8th Junior Conference on Data Science and Engineering (JDSE) 2023
The 8th edition of the Junior Conference on Data Science and Engineering (JDSE) 2023 offers students and young researchers from Université Paris Saclay and Institut Polytechnique de Paris the opportunity to share their research results and develop their critical thinking skills. JDSE is an excellent opportunity to expand your professional network and improve your research presentation skills.
If you're finishing your internship as a second-year Master's student, or if you're a first/second-year PhD student at UPSaclay or IPP, and you've got some great research results waiting to be shared with your colleagues, Master's students or PhD students: present them at the JDSE conference!
Submissions are written in English, in the form of a detailed abstract describing the new or preliminary results of their scientific work (3 pages maximum, including abstract, keyword list and references). They should be in PDF format and adopt the Springer Publications style for Lecture Notes in Computer Science (LNCS): a sample submission can be found here, and refer to this Latex template. Go here to submit your paper.
Full abstracts will be reviewed by the program's scientific and junior committees. Electronic versions of abstracts will be available on the conference website. All deadlines are 23:59 AoE (UTC-12).
Topics of interest include, but are not limited to:
- Data mining;
- Big Data analysis;
- Machine learning and deep learning;
- Applied machine learning (NLP, computer vision, audio processing, bioinformatics...) ;
- Statistics ;
- Semantic Web ;
- Data science applications (biomedical and biological data, physics, chemistry, smart cities, images, documents, audio, video, online advertising...).
Submission deadline: August 20th
Notification of acceptance: September 7th
Conference: September 27 and 28th
- Marta Milovanovic, Télécom Paris, Institut Polytechnique de Paris
- Jun Zhu, CentraleSupélec, University of Paris-Saclay
- Jhony H. Giraldo, Télécom Paris, Institut Polytechnique de Paris
- Michel Kieffer, University of Paris-Saclay
- Zacharie Naulet, University of Paris-Saclay
- Fariza Tahi, Université d'Évry, University of Paris-Saclay
- Enzo Tartaglione, Télécom Paris, Institut Polytechnique de Paris
- Giuseppe Valenzise, CNRS, University of Paris-Saclay
- Marie Laveau, University of Paris-Saclay
- Josselin Kherroubi (Schlumberger) : TBD
- Gaël Varoquaux (INRIA) : Less Prep: Data Science between databases and machine learning ;
- Jean Ponce (ENS - PSL) : Beyond the computer vision confort zone.