جست‌وجوی استاد و پژوهشگر

• Machine Learning
• AI Ethics
• Algorithmic Accountability
• +۳ مورد دیگر

Irene Unceta Mendieta is an Assistant Professor (tenure track) at ESADE Business School , affiliated with the Department of Operations, Innovation and Data Sciences and the Institute for Data-Driven Decisions . Her work focuses on machine learning, AI ethics, and algorithmic accountability, contributing to UN Sustainable Development Goals through technology-driven solutions. Research Specialization: Machine learning systems, decision behavior analysis, and resource optimization in healthcare and social services. Projects: Principal investigator in the ESADE D3 Institute (2022–2025), funded by the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR). Her research explores topics like scalable machine learning replication for accountability, ethical AI frameworks, and computational approaches to home care resource allocation. She has published widely in journals like Journal of Machine Learning Research and IEEE Access , with over 46 citations and an h-index of 5. Key research themes include: Algorithmic transparency and risk mitigation Environmental adaptation in learning systems MaxSAT-based optimization for social services

• Proof Complexity
• Computational Complexity
• Algorithmics
• +۵ مورد دیگر

Ilario Bonacina is a Lecturer at the Department of Computer Science within the College of Computer Science of Barcelona (FIB) at the Polytechnic University of Catalonia . His research focuses on Proof Complexity , Computational Complexity , and Algorithmics , particularly in Polynomial Calculus and MaxSAT Optimization . Education: Laurea in Mathematics, Laurea Specialistica in Mathematics, and Doctorate from UPC. Research Interests include proof systems (Sherali-Adams, Nullstellensatz), algebraic methods, and theoretical computer science. Recent publications analyze complexity bounds and optimization algorithms. Scientific Awards include recognition for Best Italian PhD Theses in Theoretical Computer Science. He participates in competitive R+D+i projects like the State Plan for Scientific Research and Innovation.

• Computational Complexity
• SAT Solvers
• MaxSAT Algorithms
• +۳ مورد دیگر

M. Luisa Bonet Carbonell is a researcher in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). Her work focuses on computational complexity, SAT and MaxSAT solvers, proof systems, and algorithmic optimization. She has extensive collaborations within the LOGPROG and ALBCOM research groups, contributing to projects like TASSAT3 and MULOG-2. Her research spans theoretical computer science, with emphases on proof complexity, polynomial calculus, and the analysis of industrial SAT instances. Notable contributions include studies on Sherali-Adams and Nullstellensatz proof systems, as well as the fractal dimension of SAT formulas. Over 90 publications include articles in Artificial Intelligence , Journal of Computer and System Sciences , and conferences like SAT and IJCAI. Her work bridges theoretical foundations with practical applications, such as improving MaxSAT algorithms and analyzing community structures in problem instances.