UROP Project

Scientific Machine Learning with Julia

Coding; Computation; Machine Learning;

Research Mentor: Raghav Gnanasambandam,
Department, College, Affiliation: Industrial and Manufacturing Engineering, FAMU-FSU College of Engineering
Contact Email: raghavg@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: FAMU-FSU College of Engineering/Online
Research Assistant Transportation Required: Bus
Remote or In-person: Partially Remote
Approximate Weekly Hours: 6 hrs, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

This research aims to understand the advantages of the computer programming language Julia in scientific machine learning. Python is the go-to programming language for most scientific machine learning work. Julia, a relatively new programming language, shows promise in achieving faster speeds than Python. The project will utilize a pre-existing Python code related to Physics Informed Neural Networks and convert it to Julia to analyze the advantages and disadvantages.

Research Tasks: 1. Understand the basic syntax of Python and Julia.
2. Compare the speed of simple problems (loops, matrix multiplications, and matrix inversions) between both languages.
3. Understand basics of Physics-Informed Neural Networks.
4. Convert a pre-existing Python code to Julia.
5. Compare the speed and accuracy.

Skills that research assistant(s) may need: Some knowledge of calculus (required)
Some familiarity with coding (recommended).