Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
Este repositorio recoge el código desarrollado para mi Trabajo de Fin de Grado (TFG) en Física en la Universidad Europea de Madrid. Este código da soporte a los experimentos y resultados presentados en el mismo. El código está desarrollado en el entorno de Google Colab y utiliza Qiskit y técnicas de Machine Learning para predecir la fidelidad de un estado teleportado en entornos ruidosos, empleando IA Explicable (XAI) para analizar qué tipos de ruido afectan más al protocolo. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- This repository contains the code developed for my Bachelor's Thesis (TFG) in Physics at the Universidad Europea de Madrid. This code supports the experiments and results presented therein. The code is developed in the Google Colab environment and utilizes Qiskit and Machine Learning techniques to predict the fidelity of a teleported state in noisy environments, employing Explainable AI (XAI) to analyze which types of noise most significantly affect the protocol.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduNov 2, 2026
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
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