Find Academic Supervisors

• GPU Acceleration
• Embedded Systems
• Autonomous Vehicles
• +6 more

Nicola Capodieci is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia, specializing in Information Processing Systems (IINF-05/A). He actively teaches multiple courses including Object-Oriented Programming, Web Technologies, and General Computer Science across Computer Science and Mathematics degree programs. His research interests focus on GPU acceleration for embedded systems, autonomous vehicles, and real-time computing. Dr. Capodieci's work addresses critical challenges in heterogeneous computing platforms, particularly for automotive applications and smart city infrastructure. His research bridges theoretical computer science with practical applications in autonomous driving and urban mobility systems. Analysis of his recent publications reveals a strong focus on optimizing GPU performance for latency-sensitive applications, particularly in autonomous vehicles. His work spans path planning algorithms, memory interference management, and real-time scheduling on heterogeneous platforms. A significant portion of his research addresses practical implementation challenges in embedded systems where computational resources are constrained but timing predictability is critical. Dr. Capodieci's teaching portfolio demonstrates expertise in both foundational programming concepts and advanced topics in web technologies. His courses emphasize practical implementation skills while covering theoretical foundations of object-oriented programming, web development frameworks, and computational thinking.

• Industrial robotics
• Teleoperation
• Surgical robotics
• +6 more

Riccardo Muradore is an Associate Professor at the University of Verona in the Department of Engineering for Innovation Medicine, within the Engineering and Physics section. His academic work focuses on robotics, control systems, and automation technologies with applications across various domains including industrial, surgical, and autonomous vehicle systems. Professor Muradore's research spans several key areas in robotics and control engineering: Industrial robotics and automation systems Teleoperation techniques for remote control of robotic systems Surgical robotics for medical applications Control and systems theory fundamentals Process control and fault detection methodologies Adaptive Optics technologies Unmanned Aerial and Ground Vehicles development His research is supported by numerous national and European projects as well as industry contracts, with notable projects including SARAS (Smart Autonomous Robotic Assistant Surgeon), MURAB (MRI and Ultrasound Robotic Assisted Biopsy), and ISUR (Intelligent Surgical Robotics). Professor Muradore holds several administrative roles including Communication and Third Mission Representative for the Department of Engineering for Innovation Medicine, and serves on various teaching committees and councils. He is affiliated with multiple research groups: ForMe - Formal Methods for the Design of Engineering Systems Networked Systems and Technologies PARCO – Parallel Computing Robotics, Artificial Intelligence and Control Sistemi robotici e automazione (Robotic systems and automation) His teaching portfolio includes Advanced Control Systems, Dynamic Systems, Robotics, Vision and AI, and other courses related to control engineering and robotics.

Luca SterponeView profile

Professor

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +7 more

Luca Sterpone is a Full Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He serves as Head of the Control and Computer Engineering Department (2023-2027), coordinates the Aerospace and Safety Computing Lab, and is a member of the Academic Senate and Power Electronics Innovation Center (PEIC). His research spans reconfigurable computing, fault tolerance, and radiation effects analysis in electronic systems. Professor since 2021 Department Head (DAUIN) since 2023 Coordinates international collaborations with ESA, AMD Xilinx, NVIDIA, and Thales Alenia Space Develops radiation-hardened FPGA tools (SETA, VERI-Place, PyXEL) 2007 EDAA Outstanding Dissertation Award and 2005 IEEE Best Paper Award Research Focus : Designing radiation-tolerant systems for aerospace, including fault-tolerant AI accelerators, FPGA reliability, and software-based error mitigation. He investigates soft error propagation in nanoscale circuits and develops tools for radiation sensitivity analysis in VLSI. His work integrates hardware-software co-design for mission-critical applications. Awards : EDAA Outstanding Dissertation Award (2007) IEEE European Test Symposium Best Paper (2005) SMACD Best EDA Tool Award (2018) ARC Best Paper candidate (2018) Teaching : He leads courses in Reconfigurable Computing (PhD level), GPU Programming , and Operating Systems . He has formal responsibility for teaching roles across 9 bachelor's and 7 master's years, and mentors multiple PhD students. Collaborations : Coordinates with the European Space Agency (ESA), University of Bielefeld, Universidad de Sevilla, and industrial partners like AMD Xilinx, NVIDIA, and General Motors. He leads projects such as RESCHIP4EU, VEGAS, and TERRAC for radiation-hardened computing solutions.

• Big data analytics
• Data analysis
• Data management
• +8 more

Daniele Apiletti is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Control and Computer Engineering (DAUIN). He serves as a member of the Interdepartmental Center SmartData@PoliTO and acts as Academic Advisor for the Master's degree program in Data Science and Engineering. Research Groups: DBDM - Database and Data Mining Group (DAUIN) ERC Sectors: Algorithms, Artificial Intelligence, Machine Learning, Web and Information Systems Research Interests span Big Data Analytics, Data Science, Machine Learning, Computer Vision, and Quantum Computing. His work focuses on integrating data-driven and theory-guided approaches for heterogeneous data querying, cloud continuum machine learning, and spatio-temporal models for crisis management. Recent Publications highlight trends in medical image segmentation, predictive industrial modeling, and fault-tolerant data systems. Key subfields include AI in healthcare, scalable manufacturing analytics, and vision-language models for game tutorials. Teaching roles include course ownership of Big Data: Architectures and Data Analytics and Internships across multiple academic years. He has collaborated on courses in Data Science, Database Technologies, and Data Management. PhD Students Supervised: Etibar Vazirov (Cloud Continuum Machine Learning) Gabriele Scaffidi Militone (Cloud Storage Microservices) Daniele Rege Cambrin (Spatio-Temporal Ecology Models) Simone Monaco (Theory-Guided Data Science) Research Projects include commercial contracts on: - Natural language querying of corporate research archives - National tourism ecosystem platforms - AI for thermotechnical system design - Machine Learning in clinical trials and supply chains

• Numerical Linear Algebra
• Numerical Nonlinear Algebra
• Parallel Computing
• +7 more

Prof. Zhong-Zhi Bai is a Professor of Computational Mathematics at the Institute of Computational Mathematics and Scientific/Engineering Computing, part of the Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing. He is based at the State Key Laboratory of Scientific/Engineering Computing, a leading institution in applied mathematics and high-performance computing in China. His research spans a broad range of topics in computational mathematics, with a strong emphasis on numerical linear and nonlinear algebra , parallel computations , numerical optimization , and sparse matrix techniques . He has made significant contributions to the development and analysis of preconditioners and numerical methods for differential-algebraic equations and partial differential equations . His work is foundational in advancing iterative solvers and large-scale scientific simulations. The available publications, including the notable book Milestones in Matrix Computation (2007), reflect a long-standing engagement with matrix computation and numerical algorithms. The research trends indicate a deep focus on theoretical and practical aspects of numerical methods, particularly in the context of high-performance and scientific computing environments. Prof. Bai serves on the editorial boards of several leading journals in the field, including: Applied Numerical Mathematics Communications on Applied Mathematics and Computation Computational and Applied Mathematics East Asian Journal on Applied Mathematics Electronic Transactions on Numerical Analysis Journal of Computational and Applied Mathematics Journal of Mathematical Study Journal of Scientific Computing Numerical Algorithms Numerical Linear Algebra with Applications He has advised students and mentored researchers, though specific names are not listed. His work is supported by institutional affiliations and likely national research grants, given his position in a State Key Laboratory. He has developed software tools and delivered lecture series, contributing to both research and education in computational mathematics. Prof. Bai is actively involved in the numerical linear algebra community and maintains a comprehensive academic presence, including publications, editorial service, and software contributions. He leads or participates in research teams focused on advancing computational methods within the State Key Laboratory framework.

Li LiView profile

Professor

• Mobile Software Engineering
• Intelligent Software Engineering
• Software Security
• +6 more

Li Li is a Professor of Software Engineering at Beihang University , China. Previously, he served as an ARC DECRA Fellow and Senior Lecturer at Monash University , leading the SMart software Analysis and Trustworthy computing (SMAT) research lab at the Department of Software Systems and Cybersecurity. His academic journey includes a Ph.D. in Software Engineering from the University of Luxembourg (2016), supervised by IEEE Fellow Prof. Yves Le Traon and Dr. Jacques Klein. Research Interests Li's research focuses on Mobile Software Engineering (Mobile Security, Quality Assurance) and Intelligent Software Engineering (SE4AI, AI4SE). He applies static code analysis , dynamic program testing , and machine/deep learning to enhance software security and reliability. Key areas include Android API evolution, automated patch validation, and multi-language code analysis frameworks like Scalpel for Python. Scientific Recognition ARC DECRA Fellowship Rising SE Research Star Top-5 Most Impactful Early Career SE Researchers (2020, 2017) 5 Best/Distinguished Paper Awards across PLDI, WWW, ASE, MSR, and SANER Academic Contributions He has contributed to foundational Android analysis tools (e.g., AndroZoo++, DroidRA) and developed scalable systems for distributed program analysis (Seads). His work appears in top venues like ICSE, ESEC/FSE, ASE, ISSTA, POPL, and TSE.

Paolo TrunfioView profile

Professor

• Computer Engineering
• Big Data Analysis
• Machine Learning
• +5 more

Paolo Trunfio is a Professor of Computer Engineering at the University of Calabria, Italy, and co-founder of DtoK Lab S.r.l., an academic spin-off focused on data analysis and distributed systems. He holds a Ph.D. and is affiliated with the DIMES Department, specializing in big data, cloud computing, and high-performance computing (HPC). His research emphasizes scalable data analysis frameworks, edge-cloud continuum solutions, and machine learning applications for social media and disaster monitoring. Trunfio serves as an Associate Editor for ACM Computing Surveys and Journal of Big Data , and is on the editorial boards of several journals including Future Generation Computer Systems . He has authored four influential books, including Programming Big Data Applications (2024) and Data Analysis in the Cloud (2015). His work spans distributed systems, IoT-based smart objects, and exascale computing. Notable projects include the EU-funded eFlows4HPC and ASPIDE initiatives, which focus on HPC workflows and exascale programming models. Trunfio’s publications (over 200 papers) address topics like social media analytics, energy-efficient P2P networks, and parallel data mining. He leads research in urgent computing for disaster response, edge-cloud integration for urban mobility, and AI-driven data analysis. His contributions to cloud frameworks (e.g., JS4Cloud, ParSoDA) and HPC libraries (e.g., DCEx) highlight his expertise in bridging theory and practice in distributed computing ecosystems.

Roberto GiorgiView profile

Associate Professor

• Computer Architecture
• Multiprocessor Systems
• Multicore Architectures
• +6 more

Roberto Giorgi is an Associate Professor of Computer Engineering at the Department of Information Engineering, University of Siena, Italy. He has held this position since October 1, 2006, following his tenure as an Assistant Professor since March 15, 1999. His educational background includes a Ph.D. in Computer Engineering from the University of Pisa (1999) with a thesis on coherence protocols for shared-memory multiprocessors, and an Electronic Engineering degree (1995) with a thesis on trace-driven performance evaluation of multiprocessors. Giorgi's primary research focuses on Computer Architecture , particularly on multiprocessor/multicore issues including processor design, coherence protocols, programmability, and energy efficiency. His work spans both theoretical and practical aspects of computer architecture, with emphasis on real-world implementations and educational tools. He has coordinated significant EU-funded projects including AXIOM (2014-2018) on Smart Cyber-Physical Systems and TERAFLUX (2009-2014) on Many-Cores. His recent publications (2022-2025) demonstrate a strong progression toward practical applications of computer architecture research, with particular emphasis on RISC-V architecture, FPGA-based acceleration, dataflow computing models (especially DF-Threads), and graph processing. Many of his papers address educational tools for computer architecture education, real-time object detection on embedded platforms, and novel execution paradigms for edge computing and HPC. IEEE Senior Member ACM Lifetime Member Coordinator of EU-funded AXIOM project (2014-2018) on Smart Cyber-Physical Systems Coordinator of EU-funded TERAFLUX project (2009-2014) on Many-Cores Giorgi has been actively involved in securing research funding and building collaborations, particularly in high-performance computer architecture research with emphasis on scalable architectures and embedded systems. He leads the Computer Architecture Lab (ROOM 223) at the University of Siena, which was established in 2007, and has been instrumental in developing practical implementations of architectural concepts including the AXIOM platform for cyber-physical systems.

Laurence T. YangView profile

Professor

• parallel and distributed computing
• ubiquitous and pervasive computing
• embedded computing
• +3 more

Dr. Laurence T. Yang is a Professor at the School of Computer Science and Technology, Huazhong University of Science and Technology, China, and Department of Computer Science of St. Francis Xavier University, Canada. He maintains active research and professional service commitments across both institutions with significant contributions to computing disciplines. His research spans parallel and distributed systems, embedded platforms, ubiquitous/pervasive computing environments, sensor networks, supercomputing infrastructure, and scalable computing methodologies. These interests drive his extensive publication record and leadership in advancing computational theory and applications. Dr. Yang has received numerous accolades including: Honorable Mention, PROSE Awards for "Mobile Intelligence" (2010) Best Paper Award at IEEE AINA-06 (2006) Best Paper Nomination Distinguished Achievement Awards (2005, 2011) Canada Foundation for Innovation Award (2003) Multiple Best Paper Awards at international conferences His professional service includes chairing the IEEE Technical Committee of Scalable Computing (2008-2011), leading the IEEE Task Force on Ubiquitous Computing and Intelligence (2009-present), and serving on Compute Canada's National Resource Allocation Committee (2009-present). As editor-in-chief for multiple journals and author/editor of over 25 books, he has shaped scholarly discourse while delivering approximately 20 keynote addresses globally.

• Fluid Dynamics
• Biomedical Fluid Mechanics
• Microfluidics
• +3 more

Dario De Marinis is an Assistant Professor at the Department of Mechanics, Mathematics & Management, Politecnico di Bari, Italy. His research focuses on fluid dynamics with applications in biomedical engineering, aerospace, and computational physics. Research Interests Fluid-structure interaction modeling Microfluidics and particle transport Biomedical applications (blood flow, valve mechanics) Aerospace engineering (hypersonic flows, turbulence) Numerical methods (Lattice Boltzmann, immersed boundary) Publications Trend Dario's recent work (2015–2025) spans computational fluid dynamics, with emphasis on multiphase flows, viscoelastic material behavior, and biomedical microfluidic devices. He has contributed to aerospace applications and turbulent thermal flows.

• Scientific Computing
• Numerical Methods
• Computational Cardiology
• +5 more

Luca Pavarino is a Professor at the Department of Mathematics, University of Pavia. His research focuses on scientific computing and numerical methods, particularly in the context of cardiac electrophysiology and multiphysics systems. He leads the Scientific Computing group, specializing in domain decomposition methods (BDDC/FETI-DP), isogeometric analysis, and parallel algorithms. His work integrates advanced numerical techniques with biomedical applications, including cardiac electromechanical coupling, drug testing on cardiac tissues, and modeling genetic cardiac disorders like LQT8 syndrome. Key contributions include scalable solvers for nonlinear systems, preconditioners for heterogeneous media, and operator learning for ionic dynamics. Research interests span computational cardiology, numerical analysis, and parallel computing, with applications to biophysics and drug discovery. His projects often involve interdisciplinary collaborations between mathematics, engineering, and medicine. Notable contributions include: Development of BDDC/FETI-DP preconditioners for cardiac models Integration of machine learning with cardiac electrophysiology High-performance computing for multiphysics systems (Biot’s consolidation, protein stability) Labs/Teams: Scientific Computing Group at the University of Pavia’s Department of Mathematics.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +12 more

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

Agostino CortesiView profile

Professor

• Software Engineering
• Static Analysis
• Cybersecurity
• +5 more

Agostino Cortesi is a Full Professor at Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Informatics and Statistics. He serves as Rector's Delegate for Research Quality Assessment and Deputy Coordinator of the Scientific Committee for the Innovation Ecosystem Project. His academic career includes a PhD in Applied Mathematics and Informatics from the University of Padova (1992), a postdoctoral fellowship at Brown University, and visiting professor roles at institutions such as the University of Illinois and École Normale Supérieure Paris. Research interests focus on software engineering , static analysis , security applications , and abstract interpretation . He has pioneered techniques for formal verification of software systems and explored cybersecurity in e-Government and robotics. His work spans over 200 publications in top journals and conferences (e.g., ACM TOPLAS, IEEE TSE, POPL, PLDI). Key contributions include advancements in abstract domains for behavioral property verification and security-oriented analysis frameworks. He has held leadership roles including Vice-Rector at Ca' Foscari, Dean of Computer Science programs, and Chair of the Department of Computer Science. Cortesi coordinates EU Horizon 2020 projects (e.g., Families_Share €1.6M) and regional initiatives like CEVID (€360K). He founded Factors , a university spin-off focused on robotic systems verification, which won the 2020 Veneto SmartCup ICT Prize. Education: PhD in Applied Mathematics and Informatics (1992, University of Padova) Editorial Roles: Co-Editor-in-Chief of Springer’s 'Services and Business Process Reengineering', and member of editorial boards for 'Computer Languages' and others Grants: Over €3M in EU and regional funding for projects in cybersecurity, Industry 4.0, and digital innovation Teaching includes courses on Software Correctness , Data Programming , and Computer Networks across Computer Science and Management programs. His research lab actively engages in industrial partnerships with Cisco, Leonardo, and AGID (Italy’s Digital Agency).

• Flow in underground porous media
• Geoenergy
• Underground energy storage
• +12 more

Dario Viberti is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Environmental, Land and Infrastructure Engineering (DIATI). He is a member of the Interdepartmental Center Ec-L - Energy Center Lab and actively contributes to the Master's and Continuing Education School. He serves as Coordinator for both Master’s levels I and II of the Natural Resources Development and Storage program and participates in doctoral colleges for Civil and Environmental Engineering and Materials, Sustainable Processes, and Systems for the Transition. His research focuses on flow in underground porous media , geoenergy , and underground energy storage , particularly hydrogen and CO₂ storage. His expertise spans numerical modeling, reservoir engineering, fluid mechanics, well testing, and energy transition systems. He is involved in commercial research projects with ENI Corporate University and leads initiatives related to sustainable energy applications. His recent publications reveal a strong trend in underground hydrogen storage , biogeochemical modeling , pore-scale simulation , and PVT analysis of gas mixtures . These works emphasize safety, efficiency, and long-term integrity of subsurface storage systems using advanced computational and experimental methods. Scientific Manager, Underground CO2 Storage Project (2022) Scientific Manager, Reservoir Modeling Project (2022) Coordinator, Master’s Program in Natural Resources Development and Storage Member, SEASTAR Competence Center Committee (2020–2025) He mentors several PhD students, including Michel Tawil, Marialuna Loffredo, Alice Raeli, and Alice Massimiani, supporting research in microfluidics, Lattice Boltzmann simulations, and thermodynamic characterization. He teaches courses such as Numerical Modeling for Multiphase Flow , Underground Energy Storage , and Well Logging and Testing across multiple degree programs. His work aligns with UN SDGs 7 (Affordable and Clean Energy), 9 (Industry, Innovation, and Infrastructure), and 13 (Climate Action).

Luca Di GasperoView profile

Associate Professor

• Artificial Intelligence
• Combinatorial Optimization
• Metaheuristics
• +1 more

Luca Di Gaspero is an Associate Professor of Information Technology at the University of Udine, specializing in metaheuristic optimization techniques. His research enhances combinatorial optimization through hybridization of algorithms for scheduling, routing, and industrial applications. Research spans artificial intelligence in optimization, scheduling algorithms for manufacturing/healthcare, and metaheuristic framework development. Recent publications focus on LLMs in optimization, parallel batch scheduling, and energy-efficient manufacturing. Key Contributions: Developed EasyLocal++ framework for local search algorithms Advanced multi-neighborhood simulated annealing techniques Applied metaheuristics to healthcare logistics and emergency services