The UNT AI/CS Summer Research Program brings together students from a variety of AI and CS-related academic programs to supplement their traditional course-based educational experiences with focused, project-oriented research efforts

A unique aspect of this program is the immersive 5-week effort which guides students through all stages from initial project selection to research poster presentation. This is accomplished through intensive group efforts, including brief daily full group meetings ("huddles") and daily project group meetings lead by faculty and grad students. The intensive period culminates in a celebration and poster presentation event on the final Friday. This initial period demonstrates what can be accomplished with well-organized, focused, and intensive group effort, and accelerates the student preparation for more independent efforts throughout the summer and into the next academic year. Uniquely this year, we are accepting students with both AI and general computer science interest, with the goal of having project options across both domains to provide additional opportunities for teams.

Sections below:

 

KEY DATES

  1. Application opens: Tue, March 19, 2024. 
  2. Application deadline: Sunday, March 31st Friday, April 5th, 2024 (the application link is found later in this page)
  3. Acceptances are emailed by: Friday, April 12, 2024
  4. Project selection FOR ALL SESSIONS 9am-12pm, Monday, May 20, 2024. Choices to be made online before 3pm.
  5. Regular 5-week session: (9am-12pm): Tuesday, May 21st - Friday, June 21
    1. (preselected stipend students have a 10-week session with more hours per week depending on program)
  6. End of program presentations and poster session
    1. Internal (for 5 week students): Friday, June 21st, 2024
    2. External (for all): Friday, July 26th, 2024

 

2023 SUMMER PROGRAM

Accessible only to participants in the AI Summer Program (through the associated google group)

 

WHO CAN APPLY?

A variety of UNT student and faculty populations are integrated in the program, with some participation more formally arranged than others. The includes faculty, PhD students, MS students, and undergrads including TAMS. The "How to Apply" section details general expectations for all students. Each of the participating groups has additional expectations, requirements, or enrollment limits described below.

MS students (AI, Data Engineering, AI-oriented CS or CE)

Students in this group that are accepted into the program are strongly encouraged, though not required, to sign up for CSCE 5900: Special Problems or CSCE 5934: Directed Study credit under one of the program coordinators - check your degree program if such credit assists toward graduation. You will be given a choice of for-credit courses prior to the start of the program. Only those selected for the program will be able to sign up for course credit.
MS students in other Colleges (e.g. Information, Business, Science, etc) or Engineering departments

Given current resources, 5-10 students in these colleges or other departments will be selected. Proficiency in programming and diversity of skills will be used in selection.
TAMS students

NOTE: The TAMS Summer Research Scholarship deadline was early this year (2024) and decisions have already been made on support. Early Summer Research TAMS students (those just beginning the 2 year TAMS program) are particularly encouraged to apply to jump-start engagement in research. 5-10 TAMS students will be selected.

TAMS students who are also selected for the TAMS Summer Research Scholarship will be required to be at Discovery Park at least 30 hrs/week following the 10 week summer class schedule, as the program requires 10 weeks of participation. TAMS students not selected for the scholarship will only need to participate like all the other students (3 hrs/day only for 5 weeks)
Undergraduates (non-TAMS)

Undergraduate special topics course options are possible with one of the coordinators. Up to 10 UNT undergraduates (not in TAMS) will be accepted.
Ph.D. students

Do not apply to the program in the same manner as other students, however, Ph.D. students conducting AI-related research that can benefit from engaged, focused, and well-managed AI students are strongly encouraged to present their project idea to one of the program coordinators well before the first day of the summer program as an option for program students to sign up. If a Ph.D. student's project is selected, they will be expected to help advise the group pursuing that project with almost daily contact during the relevant program session.
Faculty

Faculty with project ideas are also encouraged to contact one of the coordinators who maintain a curated list of project titles, abstracts, and resources that the students in the AI summer program select among on the first day. Note: The day-to-day project planning, meeting, and advising are provided by the program coordinators and participating graduate students. It is suggested, though not required, that faculty providing project ideas or support are available for contact by project groups at least once/week over the summer for feedback. In our experience, the ideal project options provided by faculty are well-defined problems with data readily available that students can pursue relatively independently, with only daily assistance by a coordinator or knowledgable grad student. Additionally, students have to choose it on the first day so it must be appealing among the options available, and all project options presented are expected to lead to external impact.

APPLICATION

Review the following requirements and make sure you meet them before proceeding to the application:

Availability

  • You are available without interruption for the morning sessions (9am-12) every workday in the 5 weeks of the program.
  • In-person attendance is required. You should not be taking concurrent summer classes during your session given demands of the program, and classes during the morning session are not permitted at all.

Experience expectations

  • You must be actively completing a degree program at UNT or through a previous arrangement with the coordinators.
  • You have substantial programming experience, ideally Python
  • For the AI sessions, you have taken an introductory AI/Machine Learning/Data Science course (e.g. you can explain what "cross validation" is, and why it's useful - or you understand train/validation/test splits)
  • Your GPA at UNT must be 3.0 or higher, and you must have completed at least one semester of courses at UNT prior to the summer.
  • If you are a TAMS student: these are not requirements - though similar experience is encouraged.

Materials to prepare before submission

  • Prepare a Resume or CV for upload for the online application.

After reviewing and preparing the above materials, please complete the online form

Application form due by Sunday, March 31st Friday, April 5th, 2024 (note, a google account will be needed for verification)

 

CONTACT

Any questions, comments, or concerns please email one of the summer program coordinators: Mark Albert at mark.albert@unt.edu or Ting Xiao at ting.xiao@unt.edu. If it is not urgent, please allow up to two workdays for a response.

PAST YEARS

The coordinators have been running summer research programs in AI and CS continuously since 2015 (moving to UNT in Fall 2019) with over 200 students and 50+ projects total so far. Here are the following program summaries which include brief program descriptions, research posters, participants, and pictures.

  • Summer 2023 - 58 students, 18 projects, 9 participating faculty (UNT)
  • Summer 2022 - 56 students, 17 projects, 8 participating faculty (UNT)
  • Summer 2021 - 48 students, 15 projects, 9 participating faculty (UNT)
  • Summer 2020 - 22 students, 9 projects, 10 participating faculty (UNT, primarily TAMS due to COVID-19)
  • Summer 2019 - 30 students, 9 projects, 5 participating faculty (Loyola CS)
  • Summer 2018 - 28 students, 10 projects, 8 participating faculty (Loyola CS)
  • Summer 2017 - 23 students, 7 projects, 8 participating faculty (Loyola CS)
  • Summer 2016 - 30 students, 12 projects, 6 participating faculty (Loyola CS)
  • Summer 2015 - 19 students, 5 projects, 2 participating faculty (Loyola CS)

RELATED LINKS

FAQ'S

  1. I have a question about the program, who do I ask?
    Any questions, comments, or concerns please email one of the coordinators: Mark Albert at mark.albert@unt.edu or Ting Xiao at ting.xiao@unt.edu
  2. Is there a difference between participating for CSCE 5900: Special Projects credit or not?
    Students will not be treated differently in the program based on whether or not they are enrolled in course credit. However, credit helps toward graduation and taking the course indirectly supports efforts like this, and so it is encouraged if it helps you complete your degree. Attendance expectations are clearly more important with course credit on the line, and a lack of participation is generally the only way Special Projects grading would be affected.
  3. But what if I am not as interesting in AI - I just want to participate in this environment?
    That is perfectly fine. We also have CS-focussed projects about developing software, as well as more AI focussed project efforts. In fact, traditionally there have always been projects with a development focus in addition to AI model building/validation/testing. This is why we may refer to the program as the UNT AI/CS Summer Research Program.