Eduard Andrei Duta Costache

Personal Introduction

Edu’s academic background is in Computer Science, with a specialization in artificial intelligence, high-performance optimization, and physics-informed machine learning. He holds a BSc in Computer Engineering and an MSc in Artificial Intelligence from the University of Alicante, as well as an MSc in Machine Learning and Data Mining from Jean Monnet University. During his studies, he collaborated as a research assistant at the Department of Computer Science and Technology of the University of Alicante, where he developed high-performance metaheuristic algorithms for industrial material waste minimization (also known as the nesting problem). This work resulted in multiple peer-reviewed publications.

His technical skills include Python, PyTorch, C++, CUDA, and HPC tools. Within the GREENS project, He will develop deep learning models to improve Life Cycle Assessment workflows, supporting decision making in material selection, manufacturing processes, and environmental impact evaluation. My goal is to contribute to sustainable micro and nanorobotic technologies.

Project Introduction

Performance of a comprehensive Life Cycle Assessment (LCA) involving the conduct in-depth LCA, incorporating the 5R principles (Reduce, Recycle, Rethink, Repair, Reuse) from design to disposal and continuous design optimization for sustainability by rethinking and continuously optimize the design of nano/microrobots to enhance sustainability and reduce hazardous substance generation. In that regard, we aim towards an holistic sustainability assessment of developed materials and technologies, with social and costing assessment aspects integrated with environmental LCA for selected applications.