جست‌وجوی استاد و پژوهشگر

• Evolutionary Algorithms
• Machine Learning
• Optimization
• +۷ مورد دیگر

Giovanni Iacca is an Associate Professor at the University of Trento's Department of Information Engineering and Computer Science (DISI), where he serves as Coordinator of the Master's Degree in Computer Science and Deputy Director of the Information Engineering and Computer Science Doctoral School. He leads the Distributed Intelligence and Optimization Lab (DIOL) and teaches courses including Computer Architectures, Introduction to Machine Learning, Bio-Inspired Artificial Intelligence, and Optimization Techniques across multiple academic programs. PhD in Computer Science, University of Jyväskylä, Finland (2011) MSc in Computer Engineering, Technical University of Bari, Italy (2006) Professor Iacca's research focuses on the intersection of evolutionary computation, machine learning, and optimization with applications in distributed systems and robotics. His work spans from theoretical foundations of memetic computing and multi-objective optimization to practical implementations in soft robotics, embedded systems, and healthcare applications. Recent efforts emphasize interpretable AI, particularly in reinforcement learning contexts, where his team develops methods to make decision processes transparent while maintaining performance. His research bridges the gap between fundamental algorithmic development and real-world engineering challenges, with over 15 years of industrial experience in optimization applied to engineering, logistics, and scheduling. Analysis of his recent publications reveals a strong trend toward interpretable AI systems, particularly in reinforcement learning contexts, with significant contributions to federated learning optimization, evolutionary neural architecture search, and applications in healthcare scheduling. His work consistently combines evolutionary algorithms with modern machine learning techniques to solve complex optimization problems across diverse domains including soft robotics, batteryless edge computing, and supply chain management. Scientific Awards: EvoApplications Best Paper Award (2017) UKCI AWARENESS Best Paper Award (2012) IEEE CIS Outstanding Student-Paper Award (2011) Professor Iacca actively supervises a large research group with numerous PhD students across multiple doctoral programs, including Information Engineering and Computer Science, Industrial Innovation, and the National PhD in Artificial Intelligence for Society. His lab has secured significant research funding through collaborations with industry partners and international research consortia. Recent grants support work on interpretable reinforcement learning, federated optimization, and applications of evolutionary computation in healthcare and robotics. He has also been appointed to editorial roles for prestigious journals including IEEE Transactions on Evolutionary Computation and Evolutionary Intelligence. The Distributed Intelligence and Optimization Lab (DIOL) under Professor Iacca's leadership comprises over 30 researchers including postdocs, PhD students, and master's students. The lab maintains strong international collaborations and has developed specialized expertise in evolutionary computation, interpretable AI, and optimization for embedded systems. Current projects include work on the EIC Pathfinder Challenge "Awareness Inside," development of methods for batteryless edge intelligence, and applications of evolutionary algorithms to healthcare scheduling problems.

• Numerical Analysis
• Multivariate Approximation Theory
• Polynomial Interpolation
• +۵ مورد دیگر

Marco Vianello is a Full Professor of Numerical Analysis at the Department of Mathematics of the University of Padova, Italy. He has held this position since May 2017, following his tenure as Associate Professor (2001-2016) and Lecturer (1993-2000) at the same institution. Professor Vianello is Co-Editor-in-Chief of the Journal of Approximation Software (2024-) and was previously Managing Editor of Dolomites Research Notes on Approximation (2008-2022). He is the co-founder of the CAA: Padova-Verona Research Group on Constructive Approximation and Applications and an active member of the national research networks RITA (Rete ITaliana di Approssimazione) and SIMAI ANA&A Activity Group. Professor Vianello's research focuses on Multivariate Approximation Theory, with particular emphasis on Polynomial Interpolation, Numerical Quadrature and Cubature, Meshless Approximation, and Polynomial Optimization. His work includes the development of special point sets such as Padua Points, Approximate Fekete Points, Subperiodic Trigonometric Points, and CATCH (Caratheodory-Tchakaloff) Points. His research has significant applications in numerical methods for PDEs, computational mechanics, and scientific computing. His research has been recognized with the Optimization Letters Best Paper Award (2020), and his work has accumulated approximately 3,700 citations on Google Scholar. His algorithms have been implemented in several major software packages including ZEMAX OpticStudio, CP2K for molecular dynamics, and the Chebfun package. Optimization Letters Best Paper Award (2020) for 'Quadrature Based Polynomial Optimization' Approximately 3,700 citations on Google Scholar Approximately 1,200 citations by about 700 authors on MathSciNet Implementation of algorithms in ZEMAX OpticStudio, CP2K, Chebfun, and other scientific software Professor Vianello has advised 3 Ph.D. students to completion and approximately 60 B.Sc. and Master's dissertations. As a research coordinator from 2003-2025, he has secured approximately 150 kEuros in funding, supporting an average of 5 researchers per year. He has served on numerous hiring and evaluation committees, including the ASN (Italian National Scientific Habilitation) Committee in Numerical Analysis (2024-26) and hiring committees for professorships at Padova and Calabria Universities. His research group, the CAA: Padova-Verona Research Group on Constructive Approximation and Applications, maintains an active international collaboration network with researchers from institutions including Lawrence Livermore National Laboratory, Jagellonian University, University of Calgary/Verona, University of Toulouse, Colorado School of Mines, ANU Canberra, Indiana University, and several others across Europe, North America, and Asia.