Contact

Departamentul Calculatoare
Str. G. Barițiu nr. 28, 400027 Cluj-Napoca, România

Director departament - Sala C9, Telefon: +40-(0)264-202389
Secretariat - Sala M04, Telefon: +40-(0)264-401221

The Computer Science Department of the Faculty of Automation and Computer Science- Technical University of Cluj-Napoca,
and
the Computer Science Department of the Faculty of Mathematics and Computer Science- “Babes-Bolyai” University

organize the Computer Science Students Conference 2018, on June 25, 2018.

Students are invited to participate with original articles, which will be evaluated and selected for public presentation, as well as for further publication.
The papers must be submitted until the June 11, 2018, end of day, on the e-mail address paulina.mitrea@cs.utcluj.ro, together with the Registration Form (see below).

New: extensie termen de transmitere a lucrarilor: 17 iunie ora 24.00 si rezultatele de acceptanta: 22 iunie

The papers must respect the IEEE format, having no more than 6-8 pages, written in English.
After the evaluation process, the accepted papers will be presented according to the Program that will be announced in June 20, 2018.
Taking into account their scientific relevance, some papers will be considered for publication in scientific journals. The best papers will be awarded
Contact person: Assoc. Professor, PhD Paulina Mitrea
Registration form template, to be downloaded: Registration_Form_2018.

Conference Program

Computer Science Students Conference 2018 AWARDS

Locul 1: Cristian Pintea, Eugen Pintea " Extending CloudSim with Cooling System Energy Models "

Locul 2: Andreea Onaciu ," Ensemble of artificial neural networks for Aspect Based Sentiment Analysis"

Locul 3: Alexandra Ghiurau ," Abstractive Text Summarization with pre-trained embeddings and reversed input "

Mentiune 1: Bumb Alexandru ," Weather & Soil Data Provider for WSN simulators "

Mentiune 2: Andrei Rares Bucur ," Real time document/paper scanner "

Mentiune 3: Raluca Lazar, Cristina Matei, Raluca Sechel ," Artifact detection in EEG using machine learning "