Smart Services for Information Systems and Communication Networks. SISCOM

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Master and Ph.D. Theses

Ph.D. Theses offers

1. PhD position in the area of database privacy

  • RESEARCH TOPIC. Being traded as a commodity, personal information such as our habits, interests, date of birth, number of children or home address, and even our daily movements, are given up these days quite often without being aware they are being collected, stored and finally sold to a wide range of companies. With the advent of modern data-analytics technologies, the availability of massive amounts of such pieces of information –the so-called big data era– is recently creating invaluable analytical opportunities. While the volume, velocity and variety of the data being extracted offer possibilities of unquestionable benefits, they pose at the very same time evident privacy and security risks.

  • DESCRIPTION OF POSITION. The PhD position has a duration of 3 years and is made available through the research project “Big Data Anonymization” funded by “la Caixa”, a top Spanish financial institution. The main objectives of this project are to pioneer advance beyond state of the art on the design of anonymization algorithms and to develop a comprehensive understanding of privacy in a context of big data. The ultimate aim is to contribute to making big data compatible with the right to privacy. For the scholarship, we are looking for a candidate who is qualified to undertake supervised independent research in the area of database anonymization, in particular in the protection of dynamic data under popular syntactic models (e.g., l-diversity, t-closeness) and differential privacy.

  • QUALIFICATIONS. We seek a highly motivated PhD student who has completed or is about to complete by summer 2020 a Master's degree in mathematics,        computer science, or telecom engineering; with excellent academic record; good analytical skills; strong oral and written communication skills.

  • APPLICATION. Candidates should send to Prof. Jordi Forné (jordi.forne@upc.edu) the following information: their CV (including list of publications, if any); their academic record (with marks); a certificate of English (TOEFL, Cambridge or similar).
  • More information here. 

Ongoing Ph.D. Theses

  • Alberto Bazán Guillén. Supervisor: Dr. Mónica Aguilar Igartua (UPC).  "Design of federated learning framework to improve urban mobility and smart city services". Federated learning techniques to improve smart services for smart cities. We use OMNeT++/VEINS/SUMO/OSM. Dissertation planned for 2025.
  • Víctor Rubio Jornet. Supervisors: Dr. Javier Parra Arnau and Dr Jordi Forné. Anonymization technologies for mobility data. Dissertation planned for 2025.
  • Yaqoob Al-zuhairi. Supervisor: Dr. Mónica Aguilar Igartua (UPC). "Privacy-aware federated learning for vehicular networks to manage electrical vehicles charging services". Improve the charging service of electrical vehicles using federated learning techniques in vehicular networks. We use OMNeT++/VEINS/SUMO/OSM. Dissertation planned for 2025.
  • Prashanth Kannan. Supervisors: Dr. Mónica Aguilar Igartua (UPC) and Dr. Pablo Barbecho Bautista (Ecuador). "Design of privacy-aware vehicular networks for greener transportation". Using federated learning techniques, hybrid vehicular networks (LTE, 5G, DSRC), hybrid vehicles (electrical and fuel), platooning towards greener transportation. We use OMNeT++/VEINS/SUMO/OSM. Dissertation planned for 2025.
  • Adrián Tobar Nicolau. Supervisors: Dr. Dr. Jordi Forné Muñoz and Javier Parra Arnau. Dissertation planned for 2025.

Recent Ph.D. Theses defended

  • Dr. Álvaro Martín Prieto. Supervisors: Dr. Mónica Aguilar Igartua (UPC) and Marc Düvel (Volkswagen). Industrial Doctorate being done in Volkswagen.  "Control Strategy and predictive methods for performance and component lifetime enhancement in vehicle powertrains". Design of a power boost function using artificial neural networks to allow vehicles to deliver a temporary power boost when required. Dissertation on 26 April 2023.
  • Dr. Pablo Barbecho Bautista. Supervisors: Dr. Mónica Aguilar Igartua (UPC) and Dr. Luis Felipe Urquiza-Aguiar (Ecuador). Design of a smart service to improve the charge of electric vehicles (EVs) in urban scenarios. Design of tools to optimize and speed up the process of large simulations campaigns. Design of a reinforcement learning model to optimize the relation of the EV's speed and the cycle of traffic lights in smart cities. 19th May 2022.
  • Dr. Leticia Lemus. Supervisors: Dr. Mónica Aguilar Igartua (UPC) and Dr. Ahmad Mohamad Mezher (Canada). Design of a multimetric routing protocol for VANETs based on greedy perimeter stateless routing (GPSR). The weights of the metrics will be dynamically updated depending on the current scenario, according to a designed algorithm based on machine learning. Interaction of autonomous vehicles (AVs) and VANETs using machine learning techniques. 22nd July 2020.
  • Dr. Juan Pablo Astudillo León. Supervisor: Dr. Luis J. de la Cruz Llopis (UPC). Wireless Mesh Networks: Traffic routing and engineering, traffic differentiation, quality of service, congestion control, static and dynamic environments (smart grid networks, cell phone networks, wearables). 9th June 2020.
  • Dr. Ana Fernanda Rodríguez. Supervisor: Dr. Jordi Forné Muñoz. Contributions to Privacy-Enhancing Technologies for Machine Learning Applications. Design and evaluation of anonymization algorithms with special focus on improving the usability of the anonymized data.

Master Theses offers

  • Development of algorithms to identify transportation modes for MobilitApp, an Android application for citizens

MobilitApp project (http://mobilitat.upc.edu):  We offer Master/Degree thesis. The student will join the MobilitApp project that we develop in collaboration with the ATM (Autoritat del Transport Metropolità) of Barcelona. MobilitApp is able to detect the type of transportation and take statistics. Current on-going tasks: improve our machine learning algorithm to online  find out the transportation mode being used, send an emergency message upon the occurrence of an accident, suggest alternative types of transportation, among other features. Sensor data from the smart phones is gathered and periodically sent to our Raspberry Pi server, where it is analysed. The goal is to save battery avoiding the use of GPS to find out the type of transportation being used.

Some past MobilitApp theses:
https://prezi.com/vb5l_v7nlkzp/mobilitapp-2015/
https://www.youtube.com/watch?v=asVWO0HnvOM
http://arxiv.org/abs/1605.05342		Contact: Mónica Aguilar Igartua, monica.aguilarupc.edu

 

  • Development of a charging service for electrical vehicles using vehicular communications

Using a platform for vehicular communications already implemented in the OMNET++/VEINS/SUMO simulator, the student will participate on the design of a platform to manage the charging service of electrical vehicles in the city. The goal is that the smart grid can plan the energy consumption properly. We will use vehicular networks to transmit the involved messages. The student will join a team of PhD students who are doing their doctoral thesis in this field.

                                                                                     Contact: Mónica Aguilar Igartua, monica.aguilarupc.edu