Available thesis proposals:
- Optimization and simulation of industrial and engineering systems
- Analytics in smart cities, transportation & logistics, and management
- AI-Driven Optimisation for Fusion
| Thesis proposals | Researchers | Research Group |
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Internet Computing & Systems Optimization (ICSO) is an official IN3 programme supported by the DPCS research group. One of the main research topics in ICSO is the development of new hybrid algorithms and methods which combine applied optimization (eg heuristics and metaheuristics), discrete-event simulation and data analysis to support decision-making processes in realistic environments. In particular, we are interested in the real-life application of these algorithms in the contexts of logistics, transportation and production systems. Thus, the doctoral theses will be related to any of the following topics: rich (real-life) vehicle routing problems, real-life scheduling problems, green logistics, intelligent transport systems, horizontal collaboration in logistics, etc. These topics represent important challenges for the industrial sector in any developed country, which explains their relevance in the context of current international research.
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Mail:drierat@uoc.edu |
ICSO |
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Analytics in smart cities, transportation & logistics, and management Descriptive business analytics (DBA) refers to the pre-processing and processing of historical data gathered by companies in order to describe the real business context, generate information, and make rational decisions from the acquired knowledge. After describing the real business context, one can also benefit from predictive business analytics (PdBA), which relies on the use of time series analysis, regression models, and even machine learning methods in order to forecast the future or predict how certain business factors will evolve under scenarios of uncertainty. Finally, prescriptive business analytics (PsBA) aims at supporting complex decision-making processes in business through the use of optimization and simulation algorithms (including metaheuristics and simheuristics). These algorithms allow managers to “learn from the future” (by performing what-if analyses), significantly increasing the efficiency of business processes and systems, reducing operational costs and, at the end of the day, raising companies’ profits. PsBA have many applications in a variety of fields, including smart cities, transportation and logistics, finance, healthcare, tourism, etc. The aim of this line of research is to explore, from an interdisciplinary and IT-based perspective, some of the almost unlimited applications of analytics to any of the previously described service industries. |
Mail:drierat@uoc.edu |
ICSO |
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AI-Driven Optimisation for Fusion Fusion energy aims to address the rapidly growing global energy demand while reducing carbon emissions. To design and operate future fusion reactors—such as ITER and DEMO—accurate predictive models are essential. Simulation and modelling are therefore central pillars of fusion research, enabling the study of plasma behaviour, reactor performance, or material challenges in the reactor. However, fusion codes may be computationally very demanding. They typically require the use of large-scale HPC infrastructures and supercomputers. Our research group focuses on the optimisation and acceleration of fusion simulation workflows. The doctoral theses in this research line will investigate how Artificial Intelligence and techniques such as machine-learning-based surrogate modelling can be integrated into existing fusion codes to reduce execution time by orders of magnitude, while preserving physical accuracy. |
Dr Albert Gutiérrez Mail: agutierrez0@uoc.edu |