College of Computing

SURE: Summer Undergraduate Research Experience

Spend the summer with a computer science or applied mathematics research team in a College of Computing Summer Undergraduate Research Experience (SURE) program.

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 to gain an understanding of what it takes to conduct real-world research.

A 10-week SURE program will be hosted at Illinois Tech from May 28 to August 2, 2024. Program candidates will receive a stipend of $550 per week. Applicants are required to have a foundational background in mathematics (calculus, differential equations, and linear algebra) and some programming skills. If you are interested in the program, please use this form to apply. If you have any questions regarding the program, please email yding2@iit.edu.

All applications received by January 31, 2024, will be fully considered. Applications will be accepted until the positions are filled.

The SURE program gratefully acknowledges the funding by the National Science Foundation.

More detailed project information will be released soon. Please find the projects and schedule for 2023 below.

National Science Foundation Logo

SURE 2023

 

Date

Time

Event

Location

Speaker

Week 1

5/22

10:00-12:00 pm

Orientation/Kickoff Meeting

PS 111

 

12:00 - 2:00 pm

Kickoff Lunch

RE A-Trim

 

2:00 - 3:00 pm

IIT Tour

  

5/23

10:00-12:00 pm

Python Tutorial I

PS 111

Baoli Hao

5/24

10:00-12:00 pm

Python Tutorial 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

 

Week 2

5/30

10:00-12:00 pm

Intro to Computational Math

PS 111

Shuwang Li

5/31

10:00- 12:00 pm

Intro to Data Science

PS 111

Yuhan Ding

6/1

10:00-12:00 pm

Workshop on Title IX

Online

Virginia Foster

6/2

10:00-11:00 am

Research Experience Sharing

PS 111

Claude Hall

11:00-12:00 pm

Warm-up Quiz Q&A Session

PS 111

Advisers

6/3-6/4

 

2023 IDEAL Get Ready for Research Workshop

UIC

Optional

Week 3

6/5-6/7

 

PETSc Meeting

HH Ballroom

Optional

6/9

10:00-11:30 am

How to Conduct Research

PS 111

Trevor Leslie

2:00-3:30 pm

Weekly Report/Presentation

PS 111

SURE Fellows (15-20 minutes/group)

Week 4

6/16

10:00-11:30 am

Research Experience Sharing

PS 111

Onyekachi Oluseyi

Week 5

6/23

10:00-12:00 pm

Midterm Presentation

PS 111

SURE Fellows (30 minutes/group)

12:00 - 1:00 pm

Midterm Presentation Lunch

RE A-Trim

 

 

Week 6

6/30

10:00-11:00 am

Career Experience Sharing

PS 111

Martha Razo

11:00-12:00 pm

Communication with Speaker

PS 111

 

Week 7

7/7

10:00-11:00 am

Career Experience Sharing

Online

Julienne Kabre

11:00-12:30 pm

Weekly Report/Presentation

PS 111

SURE Fellows (20-30 minutes/group)

7:10 PM

White Sox Game

Guaranteed Rate Field

 

Week 8

7/11

10:00-11:30 am

How to Become A Data Scientist/Introduction to SAS Hackathon

PS 111

Sou-Cheng Choi/Narges Hosseinzadeh

7/12

8:30-11:30 am

Field Trip at SAS Inc.

  

7/14

10:00-12:00 pm

Resume Writing/Cover Letter Prep/LinkedIn with Q&A

PS 111

Bernie (career coach)

Week 9

7/18

10::00-12:00 pm

Career Exploration and Self-Assessments, with Q&A

PS 111

Julie Bruns (career coach)

7/20

1:30-3:30 pm

Field Trip at Argonne National Lab

  

7/21

10:00-11:00 am

Career Experience Sharing

PS 111

Anita Thomas

Week 10

7/28

10:00-12:00 am

Final Presentation

PS 111

SURE Fellows (30 minutes/group)

12:00-1:00 pm

Reception/Poster Presentation

RE Atrium

SURE Fellows (30 minutes/group)

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.

Project Title: Learning and Modeling Collective Behaviors

Advisers: Yubin Lu, Ming Zhong, and Trevor Lesilie

Guest Speakers: James Greene (Clarkson University), Siming He (University of South Carolina).

Description: Collective behaviors (aka Self Organization) are ubiquitous in nature. They can be used to explain interesting patterns such as crystal formation, bird flocking, fish milling, locust swarm, cell aggregation, etc.  These behaviors are the emergence of global patterns from initially random configurations through only local interactions.  They can be explained using dynamical systems, and yet they present a challenging task to model properly using mathematics.  The proper modeling of such behaviors has a great number of applications in Physics, Biology, Chemistry, Medicine, and Social Sciences.  We will learn how to model collective behaviors with the help of proper machine-learning tools and possibly validate the learning method on experimental data.

Prerequisite: Cal 1, 2, 3 and Linear Algebra, some numerical methods, some programming experience.

Modeling Collective Behaviors
Modeling Collective Behaviors

Project Title: Trustworthy Artificial Intelligence (AI)

Advisers: Binghui Wang and Ren Wang

A collaborative project (Trustworthy AI) will also be hosted at Illinois Tech from May 22 to July 28. Candidates will receive a stipend of $550 per week. The applicants are required to have linear algebra, probability and statistics, and some programming skills. All applications received by April 20 will receive full consideration. Please apply here.

Project Description: Trustworthy artificial intelligence (AI) is essential for ensuring that AI systems are safe, secure, and transparent, and can be relied upon to make decisions that are fair, unbiased, and ethical. With the increasing use of AI in various applications, including healthcare, finance, and transportation, it is crucial to develop trustworthy AI systems that are reliable, robust, and preserve privacy to protect users' interests and prevent potential harm. This undergraduate research project focuses on developing trustworthy AI through robustness and privacy. Students in this project will investigate the robustness of different machine learning algorithms against various types of attacks. Students will also evaluate privacy-preserving techniques and assess the trade-offs between robustness and privacy-preserving techniques in machine learning.

Topic: Scaling Education with OpenAI Language Models

Adviser: Lance Fortnow

Project Description: This project will use generative AI tools such as ChatGPT to create a virtual tutor that can help our students understand mathematical concepts related to high school and college pre-calc and introductory college courses. These systems will supplement our other support channels to help our students do well in our introductory math courses.

A collaborative project (Trustworthy AI) will also be hosted at Illinois Tech from May 22 to July 28. Candidates will receive a stipend of $550 per week. 

SURE Programs Summer 2023

College of Computing

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