Students

PhD Thesis

  • Alejandro Carnero Hijano. Anomaly Detection through Deep and Distributed Machine Learning techniques based on Data Streams. 2023-present

  • Antonio Jesús Chaves García. Machine learning techniques with real-time data streams. 2023-present

  • Sergio Infante Paredes. Distributed and intelligent digital twins. 2023-present

BS Thesis

  • Jesus Jimenez. BS Thesis: Web Application for the Management and Monitoring of Energy Values Collected by Smart Meters. Defense: October 2022.

  • Yeray Ruiz. BS Thesis: Machine learning application to detect energy consumption patterns. Defense: July 2022.

  • Adrián Corrales. BS Thesis: Machine learning application to predict energy prices. Defense: July 2022.

  • Alejandro Megias. BS Thesis: Monitoring system for agriculture based on Edge architectures. Defense: February 2022.

  • Antonio Jesús Chaves. BS Thesis: Tool to help to detect and count pollen particles in biological samples. Defense: June 2021.

  • Christian Martos. BS Thesis: Portable water quality monitoring system. Defense: June 2021.

  • Fernando González. BS Thesis: Creation of a smart medicine dispenser. Defense: 2021.

  • Jorge Martinez. BS Thesis: Smart thermometer. IoT cloud technologies and microcontrollers. Defense: 2021.

  • Jose Manuel Muñoz. BS Thesis: Development of disinfection robot and android control application. Defense: 2021.

  • Álvaro Manuel Aparicio. BS Thesis: Image analysis in cloud-fog architecture with lwm2m (light weight machine to machine). Defense: February 2021.

  • Sergio Fernández. BS Thesis: Arduino-based radio-controlled car racetrack construction set. Defense: September 2021.

  • Alejandro Carnero. BS Thesis: A framework for the flexible deployment of distributed neural networks in the Fog. Defense: September 2020.

  • Stefan Gabor. BS Thesis: A system to define fault-tolerance IoT applications at software and hardware levels. Defense: July 2019.

  • Manuel Granados Molina. BS Thesis: An Edge Computing framework for the development of Internet of Things applications. Defense: July 2019.

  • Jose Carlos Baena González. BS Thesis: Adaptive access and sharing of resources and sensors through CoAP. Defense: July 2018.

MS Thesis

  • Antonio Jesús Chaves. MS Thesis: Orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka-ML: a deep learning performance comparative. Defense: October 2022.

  • Alejandro Carnero. MS Thesis: Preventive Maintenance of Wind Turbines based on Deep Learning Techniques with the Help of a Telescope. Defense: September 2021.

  • Javier Luengo. MS Thesis: Optimal replication of Apache Kafka instances on the edge using Derecho library. Defense: September 2021.

  • Francisco Manuel. MS Thesis: Blockchain Traceability System. Defense: September 2021.

  • Fernando Gallego. MS Thesis: Real-time monitoring of ventilation systems. Defense: March 2021.

  • Iván Alba García. MS Thesis: A reliable system to manage IoT devices and information through Blockchain. Defense: September 2020.