​​​​​​​
​ARC - The AI2 Research Club​
​ARC - The AI​2 Research Club​ is a continuous, non-graded extracurricular academic initiative.
The Faculty of Economics and Business Administration (FEAA) from the "Alexandru Ioan Cuza" University in Iasi is our partner in this project.
The club is designed as an experential learning and research-oriented community that supports students in using Generative AI responsibly in academic work, developing research literacy, and transforming ideas into applied AI/ML/NLP projects.

​Language of the Club
​Discussions will be primarily in Romanian. However, because the global language of AI research is English, all papers, experiments, and educational materials will be in English. This questionnaire is in English to assess your comfort level with international research resources.
​Participation Format
​​ARC operated in two complementary formats:
  • ​OPEN SESSIONS (Sesiuni deschise) ​- Large sessions open to the broader FEAA community, especially workshops, Responsible AI sessions, Research craft sessions, and selected guest events. These are intended to remain accessible to all interested students.
  • RESTRICTED ​GROUP (Grup restrâns) - A selective working group of maximum 30 students​, from all years of study and all specialisations of the Faculty of Economics and Business Administration, dedicated to recurring meetings, deeper mentorship, project development and checkpoint-based progress all-year-round.
​Tracks
  • ​AI Foundations and Core Machine Learning - Fundamentals, Machine Learning intuition, evaluation basics, classic ML methods, Neural Network essentials.
  • Applied AI/ML by Domain - Applied projects in areas such as sports analytics, cybersecurity, economics/finance, marketing, operations, education, etc.
  • Research Craft & Bibliometrics - How to read papers efficiently, research question formulation, paper structure, literature review basics, bibliometrics and research synthesis methods.
  • Responsible AI & Research Workflow - Academic Integrity, verification and reproducibility, how to use LLM tools without copy/pasting and minimising hallucinations, literature discovery workflows, practical ”prompt lab” skill-building.
​How ARC works (core components)
The club​'s activities include paper discussions, research skills workshops, applied ML, scientometric methods, and responsible AI workflows. Expect a mix of structured discussion and hands-on work: less ‘passive lecture’, more ‘we actually try it and see what breaks’.
ARC is structured around recurring modules (not a fixed course module), so members can join and continue across semesters and academic years.
  • Paper Deconstructed (Core Loop) - Guided discussion sessions, similar to book clubs, where members read a selected paper/article and discuss: problem, method, evaluation, limitations, and real-world relevance. 
  • The Forge Floor (Project Pitch Sessions) - Members pitch project/research ideas in a short structured format (3-5 minutes), followed by discussions to refine the idea, the question, to identify data sources, propose a baseline AI/ML approach, and form even collaboration groups.
  • Skill Workshops (Track-based, separate sessions as needed) - Practical workshops split by tracks and depth (”Foundations ML Lab”, ”Bibliometrics Lab”, ”NLP starter”, ”Evaluation & Metrics”, ”Research writing”). Workshops are scheduled based on group demand and may run as separate sessions for different interests.
  • Responsible AI Sessions - Short sessions on using AI tools responsibly (prompting, debugging, literature discovery) with emphasis on verification, integrity, reproducibility, and avoiding fabricated references or data.
  • Research Spotlight (Occasional Guest Sessions) - Invited speakers (Academic Faculty, Researchers, PhD Students, Industry Researchers) to present their research topic and share the ”behind the paper” for published articles: idea formation, dead ends, and key decisions.
  • Project Checkpoints and Demo Sessions (periodic) - All members share progress, obstacles, and next steps. Periodic demos will showcase what was built or learnt during the individual or team project trajectory (including ”negative results”).​
​Meeting day: Saturdays (outside class time).
​Why Saturdays? We know your week is full. Saturdays allow us to focus, experiment, and discuss without the pressure of immediately running to another class while grabbing a cappuccino.. or a tea. :)
Frequency: weekly, biweekly, or every few weeks depending on the semester plan and track needs.
Format: on-site (announced via official channels in Teams).

​Eligibility
​Applications are open primarily to students of the Faculty of Economics and Business Administration (FEAA​)​,​ from:
  • Informatică Economică (Licență)
  • Software Development and Business Information Systems (Master)
  • Sisteme Informaționale pentru Afaceri (Master)
Students from Data Mining (Master), Statistică Economică și Data Science (SEDS - Licență), and all the other specialisations at any level of Bachelor / Master / PhD of the Faculty of Economics and Business Administration are welcome if they have a clear interest in practical AI / ML / NLP or research skills and they want to learn more or contribute to the community.

If you are in your final year of study in Bachelor/Master, you can still join the selection. Maybe you will want to become an alumni mentor. :)
​Selection and Membership
​ARC is a selective membership club. Admission is based on:
  1. Alignment with ARC's research and learning objectives,
  2. willingness to follow academic integrity and responsible AI rules,
  3. commitment to consistent participation (this is an active club, not a lecture),
  4. collaborative attitude and readiness to contribute.
Submitting this form does not guarantee acceptance. Accepted members will receive instructions and will be added to the official communication channels.
You can also choose just to be added to our newsletter if you want to only attend open sessions.
​Responsible AI & Academic Integrity
​ARC follows academic integrity standards. AI tools may be used for support (e.g., brainstorming, language clarity, code assistance) but must be verified. Fabricated citations, unverified claims, and undisclosed misuse are not acceptable.
This is not a club where you learn how to trick the academic world into not detecting AI-generated content. 
​Data Processing Notice
​Your data is collected for membership selection and club administration only and is handled internally by the coordinators. You may request deletion of your data at any time.
​About Us
​ARC is coordinated (at the moment) by two first-year PhD Students within the faculty community - Lilia Popescu (lilia.popescu@feaa.uaic.ro) and Mihai Iosupescu (mihai.iosupescu@feaa.uaic.ro).
You can feel free to reach out to us if you have any questions regarding the club on the institutional Teams or via mail. 
Our research interests include Artificial Intelligence / Machine Learning and Scientometric analysis (the science of analysing research), with focus areas on research design and the responsible use of AI tools in academic works.  We will do our best to help you every step of the way.​
Our team also includes Larisa (larisa@feaa.uaic.ro) - our digital infrastructure specialist- and Dan (dan.coman@student.uaic.ro​) - our Marketing wizard, both first-year PhD Students within the faculty.

​