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DTSTART;TZID=Europe/Stockholm:20260701T140000
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UID:submissions.pasc-conference.org_PASC26_sess117@linklings.com
SUMMARY:MS5B - HPC for Society: Leveraging for Trust and Transparency
DESCRIPTION:Organizer(s): Tobias Hodel (University of Bern)\n\nHigh-Perfor
 mance Computing (HPC) is increasingly central to deploying trustworthy, tr
 ansparent, and accountable AI systems in critical societal domains. This s
 ession brings together four contributions showing how advanced computation
 al infrastructures strengthen public trust across areas such as health, ag
 riculture, transportation, and energy.\nThe first speaker introduces how m
 odel predictions influence decisions and demonstrates how deep learning co
 mbined with Explainable AI (XAI) enables transparent, real-time interpreta
 bility at scale using HPC. The second speaker addresses challenges in AI s
 ystem design and evaluation, highlighting how narrow benchmarking datasets
  can lead to misleading results and limit generalization.\nThe third prese
 ntation presents an HPC-enabled intelligent toll management framework inte
 grating real-time computer vision with blockchain to ensure transparent, a
 uditable, and tamper-resistant public infrastructure transactions. The fou
 rth contribution introduces HP2C-DT, a multi-tier digital twin architectur
 e for renewable energy systems, where HPC supports large-scale simulations
 , AI training, and probabilistic analysis to improve grid resilience and d
 ecision-making.\nTogether, these works show that HPC is not just about spe
 ed or scale, but a key enabler of transparency, robustness, and reproducib
 ility. By embedding AI in secure and computationally rigorous frameworks, 
 HPC helps build systems that society can trust.\n\nEnabling Trust, Transpa
 rency, and Accountability: A Blockchain and AI Framework for Transparent T
 oll Management\n\nTransparency, accountability, and trust are essential fo
 r AI systems deployment in public domains to ensure fair treatment and gai
 n public trust. Manual toll collection and legacy RFID-based e-payment sys
 tems create significant challenges including long queues, inconsistent tre
 atment, revenue leakag...\n\n\nShahid Islam and Natasha Nigar (UET, Lahore
 , Pakistan)\n---------------------\nBuilding Trust in AI-Driven Systems: S
 calable and Explainable Deep Learning Frameworks for Health and Agricultur
 e on HPC\n\nTransparency and interpretability are essential for deploying 
 AI systems in domains where decisions affect health, safety, and food secu
 rity. This talk presents an integrated approach to building trustworthy AI
  models for image-based classification by combining deep learning with Exp
 lainable Artific...\n\n\nNatasha Nigar (UET, Lahore, Pakistan)\n----------
 -----------\nHP2C-DT: A General-Purpose Multi-Tier Digital Twin Architectu
 re Applied to Renewable-Dominated Power Systems\n\nThe large-scale integra
 tion of renewable energy sources is transforming power systems, introducin
 g variability, uncertainty, and operational complexity. Traditional contro
 l approaches, designed for centralized generation, struggle to ensure stab
 ility and resilience in renewable-rich grids. This talk...\n\n\nFrancesc L
 ordan, Eduardo Iraola, Mauro Garcia-Lorenzo, and Rosa Badia (Barcelona Sup
 ercomputing Center)\n---------------------\nBeyond Benchmark Performance: 
 Trustworthy AI, Generalization, and Translational Impact in Scientific Com
 puting\n\nArtificial intelligence (AI) and machine learning are increasing
 ly used within high-performance computing workflows to accelerate scientif
 ic discovery, particularly in data-intensive domains such as drug discover
 y. However, strong benchmark performance does not guarantee scientific or 
 translational ...\n\n\nSally Ellingson (University of Kentucky)\n\nDomain:
  Climate, Weather, and Earth Sciences, Applied Social Sciences and Humanit
 ies, Engineering, Computational Methods and Applied Mathematics\n\nSession
  Chair: Tobias Hodel (University of Bern, Switzerland)
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