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Lukas Hindemith, Anna-Lisa Vollmer, Christiane Wiebel, Heiko Wersing, Britta Wrede , "Improving HRI through robot architecture transparency", International Journal of Social Robotics, 2025.
AbstractOne ongoing challenge in human-robot interaction design is minimizing user misunderstandings and confusion. While engineers constantly improve the reliability of robots, the user’s mental model about robots and their limitations have to be addressed as well. In this work, we investigate ways to improve the human understanding about robots. For this, we propose FAMILIAR – FunctionAl user Mental model by Increased LegIbility ARchitecture, a transpa...
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Catalin-Viorel Dinu, Yash J. Patel, Xavier Bonet-Monroig, Hao Wang , "An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise", GECCO '25: Proceedings of the Genetic and Evolutionary Computation Conference Pages 710 - 718 https://doi.org/10.1145/3712256.3726352, 2025.
AbstractThe Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) is one of the most advanced algorithms in numerical black-box optimization. For noisy objective functions, several approaches were proposed to mitigate the noise, e.g., re-evaluations of the same solution or adapting the population size. In this paper, we devise a novel method to adaptively choose the optimal re-evaluation number for function values corrupted by additive Gaussian wh...
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Xavier Bonet-Monroig , "Quantum (computing) needs you! Quantum (computing) wants you!", GECCO 2025 Evolutionary Computation in Practice workshop, 2025.
AbstractIn this talk I will try to convice you that the quantum computing community is in urgent need for your help, the evoluationary and optimization community. I will start with a basic introduction of quantum computation, with special attention to what makes them stricktly more powerful than classical computers (with caveats). Next, I will show how poorly classical optimization algorithms have been used in the field, and our attempt at solving this...
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Mikel Garcia de Andoin, Alberto Bottarelli, Pranav Chandarana, Koushik Paul, Xi Chen, Mikel Sanz, Philipp Hauke , "Symmetry-enhanced Counterdiabatic Quantum Algorithm for Qudits", Physical Review Research, 2025.
AbstractQubit-based variational quantum algorithms have undergone rapid development in recent years but still face several challenges. In this context, we propose a symmetry-enhanced digitized counterdiabatic quantum algorithm utilizing qudits instead of qubits. This approach offers three types of compression as compared to with respect to conventional variational circuits. First, compression in the circuit depth is achieved by counterdiabatic protocols....
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Alberto Bottarelli, Sebastian Schmitt, Philipp Hauke , "Inequality constraints in variational quantum circuits with qudits", Physical Review Research , 2025.
AbstractQuantum optimization is emerging as a prominent candidate for exploiting the capabilities of near-term quantum devices. Many application-relevant optimization tasks require the inclusion of inequality constraints, usually handled by enlarging the Hilbert space through the addition of slack variables. This approach, however, requires significant additional resources especially when considering multiple constraints. Here, we study an alterna...
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Andreas Neofytou, Thiago de Jesus de Araujo Rios, Mariusz Bujny, Stefan Menzel, Hyunsun Alicia Kim , "Automatic differentiation-based level set topology optimization for noise minimization in 3D domains considering acoustic-structure interaction", Structural and Multidisciplinary Optimization, 2025.
AbstractThe reduction of vehicle interior noise is one of the important considerations in vehicle design and has become an active research topic in recent years. In this paper, we propose a modularized level set topology optimization (mLSTO) methodology to address noise minimization. One of the main contributions of this work is to allow for more design freedom of the vehicle body compared to previous works in which only size parameters of the vehicle pa...
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Christoph Bergmeir, Frits de Nijs, Evgenii Genov, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John Betts, Quang Bui, Nam Trong Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta-Camara, Yogesh Pipada Sunil Kumar, Alejandro Rosales-Perez, Julian Ruddick, Akylas Stratigakos, Peter Stuckey, Guido Tack, Isaac Triguero, Rui Yuan , "Predict+Optimize Problem in Renewable Energy Scheduling", IEEE Access, vol. 13, pp. 60064-60087, 2025.
AbstractAlgorithms that involve both forecasting and optimization are at the core of solutions to many difficult real-world problems, such as in supply chain (inventory optimization), traffic, and in the transition towards carbon-free energy generation in battery/load/production scheduling in sustainable energy systems. Typically, in these scenarios we want to solve an optimization problem that depends on unknown future values, which therefore need to be...
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Amirreza Razmjoo, Sylvain Calinon, Michael Gienger, Fan Zhang , "CCDP: Composition of Conditional Diffusion Policy for Interactive Sampling Refinement", Arxiv, 2025.
AbstractLearning from demonstrations offers a promising approach in robotics by enabling systems to learn directly from data without requiring explicit models, simulations, or detailed task definitions. During inference, actions are sampled from the learned distribution and executed on the robot. However, sampled actions may fail for various reasons, and simply repeating the sampling step until a successful action is obtained can be inefficient. In this ...
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Chao Wang , "Human-AI Interaction: From Connected Vehicle, Autonomous Driving to Robots", Report at Shanghai University (Oct 28) & Zhejiang University (Oct 25)), 2025.
AbstractThe goal of artificial intelligence should be to enhance human capabilities rather than replace humans, as humans and intelligent systems excel in different areas, allowing for effective complementarity. To achieve natural and seamless interaction between humans and intelligent systems, we need to design and develop cutting-edge interaction methods for human-machine collaboration This presentation will introduce innovations in human-AI interacti...
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Felix Ocker, Jörg Deigmöller, Pavel Smirnov, Julian Eggert , "A Grounded Memory System For Smart Personal Assistants", Extended Semantic Web Conference - workshop on LLM-Integrated Knowledge Graph Generation from Text (Text2KG), 2025.
AbstractA wide variety of applications — ranging from cognitive assistants for dementia patients to robotics — demand a robust memory system grounded in reality. With this paper, we propose a memory system consisting of three components. First, we combine Vision Language Models for image captioning and entity disambiguation with Language Models for precise entity extraction. Second, a knowledge graph is integrated with a vector store to efficiently manag...
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