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H2020Doctoral network2020–2024

TraDE-OPT · Training Data-driven Experts in OPTimization

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2020-06-01 → 2024-11-30
EU contribution
€3,774,874
Participants
8
Scheme
MSCA-ITN

Lines connect the coordinator with its partners.

Results in brief

Training Data-driven Experts in OPTimization

The TraDE-OPT project aimed to train 15 experts in optimization for data science, equipping them with a strong multidisciplinary background to advance the state of the art. In today's world, data is generated at an unprecedented scale. Extracting meaningful insights from vast and complex datasets is one of the central challenges of data science. Optimization plays a fundamental role in this process, providing the theoretical and algorithmic foundations for solving complex problems efficiently. While recent advances in optimization, machine learning, functional analysis, and signal processing have led to powerful mathematical tools and algorithms, many challenges remain. The size, heterogeneity, and incompleteness of modern datasets continue to pose significant obstacles, requiring new and more efficient approaches. TraDE-OPT addressed these challenges by focusing on exploiting structure—whether in data, models, or computational platforms—to develop advanced optimization algorithms with guaranteed performance. These methods leveraged decomposition techniques, incremental and stochastic strategies, and parallel or distributed computing, significantly improving scalability and efficiency in real-world applications. To achieve these goals, TraDE-OPT provided an innovative training program, combining strong technical foundations with essential employability skills, such as entrepreneurship, communication, and career planning. As a result, TraDE-OPT fellows are now well-prepared for outstanding careers in both academia and industry, contributing to the continued advancement of optimization and data science for the benefit of society.

Data: CORDIS, © European Union

Project objective

The main goal of TraDE-Opt is the education of 15 experts in optimization for data science, with a solid multidisciplinary background, able to advance the state-of-the-art. This field is fast-developing and its reach on our life is growing both in pervasiveness and impact. The central task in data science is to extract meaningful information from huge amounts of collected observations. Optimization appears as the cornerstone of most of the theoretical and algorithmic methods employed in this area. Indeed, recent results in optimization, but also in related areas such as functional analysis, machine learning, statistics, linear algebra, signal processing, systems and control theory, graph theory, data mining, etc. already provide powerful tools for exploring the mathematical properties of the proposed models and devising effective algorithms. Despite these advances, the nature of the data to be analyzed, that are “big”, heterogeneous, uncertain, or partially observed, still poses challenges and opportunities to modern optimization. The key aspect of the TraDE-Opt research is the exploitation of structure, in the data, in the model, or in the computational platform, to derive new and more efficient algorithms with guarantees on their computational performance, based on decomposition and incremental/stochastic strategies, allowing parallel and distributed implementations. Advances in these directions will determine impressive scalability benefits to the class of the considered optimization methods, that will allow the solution of real world problems. To achieve this goal, we will offer an innovative training program, giving a solid technical background combined with employability skills: management, fund raising, communication, and career planning skills. Integrated training of the fellows takes place at the host institute and by secondments, workshops, and schools. As a result, TraDE-Opt fellows will be prepared for outstanding careers in academia or industry.

Original text from CORDIS.

Participants

  • UNIVERSITA DEGLI STUDI DI GENOVA · GENOVACoordinatorItaly
  • CAMELOT BIOMEDICAL SYSTEMS SRL · GenovaItaly
  • CENTRALESUPELEC · GIF SUR YVETTEFrance
  • SYSTEMS RESEARCH INSTITUTE OF THE POLISH ACADEMY OF SCIENCES IBS PAN · WarszawaPoland
  • TECHNISCHE UNIVERSITAET BRAUNSCHWEIG · BraunschweigGermany
  • UNIVERSITAET GRAZ · GrazAustria
  • UNIVERSITATEA NATIONALA DE STIINTASI TEHNOLOGIE POLITEHNICA BUCURESTI · BUCURESTIRomania
  • UNIVERSITE CATHOLIQUE DE LOUVAIN · LOUVAIN LA NEUVEBelgium

Links

Data: CORDIS, © European Union