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Computational modeling and spatio-temporal prediction applied to social and geospatial problems.
Algorithms and frameworks for solving problems related to mobility and logistics.
Scientific computing for environment and geographical data processing
Algorithms and distributed processing methods for geospatial big data.
Analysis of Geospatial complex networks.
Algorithms and distributed processing methods for geospatial big data. Geolocations and geoparsing.
Machine Learning applied to problems with social relevance and geospatial focus.
Remote sensing and Geographic Information Systems.
Applications for solutions to socio-territorial problems.
Article submission

4/august/2023

Notification of acceptance

18/august/2023

Final version submission

26/august/2022

Publication deadline due:

31 august 2023

Publications fees: $3,700 MXN (mexican pesos)+ Taxes + Comissions for foreign transactions. For detailed information ask to enc2023@cimat.mx.

Instructions for authors:

The articles must be submitted through the CMT3 platform. Conference Management Toolkit (CMT3).

Please remove the authors information for double blind review.


Accepted articles are published in the IEEE proceedings, therefore the format must agree with the IEEE template

The articles must be written in english.

All the articles must satisfy the requirements and quality described in the General Call for Papers.

The extension of the articles must not exceed 8 pages.

The number of authors is limited to 7.

Publication fees: $3,700 MXN + Taxes and comissions (ask to ) with discount of 15% for SMCC and IEEE members

CONTACT

Dr. Rodrigo López Farías

Spatio Temporal modeling with Machine Learning


Dr. Alberto García Robledo

High performance and parallel computing, big data, data visualization, network science


Dr. Sergio Ivvan Valdez Peña

Computer Science


Dr. Jorge Paredes Tavares

Water Sciences


Dr. Hector Solano Lamphar

Atmospheric Science


Dra. Daniela Moctezuma

Digital Image processing, machine learning, natural language processing and remote sensing


Dra. Angelina Espejel

Artificial Intelligence and Data Science

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