{"id":1170,"date":"2025-08-11T20:23:43","date_gmt":"2025-08-11T20:23:43","guid":{"rendered":"https:\/\/artisteconference.polito.it\/?page_id=1170"},"modified":"2025-10-13T06:45:28","modified_gmt":"2025-10-13T06:45:28","slug":"conference-awards","status":"publish","type":"page","link":"https:\/\/artisteconference.polito.it\/index.php\/home\/conference-awards\/","title":{"rendered":"Conference Awards"},"content":{"rendered":"\n

OUTSTANDING PAPER PRESENTATION<\/strong><\/h2>\n\n\n\n

The Scientific Committee of ARTISTE2025 is pleased to announce the Outstanding Presentation Award.<\/p>\n\n\n\n

In each session, the best paper presentation will be selected by the international conference chairs. Authors nominated for this distinction will be officially invited to submit a full-length version of their conference contribution (Journal Paper) to the Special Issues organized by the Scientific Committee of ARTISTE2025.<\/p>\n\n\n\n

Minimum Requirements:<\/p>\n\n\n\n

\u2022 Candidates must submit at least an abstract of their contribution by the deadline (August 31, 2025).<\/p>\n\n\n\n

\u2022 The presentation must be delivered during the assigned session.<\/p>\n\n\n\n

Evaluation Criteria:<\/p>\n\n\n\n

\u2022 Scientific vision and background of the research<\/p>\n\n\n\n

\u2022 Demonstrated depth of knowledge and engagement with the topic<\/p>\n\n\n\n

\u2022 Clarity, scientific rigor, and completeness of the presentation<\/p>\n\n\n\n

\u2022 Proficiency in language and effectiveness in scientific communication<\/p>\n\n\n\n

\u2022 Adherence to the allotted presentation time<\/p>\n\n\n\n

\u2022 Ability to respond to audience questions effectively and confidently<\/p>\n\n\n\n

<\/div>\n\n\n\n

Outstanding Paper Presentation Award Winners<\/a><\/h3>\n\n\n\n
<\/div>\n\n\n\n
Special Session<\/strong><\/th>Winner name<\/strong><\/th>Title of the presentation<\/strong><\/th><\/tr><\/thead>
SS01<\/a><\/td>Joseph Harrish<\/a><\/td>Deep convolutional autoencoders and generative adversarial networks for vibration-based damage detection in nonlinear dynamical systems<\/td><\/tr>
SS02<\/a><\/td>Brett Story<\/a><\/td>Physics-Inspired, AI-Driven Bridge Strike Detection and Characterization<\/td><\/tr>
SS02<\/a><\/td>Valentina Giglioni<\/a><\/td>A population of laboratory-scale bridges for validating transfer learning in PBSHM<\/td><\/tr>
SS03 <\/a>& SS11<\/a><\/td>Yanda Shao<\/a><\/td>Discovering Interpretable Blast Loading Equations from Black-Box Machine Learning Models<\/td><\/tr>
SS04<\/a><\/td>Zhewen Huang<\/a><\/td>Modeling the chloride transport into cracked concrete through Physics-informed Neural Network<\/td><\/tr>
SS04<\/a><\/td>Lenganji Simwanda<\/a><\/td>Generative Design and Optimisation of Ultra-High-Performance Concrete Mixes Using Variational Autoencoders, Ensemble learning, and Genetic Algorithms<\/td><\/tr>
SS05<\/a><\/td>Riccardo Malacrida<\/a><\/td>MORL\u2013DB method. Declining Reinforcement Learning into the Structural Multi-Objective Optimisation context<\/td><\/tr>
SS06<\/a><\/td>Said Quqa<\/a><\/td>Leveraging InSAR archives for population-based structural health monitoring of bridges.<\/td><\/tr>
SS06<\/a><\/td>Tsukasa Mizutani<\/a><\/td>Estimation of Flexural Rigidity Distribution in Euler\u2013Bernoulli Beams: Numerical and Experimental Investigation using Acceleration Data and Physics-Informed Neural Networks<\/td><\/tr>
SS09<\/a><\/td>Tomoki Takizawa<\/a><\/td>Development of an Autonomous LLM-Based Agent for Fatigue Analysis of In-Service Bridge Reinforced Concrete Slabs Using FEM<\/td><\/tr>
SS10<\/a><\/td>Santiago Londono Lopez<\/a><\/td>Rotation-Independent Ground-Motion Framework: Data-Driven Clustering and Validation against Performance-Based Demand Metrics<\/td><\/tr>
SS10<\/a><\/td>Gerardo Sorrentino<\/a><\/td>Al-Driven Corrosion Quantification in Cementitious Materials for Structural Health Monitoring<\/td><\/tr>
SS13<\/a><\/td>Jonathan Melchiorre<\/a><\/td>Human-Guided Machine Learning for Structural and Architectural Design and Optimization of Gridshells<\/td><\/tr>
SS14<\/a><\/td>Roberta Di Bari<\/a><\/td>Development of a Novel Integrated Framework for Evolutionary Sustainability and Resilience Assessment of the Built Environment<\/td><\/tr>
SS14<\/a><\/td>Jana Olivo<\/a><\/td>Optimization of RC frame-shear wall buildings with variable wall height and layout<\/td><\/tr>
SS15<\/a><\/td>Yuan Ma<\/a><\/td>Design Optimization of Cable-stayed Bridges: Decoupling Strategy and Surrogate Modeling<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
<\/div>\n\n\n\n
<\/div>\n\n\n\n

JOHN HENRY HOLLAND PRIZE<\/strong><\/h2>\n\n\n\n
\"john<\/figure>
\n

The Scientific Committee of ARTISTE2025 is proud to announce the John Henry Holland Prize<\/strong>, established in memory of the pioneering American scientist and father of Genetic Algorithms (USA, 1929\u20132015). This prestigious award honors the Best Paper of the Conference<\/strong> and aims to recognize outstanding contributions from young researchers, designers, and engineers in the field of Artificial Intelligence applied to structural design and the civil construction sector.<\/p>\n\n\n\n

Eligibility Requirements:<\/strong>
Candidates must submit the full extended version<\/strong> of their conference paper by October 31st, 2025<\/strong>, to be considered for the award.<\/p>\n\n\n\n

Award and Recognition:<\/strong>
The winner of the John Henry Holland Prize will be announced on the official homepage of the ARTISTE2025 Conference. In addition, the awardee will receive an official invitation from the Scientific Committee to submit a full-length version of their work (Journal Paper) for inclusion in the Special Issues<\/strong> organized in conjunction with ARTISTE2025.<\/p>\n\n\n\n

Prize Committee:<\/strong>
The members of the John Henry Holland Prize Jury is composed of:<\/p>\n\n\n\n