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
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.