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.

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

National Science Foundation Logo

Summer 2024 projects

Topic:  Speedier Simulations

Advisers: 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.

Topic:  Baseball Game Simulation

This is a collaborative project with the Chicago White Sox. 

Advisers: Matt Koeing and Yuhan Ding

Descriptions: Take in two rosters, starting lineups, statistical data, and the rules of a baseball game to create a game simulator to predict the final score and statistics of a game. This simulator will simulate each at bat of a game using the present situation, players, and rules to predict the outcome. This tool could be used to test out the performance of different lineups, predict a season, or to predict a certain outcome.

Topic:  Machine Learning for Traffic Accident Prediction 

 

Advisers: Huiling Liao 

Descriptions: Controlling traffic accidents is an important public safety challenge, therefore, accident prediction has been a topic of much research. With a large-scale but sparse publicly available dataset including a variety of data attributes such as traffic events and weather data, we try to tackle the traffic accident prediction through modeling the nonlinear evolution of spatio-temporal patterns. In this study, students will work together, starting from identifying research problems to coming up with a solution, to explore different spatio-temporal models and also learn to model the patterns and predict the occurrence and severity of accidents with the proper machine learning tools.

Summer 2024 Schedule 

 

Date

Time

Event

Location

Speaker

Week 1

5/28

10:00-12:00 pm

Orientation/Kickoff Meeting

PS 111

 

12:00 - 2:00 pm

Kickoff Lunch

RE Atrium

 

2:00 - 3:00 pm

IIT Tour/HR Office Visit

PS 111

 

5/29

10:00-12:00 pm

Research Integrity

PS 111

Charles W. Uth

5/30

10:00-12:00 pm

Individualizing Biomechanical Models – How the White Sox Tune Their Biomechanics Models to Individual Player Traits

PS 111

Matthew Koenig

5/31

 

Project Selection/Group Meeting with Advisors

 

Group Meetings

Week 2

6/3

10:00-12:00 pm

Data Science/Open AI

PS 111

Sou-Cheng Choi

6/4

10:00- 12:00 pm

Latex Tutorial

PS 111

Yuanxing Cheng

6/5

10:00-12:00 pm

Intro to Python

PS 111

Larysa Matiukha

6/6

10:00-12:00 pm

Intro to Machine Learning

PS 111

Gael Dimitri Tekam Fongouo

6/7

10:00-12:00 pm

How to Conduct Research

PS 111

Ming Zhong

Week 3

6/14

10:00-11:30 am

Weekly Report/Presentation

PS 111

SURE Fellows (15-20 minutes/group)

Week 4

6/19

 

Juneteenth Day—No Classes

  

6/21

10:00-11:30 am

Research Experience Sharing

PS 111

Emily Willis

Week 5

6/28

10:00-12:00 pm

Midterm Presentation

PS 111

SURE Fellows (30 minutes/group)

12:00 - 1:00 pm

Midterm Presentation Lunch

RE Atrium

 

Week 6

7/1

10:00-11:00 am

Research Experience Sharing at National Labs

Online

Aleksei Sorokin

7/4-7/5

 

Independence Day—No Classes

  

 

Summer 2023

 

 

College of Computing

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