Find Academic Supervisors

• Electromagnetic Fields
• RFID Technology
• Internet of Things (IoT)
• +3 more

Luca Catarinucci is an Associate Professor in Electromagnetic Fields (ING-INF/02) at the University of Salento's Department of Innovation Engineering. He leads courses in Microwaves and Electromagnetic Solutions for Hi-Tech , focusing on IoT, RFID, and 3D-printed electronic devices. His research spans electromagnetic interactions with biological systems, RFID sensor integration, and additive manufacturing for high-frequency applications. He has co-authored over 200 publications, including 80+ journal articles and 4 book chapters, and holds patents in RFID technology. His work bridges academic research and industry applications, emphasizing practical solutions for wireless communication and environmental monitoring. Education: Laurea in Electrical Engineering from the University of Perugia (1998). Professional roles include Researcher at the University of Salento (2004–2015) and collaboration with ICEMB (Interuniversity Center for Electromagnetic Field Studies). His expertise includes electromagnetic simulation, antenna design, and IoT-enabled systems. Research interests: RFID technology, IoT infrastructure, microwave engineering, 3D-printed antennas, and electromagnetic characterization of novel materials. Projects include smart waste management systems, thermal comfort monitoring, and worker safety solutions using RFID and sensor networks. Labs/Teams: Part of the Department of Innovation Engineering's research groups focused on electromagnetic design, IoT, and additive manufacturing. Collaborates with industry partners on projects involving 3D-printed RF devices and energy-autonomous sensors.

• High Performance Computing
• Grid Computing
• Cloud Computing
• +7 more

Giovanni Aloisio is a Full Professor of Information Processing Systems at the Department of Innovation Engineering, University of Salento, Italy. He is a leading figure at the Euro-Mediterranean Center on Climate Change (CMCC), where he serves as Director of the Supercomputing Center and Director of the Scientific Computing and Operations (SCO) Division. He is also a member of CMCC’s Governance bodies, including the Strategic Council and Executive Committee. His research focuses on High Performance Computing (HPC) , grid and cloud computing , and distributed data management . He has played a pivotal role in major European and international initiatives such as the European Grid Forum (Egrid), the EU FP7 IS-ENES projects, the European Exascale Software Initiative (EESI), and the International Exascale Software Project (IESP). His work bridges advanced computing infrastructure with Earth system modeling and climate science. Recent publications highlight a strong trend toward integrating HPC simulations , big data analytics , and machine learning in climate science. His team develops tools like PyOphidia for scalable data analytics and explores AI-driven methods for weather and climate modeling, pandemic forecasting, and environmental data downscaling. The research spans interdisciplinary domains including climate modeling, epidemiology, and environmental health. He has authored over 100 peer-reviewed journal articles. His leadership in EU-funded projects and international working groups, such as the ENES HPC Task Force and the WCES Working Group, reflects his significant contributions to the scientific community. He leads the HPC laboratory at the University of Salento and oversees advanced computing operations at CMCC. His work supports large-scale scientific workflows, climate data spaces within the European Open Science Cloud, and the convergence of HPC, AI, and data analytics.

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +1 more

Giacomo Vitali is a Ph.D. candidate in Computer and Systems Engineering at the Politecnico di Torino , Department of Control and Computer Science (DAUIN), while also serving as a Lecturer at the same institution. His research focuses on Quantum Computing , Machine Learning , and Parallel and Distributed Systems . Education: M.Sc. in Physics of Fundamental Interactions (2018) from the University of Pisa Research: Pioneering hybrid quantum-classical algorithms for industrial applications, including BBQ-mIS and DEN models for graph problems and quantum hardware optimization Teaching: Contributing to courses on Quantum Hardware Design and Quantum Computing at the M.Sc. level, as well as undergraduate courses in Computer Science

Stefano QuerView profile

Associate Professor

• Computer Science
• Electrical Engineering
• Formal Methods
• +7 more

Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues

• Numerical Analysis
• Machine Learning
• Computational Mathematics
• +4 more

Elena Toscano is a researcher in the Department of Mathematics and Computer Science at the University of Palermo. She specializes in numerical analysis, machine learning, and computational mathematics, with a focus on mesh-free methods like Smoothed Particle Hydrodynamics (SPH) and applications to physics, engineering, and interdisciplinary fields. Teaching: Numerical Analysis (Master's in Informatics and Mathematics, 2025/2026) Research Areas: Signal/image processing, SPH consistency restoration, genetic algorithms for tomography, and mathematical-literary collaborations (e.g., Oulipo). Her publications span computational physics, machine learning, and mathematical modeling, emphasizing numerical stability and interdisciplinary innovation.

Ritamaria BucciarelliView profile

Adjunct Professor

• Natural Language Processing
• Computational Linguistics
• Digital Humanities
• +3 more

Ritamaria Bucciarelli is an Adjunct Professor at Ca' Foscari University of Venice, affiliated with the Department of Comparative Linguistic and Cultural Studies (DSLCC) and the Research Institute for Digital and Cultural Heritage. She holds a PhD in Language Sciences (2008) and multiple advanced degrees in Literature, Pedagogy, and Natural Sciences. Her research focuses on Natural Language Processing (NLP), Digital Intelligence, and computational linguistics, with projects involving quantum physics applications and digital text analysis. She has taught Italian linguistics and language courses internationally, including at the University of Pisa and LUISS Guido Carli. Her work includes developing tools like Acro Word and Type Race for automated text generation and translation. Awards include the ESB Level 3 English certification with Distinction (2019) and recognition as top-performing in an online teaching course (2002). She has led research teams in Italy and France, collaborating on projects such as sentiment analysis and digital text cloud workshops. Bucciarelli also served as a MIUR inspector for secondary schools and has extensive experience in blended learning and e-learning platform management.

• Numerical Analysis
• Domain Decomposition
• PDE-Constrained Optimization
• +7 more

Tommaso Vanzan is a Researcher at the Department of Mathematical Sciences "GL Lagrange" (DISMA) at Politecnico di Torino . He holds a PhD from the University of Geneva (2020) under Prof. Martin J. Gander and was a postdoctoral researcher at EPFL (2020-2023) under the CSQI Chair. His research focuses on iterative methods , optimization algorithms , and uncertainty quantification for PDE-constrained problems, with applications in Stokes-Darcy coupling and manifold-based machine learning . His recent work includes multilevel quadrature for risk-averse optimization and spectral coarse spaces for substructured Schwarz methods. He has received the SWICCOMAS Prize 2021 for computational methods. He contributes to the open-source GDGMatlab library for finite element and discontinuous Galerkin methods, emphasizing educational and research usability over high-performance computing. Future developments target generalized boundary conditions in DG formulations.

Werner NuttView profile

Professor

• Data Management
• Knowledge Representation
• Intelligent Information Extraction
• +3 more

Werner Nutt is a Professor at the Free University of Bozen-Bolzano , Italy, affiliated with the Faculty of Computer Science since 2005. He previously held academic positions as a Reader at Heriot-Watt University (2000-2005), Visiting Professor at Hebrew University of Jerusalem, and Research Scientist at DFKI (1992-2000). Current Role: Professor, Free University of Bozen-Bolzano Past Roles: Reader (Heriot-Watt), Visiting Professor (Hebrew University), Research Scientist (DFKI) Research Interests focus on Data Management , Knowledge Representation , and Intelligent Information Extraction , with emphasis on modeling Construction Processes and ensuring Data Quality . His work bridges Semantic Web technologies with Business Process Management , notably through the COCkPiT project (2017-present) for construction process optimization. Key Contributions include foundational work on Query Completeness in databases, SPARQL Reasoning , and Semantic Diagnostics . He has published extensively in venues like ISWC , BPM , and CIKM , with an h-index of 35 on Google Scholar. His 154+ publications span topics from Probabilistic XML to Construction Process Modeling .

• Numerical Analysis
• Optimal Control
• Finite Element Methods
• +9 more

Enrico Bertolazzi is an Associate Professor in Numerical Analysis at the University of Trento's Department of Industrial Engineering. He specializes in numerical methods for optimal control, finite element methods, sparse matrix computations, and symbolic computation. His work integrates advanced programming skills in C/C++, MATLAB, and other languages to develop computational tools for engineering and mathematical challenges. Bertolazzi's research addresses complex systems such as vehicle dynamics, trajectory optimization, and real-time simulations, with applications in automotive engineering, renewable energy, and robotics. Research Interests: Numerical Optimal Control and Trajectory Planning Finite Element/Finite Volume Methods for PDEs Sparse Matrix Algorithms Clothoid Curve Modeling Symbolic-Numeric Hybrid Techniques Vehicle Dynamics and Autonomous Systems Publications: Recent work focuses on real-time tire models, DAE index reduction, and autonomous vehicle path planning. His contributions span algorithm development, computational toolboxes (e.g., TrussMe-Fem), and interdisciplinary applications combining mathematics with engineering. Grants & Advising: Advises on optimal control, robotics, and simulation projects. Active in developing educational software like the virtual racing car championship platform. Labs/Teams: Involved in research groups focused on intelligent vehicles, computational mechanics, and numerical methods for industrial applications.

• Artificial Intelligence
• Bioinformatics
• Machine Learning
• +7 more

Enrico Blanzieri is an Associate Professor at the University of Trento's Department of Information Engineering and Computer Science. His research focuses on artificial intelligence, bioinformatics, quantum computing, machine learning, and computational biology. He actively contributes to interdisciplinary projects such as Vitis OneGenE for gene network analysis and quantum machine learning pipelines. His teaching includes courses like Algorithms for Bioinformatics, Quantum Machine Learning, and Data Mining. Blanzieri's work bridges theoretical foundations and practical applications, with notable contributions in quantum annealing-based algorithms, gene network expansion using distributed computing, and socially-competent artificial agents. His research integrates computational methods with biological systems, addressing challenges in precision agriculture and systems biology. His recent publications emphasize quantum machine learning advancements, causal role attribution in gene networks, and ethical AI frameworks for language models. Collaborative projects include the GENE@HOME volunteer computing initiative for bioinformatics tasks. Blanzieri also engages in educational activities, supervising courses that blend theoretical computer science with real-world applications.

Antonio BrogiView profile

Professor

• Service Computing
• Cloud Computing
• Fog Computing
• +4 more

Antonio Brogi is a Full Professor at the Department of Computer Science, University of Pisa. He leads the Service-Oriented, Cloud and Fog Computing (SOCC) research group and is actively involved in multiple editorial roles, including for Electronics , Heliyon Computer Science , and Journal of Computer Languages . His research focuses on cloud-edge computing, quantum software engineering, and formal methods for distributed systems. He chairs program committees for major conferences like ESOCC, ADAPTIVE, and IEEE ICWS. Research Interests: Service computing, fog computing, quantum software engineering, system coordination, resilience, and sustainability. He has pioneered declarative approaches for managing distributed systems and has contributed to frameworks like ECLYPSE and FREEDA. Teaching: Teaches Cloud Computing (BSc) and Advanced Software Engineering (MSc) at the University of Pisa. Supervises master's and bachelor's theses in related areas. Grants & Projects: Participated in EU-funded initiatives like SeaClouds and national projects DECLware and Through the Fog. Active in industry collaborations for cloud-edge infrastructure optimization.

Alfredo PulvirentiView profile

Professor

• Bioinformatics
• Biomedicine
• RNA Interference
• +9 more

Alfredo Pulvirenti is a Full Professor of Computer Science at the University of Catania, Italy. He holds a joint appointment with the Department of Clinical and Experimental Medicine and the Department of Mathematics and Computer Science. Born in 1974, he earned his Laurea (1999, summa cum laude), PhD (2003), and post-doc (2004) in Computer Science from the University of Catania. His academic career includes roles as Assistant Professor (2005-2014), Associate Professor (2014-2023), and Full Professor since 2023. His research bridges Bioinformatics and Biomedicine , focusing on RNA interference (microRNAs, long non-coding RNAs) via stochastic and network-based inference methods. Key contributions include subgraph matching , motif finding , and multiple network alignment using Monte Carlo techniques for analyzing biological networks . He also applies time series analysis to seismic and infrasonic signals through collaborations with Italy's National Institute of Geophysics and Volcanology (INGV). Recent publications highlight advancements in graph algorithms (e.g., MultiGraphMatch, ArcMatch) and systems biology tools like MITHrIL and SPECifIC. He co-directs the Jacob T. Schawartz International School for Scientific Research and leads national/regional projects on Bioinformatics and Big Data in Cancer . His group includes 3 researchers, 1 post-doc, and 3 PhD students in Complex Systems. Awards and Leadership : Best Paper Award at CBS 2009 Guest Editor for BMC Bioinformatics, Briefings in Bioinformatics, Elsevier Program Committee Member for major international conferences International Collaborations span institutions like NYU, Ohio State University Wexner Medical Center, Brown University, Tel Aviv University, Toronto University, and Università di Ancona.

Mihai Teodor LazarescuView profile

Associate Professor

• Artificial intelligence
• Capacitive sensors
• Embedded software
• +10 more

Dr. Mihai Teodor Lazarescu is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino , where he contributes to research and teaching activities. He is also a member of the PolitoBIOMed Lab (Biomedical Engineering Lab) and the Ambient Sensing and Processing research group. Scientific Affiliation: IEEE Member (2019-present) Editorial Roles: Guest Editor for SENSORS, ELECTRONICS, and ACM Transactions on Embedded Computing Systems His research interests focus on hardware acceleration for machine learning algorithms, particularly using FPGAs for data center and embedded applications. He works on high-level synthesis optimization flows, capacitive sensor design for indoor monitoring, and low-power embedded systems . His work intersects Internet of Things , Wireless Sensor Networks , and Machine Learning with applications in human localization, environmental monitoring, and industrial automation. Recent publications demonstrate expertise in neural network optimization , DSP resource sharing , and multi-FPGA allocation . His teaching spans Applied Electronics , Digital Electronic Design , and Embedded Systems Optimization across bachelor's and master's programs in Electronic Engineering and Computer Engineering . Patents: Noise cancellation for single-plate capacitive sensors Capacitive sensor for space change detection Projects: Scientific Manager for Horizon 2020-S2RJU project (2018)

Giovanni IaccaView profile

Researcher

• Machine Learning
• Evolutionary Algorithms
• Optimization
• +5 more

Giovanni Iacca is affiliated with the University of Trento , where he contributes to research in computational intelligence and optimization. His work spans evolutionary algorithms, memetic computing, and constrained optimization, often intersecting with engineering and applied machine learning. Research interests include Memetic Computing Evolutionary Algorithms Optimization Problems Neural Architecture Design Social Network Analysis Sensor Networks His publications reveal a focus on hybridizing evolutionary methods with adaptive strategies (e.g., Super-fit Multicriteria Adaptive Differential Evolution ), constrained optimization techniques (e.g., Memetic Viability Evolution ), and applications in sensor networks and social systems. He frequently collaborates with researchers like Ferrante Neri, E. Mininno, and D. Floreano.

Marco DaddaView profile

Associate Professor

• Animal Cognition
• Behavioral Asymmetries
• Lateralized Brain Functions
• +3 more

Marco Dadda is an Associate Professor at the Department of General Psychology, University of Padova. His research focuses on the evolution of behavioral asymmetries and lateralized brain functions in vertebrates, alongside studies on animal cognition. He investigates mechanisms underlying perception, learning, and decision-making in species like zebrafish, guppies, and plants. Key interests include lateralization costs/benefits, numerical cognition in fish, and environmental enrichment effects. Research highlights include groundbreaking work on plant communication via volatile compounds and perceptual completion in pea plants. His studies on zebrafish explore early learning, anxiety modulation through environmental factors, and operant conditioning methodologies. He also examines laterality's role in spatial navigation and simultaneous task performance across species. Publications consistently bridge behavioral biology with neuroethology, emphasizing cross-species comparisons (e.g., plant-fish cognition parallels). Ongoing work investigates how developmental experiences (light exposure, predation cues) shape lateralization patterns and cognitive capabilities. His lab employs innovative tools like automated behavioral tracking systems and minimally invasive testing protocols for neonatal fish.