Large-scale Distributed Systems

We are interested in the design and development of large-scale distributed systems based on non-dedicated resources, that are voluntarily contributed by the participants in the system. Currently, we are involved in the following projects: Garlanet (a Twitter-like decetralized microbogging social network) and LSim (a tool for testing applications or protocols in a set of distributed computers). Contact: Dr. Joan Manuel Marquès (jmarquesp(@)

Collaborative Learning Systems
Collaborative Learning Systems

We investigate issues concerning Computer-Mediated Collaboration and Learning within an Adaptive, Interactive, Personalized, Emotion and Context-aware Environment, the design of an integrated model of cognitive e-assessment based on emotional-affective aspects, as well as the development of a live and effective Learning Organization that provides better professional development through collaboration, adaptive training and support in the work place. Contact: Dr. Atanasi  Daradoumis (adaradoumis(@)

Optimization Algorithms for Smart Logistics & Production

We develop metaheuristic algorithms for supporting complex decision-making processes in different fields, including: transportation & logistics, smart cities, Internet computing, production systems, finance, etc. In particular, our simheuristic algorithms combine metaheuristic optimization, simulation, and parallelization techniques to efficiently deal with uncertainty issues in real-life scenarios. Contact: Dr. Angel A. Juan (ajuanp(@)

Applied Data Science

Data analysis is the process of capturing, preprocessing, analyzing, and creating visualization tools and reports in order to transform data into knowledge. Therefore, data analysis enables agents (individuals, companies, governments, …) to make better decisions. We focus on the development of related tools and their applications in the fields of business intelligence, health, e-learning, finance, computational biology, and sports. Contact: Dr. Laura Calvet (lcalvetl(@)

– Selection of Papers in Open Access

  • “Electric Vehicles in Logistics and Transportation: A Survey on Emerging Environmental, Strategic, and Operational Challenges” (link)
  • “A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems” (link)
  • “Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs” (link)
  • “Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends” (link)
  • “Educational Data Mining and Learning Analytics: differences, similarities, and time evolution” (link)