4 Search Results for "Soto, Ricardo"

Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.15
Integrating Human-In-The-Loop AI to Tackle Space Communication Delay Challenges

Authors: Nikos Mavrakis, Effie Lai-Chong Law, and Hubert P. H. Shum

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
Deep space missions face significant communication delays that disrupt both operational workflows and psychological support for crew members. Unlike low Earth orbit operations, delays ranging from several minutes to nearly an hour make real-time communication with mission control infeasible, forcing crews to act with greater independence under uncertain conditions. This position paper examines how human-in-the-loop AI, digital twins, and edge AI can be integrated to mitigate these delays while maintaining astronaut autonomy and engagement. We argue that human-in-the-loop AI enables decision-making processes that are responsive to local context while remaining adaptable to changing mission demands. Digital twins offer real-time simulation and predictive modelling capabilities, allowing astronauts to explore options and troubleshoot without waiting for ground input. Edge AI brings computation closer to data sources, enabling low-latency inference onboard spacecraft for time-critical decisions. These ideas are explored through two use cases: using deepfakes to support emotionally resonant communication with loved ones, and applying visual-language models for onboard fault diagnosis and adaptive task replanning. We conclude with reflections on system design challenges under constrained and high-stakes conditions.
Cite as

Nikos Mavrakis, Effie Lai-Chong Law, and Hubert P. H. Shum. Integrating Human-In-The-Loop AI to Tackle Space Communication Delay Challenges. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 15:1-15:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mavrakis_et_al:OASIcs.SpaceCHI.2025.15,
  author =	{Mavrakis, Nikos and Law, Effie Lai-Chong and Shum, Hubert P. H.},
  title =	{{Integrating Human-In-The-Loop AI to Tackle Space Communication Delay Challenges}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{15:1--15:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.15},
  URN =		{urn:nbn:de:0030-drops-240051},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.15},
  annote =	{Keywords: Human-in-the-loop AI, communication delays, human spaceflight}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.16
PrintTalk: A Language for Constraint-Based 3D Modelling

Authors: Jef Jacobs, Wolfgang De Meuter, and Jens Nicolay

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Programmatic CAD (PCAD) is an emerging alternative to traditional visual CAD software. However, state-of-the-art PCAD tools have limited or no support for constraints. Consequently, these tools depend solely on parametrisation for variability, reusability, and composition of shapes. This leads to problems such as parameter explosion, leaky compositional abstraction, and prevents a declarative approach to defining spatial patterns (linear, grid, circular, etc.) for the constituents of a composition. This paper describes the design of PrintTalk, a PCAD language that supports 3D modelling by composing shapes and expressing relations between them using first-class constraints. Evaluating PrintTalk against state-of-the-art PCAD tools demonstrates that its expressive abstraction and composition mechanisms facilitate the design and promotes the reuse of shapes.
Cite as

Jef Jacobs, Wolfgang De Meuter, and Jens Nicolay. PrintTalk: A Language for Constraint-Based 3D Modelling. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 16:1-16:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{jacobs_et_al:LIPIcs.CP.2025.16,
  author =	{Jacobs, Jef and De Meuter, Wolfgang and Nicolay, Jens},
  title =	{{PrintTalk: A Language for Constraint-Based 3D Modelling}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{16:1--16:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.16},
  URN =		{urn:nbn:de:0030-drops-238775},
  doi =		{10.4230/LIPIcs.CP.2025.16},
  annote =	{Keywords: Programmatic 3D Modelling, PCAD, Domain specific language, Constraints}
}
Document
Academic Track
DOI: 10.4230/OASIcs.SAIA.2024.7
Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track)

Authors: Christoph Tobias Wirth, Mihai Maftei, Rosa Esther Martín-Peña, and Iris Merget

Published in: OASIcs, Volume 126, Symposium on Scaling AI Assessments (SAIA 2024)

Abstract
The development of AI technologies leaves place for unforeseen ethical challenges. Issues such as bias, lack of transparency and data privacy must be addressed during the design, development, and the deployment stages throughout the lifecycle of AI systems to mitigate their impact on users. Consequently, ensuring that such systems are responsibly built has become a priority for researchers and developers from both public and private sector. As a proposed solution, this paper presents a blueprint for AI ethics assessment. The blueprint provides for AI use cases an adaptable approach which is agnostic to ethics guidelines, regulatory environments, business models, and industry sectors. The blueprint offers an outcomes library of key performance indicators (KPIs) which are guided by a mapping of ethics framework measures to processes and phases defined by the blueprint. The main objectives of the blueprint are to provide an operationalizable process for the responsible development of ethical AI systems, and to enhance public trust needed for broad adoption of trusted AI solutions. In an initial pilot the blueprinted for AI ethics assessment is applied to a use case of generative AI in education.
Cite as

Christoph Tobias Wirth, Mihai Maftei, Rosa Esther Martín-Peña, and Iris Merget. Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track). In Symposium on Scaling AI Assessments (SAIA 2024). Open Access Series in Informatics (OASIcs), Volume 126, pp. 7:1-7:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{wirth_et_al:OASIcs.SAIA.2024.7,
  author =	{Wirth, Christoph Tobias and Maftei, Mihai and Mart{\'\i}n-Pe\~{n}a, Rosa Esther and Merget, Iris},
  title =	{{Towards Trusted AI: A Blueprint for Ethics Assessment in Practice}},
  booktitle =	{Symposium on Scaling AI Assessments (SAIA 2024)},
  pages =	{7:1--7:19},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-357-7},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{126},
  editor =	{G\"{o}rge, Rebekka and Haedecke, Elena and Poretschkin, Maximilian and Schmitz, Anna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SAIA.2024.7},
  URN =		{urn:nbn:de:0030-drops-227478},
  doi =		{10.4230/OASIcs.SAIA.2024.7},
  annote =	{Keywords: Trusted AI, Trustworthy AI, AI Ethics Assessment Framework, AI Quality, AI Ethics, AI Ethics Assessment, AI Lifecycle, Responsible AI, Ethics-By-Design, AI Risk Management, Ethics Impact Assessment, AI Ethics KPIs, Human-Centric AI, Applied Ethics}
}
Document
DOI: 10.4230/LIPIcs.CP.2021.26
A Job Dispatcher for Large and Heterogeneous HPC Systems Running Modern Applications

Authors: Cristian Galleguillos, Zeynep Kiziltan, and Ricardo Soto

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
High-performance Computing (HPC) systems have become essential instruments in our modern society. As they get closer to exascale performance, HPC systems become larger in size and more heterogeneous in their computing resources. With recent advances in AI, HPC systems are also increasingly being used for applications that employ many short jobs with strict timing requirements. HPC job dispatchers need to therefore adopt techniques to go beyond the capabilities of those developed for small or homogeneous systems, or for traditional compute-intensive applications. In this paper, we present a job dispatcher suitable for today’s large and heterogeneous systems running modern applications. Unlike its predecessors, our dispatcher solves the entire dispatching problem using Constraint Programming (CP) with a model size independent of the system size. Experimental results based on a simulation study show that our approach can bring about significant performance gains over the existing CP-based dispatchers in a large or heterogeneous system.
Cite as

Cristian Galleguillos, Zeynep Kiziltan, and Ricardo Soto. A Job Dispatcher for Large and Heterogeneous HPC Systems Running Modern Applications. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 26:1-26:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{galleguillos_et_al:LIPIcs.CP.2021.26,
  author =	{Galleguillos, Cristian and Kiziltan, Zeynep and Soto, Ricardo},
  title =	{{A Job Dispatcher for Large and Heterogeneous HPC Systems Running Modern Applications}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{26:1--26:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.26},
  URN =		{urn:nbn:de:0030-drops-153171},
  doi =		{10.4230/LIPIcs.CP.2021.26},
  annote =	{Keywords: Constraint programming, HPC systems, heterogeneous systems, large systems, on-line job dispatching, resource allocation}
}
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