The UNT AI Summer Research Program brings together students from a variety of AI-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 4-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 twice-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 Friday after the 4 week intensive period ends. 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 rest of the summer at a more sustainable pace. [special note: Summer 2021 will be conducted 100% online]
- Key dates
- Who can participate?
- How to apply
- Past summer programs
- Contact information
- Related links
- FAQ (frequently asked questions)
- Application opens: Monday, March 15, 2021
- Application deadline:
Friday, April 9, 2021Extended to Wednesday night, April 14th
- Acceptances are emailed by: Friday, April 16, 2021
- Program begins: Tuesday, June 1, 2021 (10am - 4pm, for both morning and afternoon sessions)
- Intensive period ends: Friday, June 25, 2021 (10am - 12pm celebration event for both morning and afternoon sessions)
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.
Core MS students (AI, Data Engineering, AI-oriented Computer Science/Engineering MS): Students in this group that are accepted into the program are encouraged, though not required, to sign up for CSCE 5900: Special Problems credit under Dr. Mark Albert or Dr. Ting Xiao - check your degree program if such credit assists toward graduation. The intention for Summer 2021 is to expand the program as needed to accomodate any MS in AI/DE student who is able to participate (while this will not be possible in future summers due to expanded enrollments, AI/DE students will always be given priority). 20+ MS in AI/DE students are expected to enroll, though more can be accomodated.
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 student deadline to apply for this summer program is April 7nd (two days earlier) to coincide with the TAMS Summer Scholarship (which will be decided by April 9th through TAMS). Additional restrictions apply for TAMS Summer Scholars that will be discussed. 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.
Undergraduates (non-TAMS): Undergraduate special topics course options are possible with one of the coordinators (Dr. Albert or Dr. Xiao). 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, focussed, and well-managed AI students are strongly encouraged to present their project idea to one of the program coordinators (Dr. Albert or Dr. Xiao) well before the first day of the summer program as an option for program students to sign up for. If a Ph.D. student's project is selected, they will be expected to help advise the group pursuing that project with daily contact during June.
Faculty with project ideas are also encouraged to contact one of the coordinators (Dr. Albert or Dr. Xiao) 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 is provided by the program coordinators and participating graduate students. It is suggested, though not required, that faculty providing projects 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.
Review the following requirements and make sure you meet them before proceeding to the application:
- You are available without interruption for either morning sessions (8am-12) or afternoon sessions (1-5pm) every workday in the 4 weeks from June 1 to June 25.
- Again, attendance is required [virtually for Summer 2021 - but still required]. Though not explicitly checked, you should not be taking concurrent summer classes in June given demands of the program.
- 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
- 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
Friday, April 9, 2021Extended to Wednesday night, April 14th (note, a google account will be needed for verification)
Any questions, comments, or concerns please email one of the summer program coordinators: Mark Albert at email@example.com or Ting Xiao at firstname.lastname@example.org. If it is not urgent, please allow up to two workdays for a response.
The coordinators have been running summer research programs in AI and CS continuously since 2015 (moving to UNT in Fall 2019) with over 150 students and 40+ projects total so far. Here are the following program summaries which include brief program descriptions, research posters, participants, and pictures.
- Summer 2020 summary - 22 students, 9 projects, 10 participating faculty (UNT, primarily TAMS due to COVID-19)
- Summer 2019 summary - 30 students, 9 projects, 5 participating faculty (Loyola CS)
- Summer 2018 summary - 28 students, 10 projects, 8 participating faculty (Loyola CS)
- Summer 2017 summary - 23 students, 7 projects, 8 participating faculty (Loyola CS)
- Summer 2016 summary - 30 students, 12 projects, 6 particpating faculty (Loyola CS, 12 students BSMP)
- Summer 2015 summary - 19 students, 5 projects, 2 participating faculty (Loyola CS, 5 students BSMP)
- The application form - deadline April 9, 2021
- Additional AI Summer Experiences available
- 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 email@example.com or Ting Xiao at firstname.lastname@example.org.
- 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 expecations 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.