Preparation before matching
Students first complete a short preparation phase covering research fundamentals, tooling, paper reading, technical readiness, and communication habits.
American University of Beirut
AUB Frontier AI Fellows
Frontier AI research exposure for current AUB undergraduates in CCE, CSE, ECE, ME, Computer Science, and related fields, with the bar set by top-tier AI journals and conferences.
Why it exists
Early exposure to top-tier AI research culture.
AUB Frontier AI Fellows connects motivated current AUB undergraduates with Lebanese researchers working in frontier AI labs, PhD programs, and research-focused industry roles. It is designed for students in CCE, CSE, ECE, ME, Computer Science, and related fields who want practical exposure to paper reading, implementation, experimentation, communication, and the publication standards of leading AI conferences and journals. The target is serious, top-venue research output, not generic publication volume.
Program shape
Lightweight, selective, and top-venue publication-facing.
Small mentor interactions
Selected students are matched with a mentor for focused research exposure: paper discussions, reproductions, implementation tasks, experiments, and feedback shaped by the expectations of high-end AI venues.
Top-tier outcomes
The initiative tracks internships, research assistantships, top-tier conference and journal submissions, PhD admissions, open-source work, and notable student achievements.
Research pods
A small structure keeps mentorship meaningful.
Pods are intentionally compact so students get real attention while mentors keep a manageable commitment. Each pod is supported by an AUB mentor for coordination and follow-up.
1
frontier AI researcher or PhD mentor
1-3
AUB undergraduate students
AUB mentor*
coordination and student follow-up
*The AUB mentor keeps the pod coordinated and supports continuity across the program.
Student journey
Two phases before deeper research opportunities.
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1
Pre-selection phase
A lightweight preparation and filtering stage before the academic semester. Students practice reading papers, setting up research tools, communicating progress, and completing technical readiness tasks.
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2
Mentor interaction phase
Matched students work with a Lebanese AI researcher or mentor through focused interactions that reveal how research questions, experiments, and publication workflows for leading journals and conferences actually evolve.
Good fit
For current AUB undergraduates who can be consistent before they are advanced.
Students in CCE, CSE, ECE, ME, Computer Science, and related fields do not need a publication record to start, but they should be ready to work toward a top-tier research standard. The strongest candidates show:
- curiosity about modern AI research questions
- comfort learning new technical tools quickly
- clear written updates and follow-through
- willingness to read papers, reproduce results, and ask precise questions
Visibility and community
Quarterly conversations with Lebanese AI researchers.
The AUB-FAF podcast will host leading Lebanese AI researchers to discuss frontier AI research, academic and industry pathways, lessons from top labs and publication venues, and advice for students entering the field.
Public outcomes
A transparent record of serious research outcomes.
Internships
Research assistantships
Top-tier submissions
Top-tier publications
PhD admissions
Open-source contributions
Student achievements
Next cohort
Applications should open before the semester starts.
The first intake can begin with a short expression-of-interest form for current AUB undergraduates in CCE, CSE, ECE, ME, Computer Science, and related fields, followed by the preparation phase and mentor matching for students interested in high-end AI journal and conference work.
Slack access is shared with selected participants so preparation, matching, and pod communication stay focused.
For more information, contact Ammar Mohanna at am288@aub.edu.lb.