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Tutorial: Julia for Scientific Machine Learning

October 25, 2022

10:00 am - 12:00 pm

Steven Chiu
Ph.D. Student
Department of Electrical and Computer Engineering

Background and Objectives

Julia ( is a generic programming language designed for high-performance computing. It solves the “two language problem” of scientific computing. Julia is dynamically typed like scripting language such as Python and can be compiled into native machine code. Besides, composability via multiple dispatches makes Julia ideal for integration across packages. SciML ( is an open-source software for scientific machine learning based on the Julia language that combines machine learning and scientific computing by integrating numerous standalone packages. Julia is an open-source project under an MIT license.

This tutorial aims to introduce the participants to the potential of Julia in the Scientific Machine Learning field. First, we will give an introductory overview of the Julia programming language, and then explore the Julia SciML ecosystem for SciML. The second part of the tutorial will explore in detail applications of Julia to neural differential equations and modeling of infectious disease transmission. Both parts will include presentations and hands-on sessions. Prior knowledge of Python is recommended, and participants are encouraged to bring their laptops.


10:00 AM – 10:25 AMIntroduction to the Julia programming language
10:30 AM – 11:00 AMThe Julia SciML ecosystem
11:00 AM – 11:10 AMBreak
11:10 AM – 12:00 PMHands-on session with neural differential equations/infectious disease model


Steven Shao-Ting Chiu is a Ph.D. Student in the Department of Electrical and Computer Engineering, where his research advisor is Ulisses Braga-Neto. Previously, he was with Pumas-AI, working in the application of Julia to pharmaceutics and personalized medicine applications, under the supervision of Chris Rackauckas. He received both bachelor’s and master’s degrees at the Department of Electrical Engineering of National Taiwan University, with a specialization in physical modeling/simulation of biological systems. He is the recipient of a prestigious Texas A&M ECE Department Graduate Fellowship.