SURE: Summer Undergraduate Research Experience

SURE offers insight and learning into some of the hottest topics in data science and computational mathematics through hands-on research experience. Learn to work as a team member by interacting with graduate students and faculty and gain an understanding of what it takes to conduct real-world research.

A ten-week SURE program will be hosted at Illinois Tech from May 22 to July 28. The program candidates will receive a stipend of $550 per week. The applicants are required to have a foundational background in mathematics (calculus, differential equations, and linear algebra) and some programming skills. If you have any questions regarding the program, please feel free to email yding2@iit.edu.

All applications received by March 15th will receive full consideration. Applications will be received until the positions are filled.

The SURE program is funded by National Science Foundation's Research Experience for Undergraduates (REU) program.

SURE 2023

Date	Time	Event	Location	Speaker
5/22	10:00-12:00 pm	Orientation/Kickoff Meeting	PS 111	Advisers
	12:00 -1:30 pm	Kickoff Lunch	RE A-Trim
	1:30 - 3:00 pm	IIT Tour
5/23	10:00-12:00 pm	PythonTutorial I	PS 111	Baoli Hao
5/24	10:00-12:00 pm	PythonTutorial II	PS 111	Baoli Hao
5/25	10:00-12:00 pm	Latex Tutorial	PS 111	Yuhan Ding
5/26	10:00-11:30 am	Project Selection/Group Meeting with Advisors	PS 111

Summer 2023 projects

Project Title: Speedier Simulations

Advisers: Sou-Cheng Choi and Fred Hickernell

Description: Monte Carlo methods are used to solve problems involving uncertainty, such as financial risk and geophysical problems whose parameters are not known precisely. The speedy simulations research group develops and implements algorithms in an open source Python package, called QMCPy that speeds up Monte Carlo simulations. Students will contribute to QMCPy by exploring new use cases, by implementing new algorithms, and/or by improving performance through parallel processing. By joining the speedy simulations research group, students will experience teamwork, learn to identify and solve research problems, follow good practices in technical software development, and hone their communication skills. A background in statistics and Python (or other language) programming will be an advantage.

Project Title: From the Formation of Snowflakes to Crystal Growth

Adviser: Shuwang Li

Description: Crystal growth is a classic example of a phase transformation from the liquid phase to the solid phase via heat transfer. For example, water becomes ice if heat is removed by decreasing the temperature. The solidification process is very important because material properties, such as electrical conductivity, mechanical ductility, and strength, are determined by the microstructures formed during phase transformations. Therefore, it is essential to know how crystals evolve during solidification and what kinds of geometric patterns they can form. As early as the 1600s, Johannes Kepler, a well-known astronomer, was amazed by the beauty of snowflakes and tried to understand this symmetry. While Kepler did not know about crystalline symmetry, he did have the insight that the symmetry of snowflakes (shown in the Figure) may be derived from a facultas for matrix (i.e. morphogenetic field or some inherent properties). In this project, students will learn the underlying physics of snowflake formation and evolution. In particular, students will be exposed to the general concepts of mathematical modeling and hands-on scientific computing.