SIMBig
SIMBig is one of the first conferences in Latin America grouping areas such as Artificial Intelligence, Machine Learning, Deep Learning, Healthcare Informatics, Natural Language Processing, Semantic Web, Software Engineering, among others.
+2000
Participants in all editions of SIMBig
+200
Published Research Articles
+50
Top Keynote Speakers
Keynote Speakers
Outstanding leaders who will challenge your ideas and enhance your creativity.
LEARN, CONNECT and EXPERIENCE.
Important Dates
Don't miss the crucial deadlines for paper submissions at our event.
August 10 September 07, 2024
Papers submission deadline
September 30, 2024
Notification of acceptance
October 28, 2024
Camera-ready versions
November 20 - 22, 2024
Conference held at the Universidad Nacional de Moquegua, Peru
Call for Papers
Participate in one of the first conferences in Latin America that group data science topics and be part of the technological change.
EE-AI-HPC Special Track
Efficieny Enhencement for Artificial Intelligence and High-Performance Computing
More DetailsConference proceedings
All papers of SIMBig 2024 will be published with Springer CCIS series (Communications in Computer and Information Science).
(To be confirmed)
Travel grants
Thanks to the Artificial Intelligence Journal - AIJ support, SIMBig 2024 is offering six travel awards for authors attending the conference
Organizing Institutions & Sponsors
Meet our sponsors and organizers.
Organizing Institutions
Co-organizing Institutions
Sponsors
Past Keynote Speakers Testimonials
Discover the opinions of past speakers.
SIMBig is a very good opportunity to make new collaborations between Peruvian and foreign universities.
Pascal Poncelet
[University of Montpellier, France]
SIMBig is a very good conference with very quality presentations.
Diana Impken
[University of Ottawa, Canada]
Events like these [SIMBig] are a great opportunity for students to interact with researchers and to see cutting edge things happening.
Lise Getoor
[University of California, USA]
[SIMbig] attracts the next generations data mining and bigdata researches. One important thing is to bridge between areas as big data and supply chain and attract more people.
Jian Pei
[Simon Fraser University, Canada]
