Learning Time-Series Data of Industrial Design Optimization using Recurrent Neural Networks. - Sneha Saha; Thiago Rios; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck; Xin Yao 001; Zhao Xu 001; Patricia Wollstadt (ICDM Workshops, 2019)

On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization. - Thiago Rios; Bernhard Sendhoff; Stefan Menzel; Thomas Bäck; Bas van Stein (SSCI, 2019)

Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders. - Thiago Rios; Patricia Wollstadt; Bas van Stein; Thomas Bäck; Zhao Xu 001; Bernhard Sendhoff; Stefan Menzel (SSCI, 2019)

Optimal Evolutionary Optimization Hyper-parameters to Mimic Human User Behavior. - Sneha Saha; Thiago Rios; Leandro L. Minku; Xin Yao 001; Zhao Xu 001; Bernhard Sendhoff; Stefan Menzel (SSCI, 2019)

Feature Visualization for 3D Point Cloud Autoencoders. - Thiago Rios; Bas van Stein; Stefan Menzel; Thomas Bäck; Bernhard Sendhoff; Patricia Wollstadt (IJCNN, 2020)

On the Performance of Oversampling Techniques for Class Imbalance Problems. - Jiawen Kong; Thiago Rios; Wojtek Kowalczyk; Stefan Menzel; Thomas Bäck (PAKDD (2), 2020)

Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds. - Thiago Rios; Jiawen Kong; Bas van Stein; Thomas Bäck; Patricia Wollstadt; Bernhard Sendhoff; Stefan Menzel (SSCI, 2020)

On the Performance of Oversampling Techniques for Class Imbalance Problems. - Jiawen Kong; Thiago Rios; Wojtek Kowalczyk; Stefan Menzel; Thomas Bäck (Zenodo, 2020)

Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization. - Thiago Rios; Bas van Stein; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (3DV, 2021)

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders. - Thiago Rios; Bas van Stein; Patricia Wollstadt; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (CEC, 2021)

Exploiting Generative Models for Performance Predictions of 3D Car Designs. - Sneha Saha; Thiago Rios; Leandro L. Minku; Bas van Stein; Patricia Wollstadt; Xin Yao 001; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (SSCI, 2021)

Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation. - Thiago Rios; Bas van Stein; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (IEEE Trans. Evol. Comput., 2022)

Large Language and Text-to-3D Models for Engineering Design Optimization. - Thiago Rios; Stefan Menzel; Bernhard Sendhoff (SSCI, 2023)

Prompt Evolutionary Design Optimization with Generative Shape and Vision-Language models. - Melvin Wong; Thiago Rios; Stefan Menzel; Yew Soon Ong (CEC, 2024)

Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model. - Melvin Wong; Thiago Rios; Stefan Menzel; Yew Soon Ong (CoRR, 2024)

LLM2FEA: Discover Novel Designs with Generative Evolutionary Multitasking. - Melvin Wong; Jiao Liu; Thiago Rios; Stefan Menzel; Yew Soon Ong (CoRR, 2024)

From Idea to CAD: A Language Model-Driven Multi-Agent System for Collaborative Design. - Felix Ocker; Stefan Menzel; Ahmed Sadik; Thiago Rios (CoRR, 2025)

Controlled Agentic Planning & Reasoning for Mechanism Synthesis. - João Pedro Gandarela de Souza; Thiago Rios; Stefan Menzel; André Freitas (CoRR, 2025)

LLM-to-Phy3D: Physically Conform Online 3D Object Generation with LLMs. - Melvin Wong; Yueming Lyu; Thiago Rios; Stefan Menzel; Yew-Soon Ong (CoRR, 2025)