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Nigel D

- Research Program Mentor

MS candidate at University of California San Diego (UCSD)

Expertise

machine learning, artificial intelligence, data science, data analytics, python programming, statistics

Bio

Hello potential mentees! I am a practicing Data Scientist with a particular interest in applying data analytic approaches to problem solving. These approaches can vary widely including building machine learning models to detect attacks on computer networks, using graph modeling to understand maritime vessel coordination, or simply creating interesting data visualizations to help further understand possible solutions to real world problems. My interests are wide ranging among the artificial intelligence and data science fields, but I am primarily focused on anomaly detection research problems at present. I live in San Diego and love to take advantage of the beautiful weather and outdoors we have here! I am passionate about bouldering, mountain biking, and hiking. I also enjoy reading in my free time, especially older sci-fi authors such as Isaac Asimov, Arthur C. Clarke, and Frank Herbert. Additionally, I enjoy watching the latest tv shows and love rewatching sitcoms such as Parks and Rec!

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Is this AI Model Fair?

There is a lot of excitement about machine learning models being used more commonly in daily life. However, the impacts of these models on marginalized groups are not well understood. In this project, the student can choose a machine learning model, or build one from scratch, and assess how fair the model's predictions are for different groups of the target population. The student can then write a research paper exploring their findings.

Where's Waldo? Using Machine Learning for Trajectory Anomaly Detection

In this project, the student will be focused on designing a typical machine learning approach to a problem. The student will identify a trajectory based dataset, such as vehicle traffic, animal movements, or anything that moves, and build machine learning anomaly detection models to identify possible anomalous movements. The student will learn about machine learning, experimental design, and some of the common barriers to creating good models. Finally, they will write a research paper documenting their findings.

Coding skills

python, R, java, HTML, javascript

Teaching experience

I have previously mentored interns as part of my job as a Data Scientist in industry. These mentorship experiences consisted of guiding community college students through a summer research project which I designed for them. The projects were centered around gaining familiarity with python, data analysis, and machine learning.

Credentials

Work experience

Naval Information Warfare Center Pacific (2021 - Current)
Data Scientist

Education

University of California San Diego (UCSD)
BS Bachelor of Science (2021)
Data Science
University of California San Diego (UCSD)
MS Master of Science candidate
Data Science with Specialization in Artificial Intelligence

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