Teclas de Ayuda de acceso Rápido

ALT + 1 Inicio

ALT + 2 Noticias

ALT + 3 Mapa de sitio

ALT + 4 Búsqueda

ALT + 5 Preguntas frecuentes

ALT + 6 Atención al ciudadano

ALT + 7 Quejas y reclamos

ALT + 8 Iniciar Sesión

ALT + 9 Directorio telefónico

Botones de Accesibilidad



martes, 7 de diciembre 2021


Research group


Intelligent Information Systems Lab In2Lab

Academic Unit: Faculty of Engineering

Colombian Ministry of Science








Engineering and technology


Other engineering and technologies

Download get_app

Strategic Focus

The aim of the Intelligent Information Systems Lab group (UdeA) is to contribute to technological development both regionally and nationwide in Colombia by generating knowledge and developing basic and applied research projects on information technology. We specialize in the development of information systems that incorporate cognitive components based on artificial intelligence techniques with the intention of generating high added-value innovative solutions that have a positive impact on the international academic community, on the work of other research groups, and on national companies.

Research Areas and Topics

  • Data Management and Modeling (mathematical models and simulation, computational intelligence-based prediction, machine learning and data mining, parallel and distributed algorithms).
  • Software Engineering Methods and Techniques (model-directed development; adaptive and personalized software).

Sustainable Development Goals (SDGs)

Good health and well-being Industry innovation and infraestructure Sustainable cities and communities

Group Coordinator

John Fredy Duitama

Group Coordinator Email


Scientific Cooperation

Collaborative Relationships

  • Universidad Nacional de Colombia.
  • Universidad Tecnológica Pereira.
  • Universidad del Rosario.
  • Universidad de Medellin.
  • Universidad EAFIT.
  • ARTICA center of excellence: Regional Alliance on Applied Information and Communication Technologies.
  • E.G.M. Ingeniería Sin Fronteras S.A.S.
  • Humax Pharmaceutical S.A.
  • Bialtec S.A.S.
  • Université de Paris I.
  • Universidad Politécnica de Madrid.
  • Universidad Politécnica de Cataluña.

Notable Projects

  • Automatic detection of fraud in virtual transactions with debit and credit cards.
  • Technological prospection analysis on mHealth, video game apps, and big data.
  • Construction of an Interoperability Model for information products and services in health II.
  • Computational Tool for Predicting Dissolution Profiles and Oral Solid Medication Formulations in the Optimization of the Pharmaceutical Development Process.
  • Technological platform for medical emergencies, telemedicine, and permanent monitoring for patients; also, support for promotion and prevention programs.

Main Research Results

  • Multimodal and Multi-output Deep Learning Architectures for the Automatic Assessment of Voice Quality Using the GRB Scale. DOI: https://bit.ly/2z4i7Ao
  • Reference Software Architecture for Improving Modifiability of Personalised Web Applications – A Controlled Experiment. DOI: https://bit.ly/30bpEZe
  • Weaving of Metaheuristics with Cooperative Parallelism. DOI: https://bit.ly/2MvJJS3
  • Common Disbalance in the Brain Parenchyma of Dementias: Phospholipid Profile Analysis Between CADASIL and Sporadic Alzheimer's Disease. DOI: https://bit.ly/3eN5Sr2

Research Portafolio

  • The group is highly experienced in data analysis techniques and is equipped with the appropriate infrastructure for processing high volumes of information. It offers consulting and development services for projects requiring the use of technologies related to Big Data ecosystems, such as Hadoop, Spark, Hive, HBase, etc., as well as those related to data analysis, Machine Learning, and Deep Learning, such as TensorFlow, PyTorch, SparkML, sklearn or technologies related to data visualization and BI. The group is qualified for supporting and developing solutions based on the technologies mentioned and also for addressing basic problems that require redesign and development of new ML algorithms and/or models for processing information according to the project requirements.

More Information


Universidad de Antioquia | Vigilada Mineducación | Acreditación institucional hasta el 2022 | NIT 890980040-8
Recepción de correspondencia: calle 70 No. 52 - 21 | Apartado Aéreo 1226 | Dirección: calle 67 No. 53 - 108 | Horario de atención
Conmutador: [57 + 604] 219 8332 | Línea gratuita de atención al ciudadano: 018000 416384 | Fax: [57 + 604] 263 8282
Peticiones, quejas, reclamos, sugerencias, denuncias, consultas y felicitaciones
Política de tratamiento de datos personales
Medellín - Colombia | Todos los Derechos Reservados © 2020