9h@r.postjobfree.com -- https://www.linkedin.com/in/dylan-bragdon-757332184/ Summary

I am fascinated by the human ability to model the natural world using past data and statistical methods. I am working following a career in machine learning/data science, in hopes of applying my skills to as many fields as possible. I would love to apply all of my knowledge to working with full-stack machine learning development in any field.

Professional History

- Data Science/Natural Language Processing Fellow

- United States Census Bureau

- Optimized information extraction of user-feedback for data.census.gov, the Census Bureau’s website for accessing census data

- Created Sentiment Analysis models and topic models for identifying user-frustration and classifying points of feedback instantly

Education

- University of California, San Diego

- B.S. In Cognitive Science with Specialization in Machine Learning and Neural Computation

- Minor in Mathematics

Conferences

- Census Bureau Natural Language Processing Affinity Group

- Co-chair

- Helped organize presentations of current projects involving NLP at the U.S. Census Bureau

- Keynote speaker for NLP/Data Science work in optimization of user-feedback extraction Projects

- Predicting Parkinson’s Disease Using Support Vector Machines and Principal Component Analysis

- https://github.com/dbragdon1/Parkinson-s-Disease-Prediction

- Predicting and Visualizing Hate Speech in Online Communities Using Gated Recurrent Units

- https://github.com/dbragdon1/Hate-Speech-Detection

- Sentiment Classification on the Yelp Dataset

- https://github.com/dbragdon1/NLP-CompLing-Projects/blob/master/Sentiment%20Classification.i pynb

- Implementing Porter’s Algorithm for Stemming English Words

- https://github.com/dbragdon1/NLP-CompLing-Projects/blob/master/Porter's%20Algorithm.ipynb

- Using Predictive Modeling to Classify Protein Localization Sites in E. coli (Poster)

- https://github.com/dbragdon1/Ecoli-Protein-Localization

- Self-Solving Rubik's Cube Robot, Computational-to-Physical Design Team Leader

- Used Open-CV for cube face-scanning technology

- Configured on Raspberry Pi with LINUX terminal

- Re-Implementing Google Brain’s “Attention Is All You Need” Paper for Seq2Seq Learning.

- https://github.com/dbragdon1/Transformer

- Implementing IBM Translation Models 1 and 2

- https://github.com/dbragdon1/IBM-Models-1-and-2

Dylan Bragdon

951-***-**** -- adhs9h@r.postjobfree.com -- https://www.linkedin.com/in/dylan-bragdon-757332184/ Internships

- Machine Learning/NLP Intern: Advanced Continuing Education Association (January 2020 - June 2020)

- Applying Statistical NLP to user data to create recommender system for customers

- Creating Web APIs with Python backend using Flask Research

- “Array Sensor Localization Using Extended Toeplitz Sets”, IEEE, Noise Lab @UCSD, in progress. Teaching Positions

- Instructional Assistant for COGS 109 (Data Modeling and Analysis)

- Taught students Python for Data Science

- Held section/office hours to help students

- Created homework assignments

- Helped students solve problems regarding data science and data modeling problems Relevant Coursework

- Supervised Machine Learning Algorithms (COGS 118A)

- Deep Learning and Neural Networks (COGS 181)

- Deep Learning and Natural Language Processing (LIGN 167)

- Statistical NLP (CSE 156)

- Recommender Systems (CSE 158)

- Data Modeling and Analysis (COGS 109)

- Introduction to Numerical Optimization/Linear Programming (MATH 171A)

- Exploratory Data Analysis & Inference (MATH 189)

- Introduction to Probability (MATH 180A)

- Introduction to Numerical Analysis (MATH 170A)

Skills

- Python (4+ years)

- Building NLP-Based Recommender Systems

- Deep Learning in Python w/ Pytorch and Tensorflow

- Data modeling experience in Python, MATLAB and R

- Linear optimization experience in Julia

- Clojure (LISP) Programming Experience for Computational Linguistics

- UNIX Command Line Experience

- Full Stack Deep Learning Experience

- Group project leadership experience, in both class and extracurricular projects References

- Leon Bergen

Assistant Professor, Department of Linguistics

Relationship: Professor, Deep Learning and Natural Language Processing (LIGN 167) Email: adhs9h@r.postjobfree.com

Phone: 858-***-****

- Mark Wagner

Graduate Student, NoiseLab@UCSD

Relationship: Research Supervisor

Email: adhs9h@r.postjobfree.com

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