ERTS

PhD Dissertation Award

 » Call for nominations: ERTS 2026 PhD Dissertation Award on embedded critical computing systems « 

About the ERTS PhD Dissertation Award

The award aims at recognizing an individual who has made throughout his or her PhD dissertation a significant contribution to the development and operation of safe, secure, real-time, autonomous and sustainable embedded critical computing systems. All topics related to the design, architecture, verification, validation or assessment of critical embedded systems and networks, including software and hardware layers, as well as engineering practices and tools are relevant.

The award recipient will receive a waived registration fee to attend the edition of the Embedded Real-Time Systems (ERTS) Congress at which the award is presented. The recipient will be required to attend ERTS to receive the award and will be invited to give a presentation to ERTS attendees.

Award Details and Eligibility

What the Winner Receives

  • Complimentary registration to the ERTS Congress.
  • Opportunity to present their work to the ERTS community.

PhD Award Selection committee

Chair: Simin Nadjm-Tehrani, Linköping University, Sweden

Members:

  • Antonio Casimiro, University of Lisbon, Portugal
  • Juan-Carlos Ruiz, Universitat Politécnica de València, Spain
  • Mario Trapp, Technical University of Munich and IKS Fraunhofer, Germany

Eligibility and Nomination

To be eligible for the award, the nominee’s PhD defense must be completed prior to the nomination deadline not submitted in the previous ERTS2024 edition and must have occurred during the period [March 1st 2024 – October 31st 2025].

Nominations are to be made by the nominee’s PhD advisor. The nominations package should include (in a single PDF file):

  • A cover letter from the PhD advisor, including the name of the PhD granting institution, the date of the PhD defense and a brief nomination statement (1 page max).
  • A two-page summary of the research work in English, including: 1) Problem description and significance, and 2) an argument supporting the innovative and the impact of the contributions.
  • The curriculum vitae of the PhD recipient, including a list of publications that resulted from the dissertation research (including those that are under review at the time of nomination).
  • Copies of up to three papers resulting from the dissertation work among the list above
  • The reports of the PhD defense committee (rapporteurs’ reports, and the minutes of the defense if applicable).
  • The complete dissertation in its original language.

A special committee will evaluate all nominations made in the current edition and choose the award recipient. The committee Chair and the committee members will be appointed by the ERTS Scientific Committee chair after the nomination deadline to avoid potential conflicts of interest. The ERTS award committee shall not include members who have nominated someone for the award have contributed to the research carried out by a nominee. The committee chair and members will be published at the web site of the current ERTS edition.

Submission Guidelines and Notification dates

Nominations for the award to be presented at the 2026 edition of ERTS should be mailed to the ERTS-2026 Program Committee Chair (mohamed.kaaniche@laas.fr), no later than 11:59pm CET on November the 2nd, 2025.

Make sure the words ERTS PhD Award are in the subject line.

You will receive an acknowledgement of receipt (try again if you don’t). If you have difficulties with the size of the file including the nomination package, you may provide a URL link for retrieval in your email. The winning work will be announced by End-December 2025.

Insérer ici un formulaire de soumission vers le mail du comité choisi, non visible.

Ajouter l’option ajouter un pdf, collecte site mail + envois mail.
Vérifier la limite du poids du pdf, demander un ancien dossier pour vérifier (le plus lourd).

ERTS 2026 PhD Dissertation Award Winner

Marco Barletta, Federico II University of Naples, Italy

PhD Title : Mixed-Criticality Orchestration of Real-time Containerized Systems

Advisor : Marcello Cinque

Defense date : 17/02/2025

 

Bio:

Dr. Marco Barletta earned in 2025 his Ph.D. in Information Technology and Electrical Engineering from the Federico II University of Naples, Italy.  Currently, he serves as a Senior Research Engineer at the Huawei Technologies R&D Edinburgh Research Center, where he drives applied research in cloud infrastructures for AI.  With a research background in dependability assessment of real-time and mixed-criticality systems, his main expertise spans cloud and edge architectures – from high-performance computing systems to embedded devices and Multi-Processor System-on-Chip.

 

PhD Abstract: 

As critical computing systems employed in industry verticals grow increasingly complex, hardware components are replaced with software ones that demand greater computational resources. Hence, embedded systems are evolving into more powerful mixed-criticality platforms. Cloud native technologies are an appealing solution to automate component management  across such mixed-criticality platforms and the edge infrastructure to increase flexibility, interoperability, and scalability. However, they were not designed to meet the heterogeneity of hardware and non-functional requirements of industrial settings.  Dr. Barletta’s research investigates whether current container orchestration systems meet the requirements of critical systems, and introduces mixed-criticality orchestration to address their limitations. His dissertation makes three key contributions: i) it introduces a model for mixed-criticality orchestration, ii) it performs a failure and timing analysis to assess the behavior of container orchestration systems in non-nominal conditions, and iii) it proposes a set of solutions based on the model to improve the resilience, timeliness, and isolation from interference for both container orchestration and containers.  The analysis reveals that even a single error can cause overloads and disrupt an entire cluster, whereas high orchestration loads can cause delays of tens of seconds in scaling services or handling failures, threatening service level objectives (SLOs). The proposed solutions include designs and methods for mixed-criticality orchestration, which builds upon the concepts of node assurance and service and pod criticality to differentiate the management of critical services when orchestrating, placing, and running them. The implemented prototypes demonstrate that mixed-criticality orchestration improves the resilience of critical services by providing stable orchestration times, and improved timing and failure isolation for critical containers.

 

Runner up / Honorary Mention :

Iryna de Albuquerque Silva, ONERA 

PhD Title : Certifiable and efficient implementation of neural networks on embedded safety-critical real-time systems

Advisors: Claire Pagetti (ONERA), Thomas Carle (IRIT)

Defense date : 16/07/2024