We are pleased to announce the third edition of the Best Romanian AI Thesis Awards (BRAIT). This competition recognizes outstanding Bachelor’s, Master’s, and PhD theses in Artificial Intelligence, fostering innovation and excellence in AI research.
🏆 Competition Tracks
Best Bachelor’s Thesis
Best Master's Thesis
Best PhD Thesis
📢 Top papers will be invited to present their work either as posters or oral presentations during Romanian AI Days 2026.
🏅 Win prizes and EEML 2027 scholarships.
✈️ Travel Grants: If your paper is selected for presentation at Romanian AI Days, you may apply for financial support.
We invite professionals from academia and industry to support the review process. Interested?
Register here: registration form
✅ Graduates with a Bachelor’s, Master’s, or PhD thesis in Artificial Intelligence
📅 Bachelor's & Master's theses defended between 1 January 2025 – 30 June 2026*
📅 PhD theses defended between 1 January 2024 – 30 June 2026
🏛️ Studies completed at a Romanian higher education institution (full-time or visiting student, e.g., Erasmus)
*for Bachelor's and Master's levels, we also welcome submissions from students scheduled to defend their theses in July 2026
🚀 Submissions Open 1 May 2026
⏳ Submission Deadline 1 July 2026
🎯 Decisions Announced 1 September 2026
Warning: Registration is through OpenReview. If you register using a non-institutional email, it may take up to 2 weeks for your OpenReview account to be activated. Make sure you meet the competition deadline.
📌 For full submission rules, formatting templates, and anonymization details, see Submit page.
📄 What to Submit?
✅ Short Paper (4 pages) summarizing your thesis contributions
✅ Bachelor’s / Master’s / PhD Thesis
📥 Submit via OpenReview <details coming soon>
⚠️ Important Notes:
Documents and reviews will not be made public without author consent.
OpenReview registration: Non-institutional emails may take up to 2 weeks for activation—plan ahead!
🎭 Double-Blind Review
Submissions must be fully anonymized to ensure fairness.
The short paper is the primary evaluation document, but reviewers may consult the thesis.
🕵️ Anonymization Guidelines (Key Points)
✅ Short Paper: Remove names, affiliations, acknowledgments, and self-referencing.
✅ Thesis: Remove names, affiliations, acknowledgments and institution logos. Minor deviations are acceptable - see Submit page
For a comprehensive breakdown of the evaluation criteria, please see the [Official Evaluation Criteria (PDF)].
Core Intellectual Contribution The submitted thesis must represent the original intellectual work of the author. This prize is intended to recognize theses that demonstrate strong student-led research conduct regarding the formulation of hypotheses, experimental design, and critical interpretation of results. The student remains fully responsible for the validity, originality, and integrity of the work.
Permitted Use & Documentation
Methodological Integration: Use of LLMs as a subject of study or as part of the experimental setup (e.g., data labeling, code generation, or model benchmarking) is permitted. Such use must be formally documented within the Methodology section of the thesis, detailing the model version and specific role it played in the workflow.
Writing Assistant:
Grammar & Style: The use of AI for standard grammar correction, spell-checking, and basic linguistic polishing (e.g., Grammarly or LLM-based spell-checks) is permitted and does not require formal disclosure.
Structural/Substantive Editing: Use of AI for structural suggestions or substantive paraphrasing is permitted but must be noted in the AI Transparency Statement.
Attribution of Generative Content: If an LLM is used to generate specific text segments (e.g., a summary of a concept), it must be clearly attributed or block-quoted to maintain academic integrity and avoid plagiarism.
Disclosure: AI Transparency Statement
All submissions must include a brief AI Transparency Statement (placed before the References). This statement should:
Identify the specific models used (e.g., GPT-4o, Claude 3.5).
State the purpose of the assistance (e.g., "Used for Python code optimization" or "Used for structural feedback on the literature review").
Accountability & Integrity The author is strictly responsible for the accuracy of all content. AI-generated errors (such as fake citations or fabricated data) will be treated as standard academic misconduct.
The committee reserves the right to request additional documentation if the integrity of the core intellectual contribution is in question.
Adriana Stan, UTCN
Alexandru Sorici, UNSTPB & ARIA
Elena Burceanu, Bitdefender & UNSTPB
Emanuela Haller, UiPath & UNSTPB
Florin Brad, Bitdefender
Sorin Grigorescu, RovisLab & Transilvania Univ.
Răzvan Pașcanu, EEML & DeepMind
Traian Rebedea, NVIDIA & UNSTPB
Viorica Pătrăucean, EEML & DeepMind
BRAIT is organised as part of Romanian AI Days. If you are interested in sponsoring the awards please get in touch at contact ai romania dot eu to learn about the benefits for sponsors.
For any questions please get in touch at contact at airomania dot eu