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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.

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  4. 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 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 Koenig 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.

SURE Baseball Game Simulation

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

 DateTimeEventLocationSpeaker
Week 15/2810:00-12:00 pmOrientation/Kickoff MeetingPS 111 
12:00 - 2:00 pmKickoff LunchRE Atrium 
2:00 - 3:00 pmIIT Tour/HR Office VisitPS 111 
5/2910:00-12:00 pmResearch IntegrityPS 111Charles W. Uth
5/3010:00-12:00 pmIndividualizing Biomechanical Models – How the White Sox Tune Their Biomechanics Models to Individual Player TraitsPS 111Matthew Koenig
5/31 Project Selection/Group Meeting with Advisors Group Meetings
Week 26/310:00-12:00 pmReproducible Computational Research using Git, GitHub, and Generative-AI ToolsPS 111Sou-Cheng Choi
6/410:00- 12:00 pmHow to Conduct ResearchPS 111Ming Zhong
6/510:00-12:00 pmIntro to PythonPS 111Larysa Matiukha
6/610:00-12:00 pmIntro to Machine LearningPS 111Gael Dimitri Tekam Fongouo
6/710:00-12:00 pmLatex TutorialPS 111Yuanxing Cheng
Week 36/1410:00-11:30 amWeekly Report/PresentationPS 111SURE Fellows (15-20 minutes/group)
Week 46/19 Juneteenth Day—No Classes  
6/2110:00-11:30 amResearch Experience SharingOnlineEmily Willis
Week 46/19 Juneteenth Day—No Classes  
6/2110:00-11:30 amResearch Experience SharingOnlineEmily Willis
Week 56/2410:00-1:00 pmSAMPSCI 2024 WorkshopZoom MeetingOptional
6/2510:00-1:00 pmSAMPSCI 2024 WorkshopZoom MeetingOptional
6/2810:00-11:30 pmMidterm PresentationPS 111SURE Fellows (25 minutes/group)
Week 67/110:00-11:00 amResearch Experience Sharing at National LabsOnlineAleksei Sorokin
7/4-7/5 Independence Day—No Classes   
Week 77/1210:00-12:00 pmWeekly Report/PresentationPS 111SURE Fellows (20-30 minutes/group)
Week 87/1910:00-11:00 pmCareer Experience SharingPS 111Anita Thomas
SURE Speedier Simulations Team
SURE Baseball Game Simulation Team
Machine Learning for Traffic Accident Prediction Team

College of Computing

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312.567.3800

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