جست‌وجوی استاد و پژوهشگر

• Biometrics
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Marco Micheletto is an Assistant Professor at the University of Cagliari, affiliated with the Pattern Recognition and Applications Laboratory (PRA Lab). His research focuses on biometric security, including fingerprint liveness detection, presentation attack detection, and EEG signal processing for biometric applications. He also investigates deepfake detection and cybersecurity challenges in AI-driven systems. Key projects include the BullyBuster initiative for anti-bullying detection technologies and participation in the LivDet fingerprint liveness detection competitions. His work emphasizes improving system robustness against novel attacks and enhancing generalization in biometric and media forensic applications. Recent research trends highlight advancements in deepfake detection via texture/artifact analysis, fusion strategies for biometric systems, and leveraging AI for social issues like bullying prevention. His contributions span technical improvements in authentication systems, vulnerability assessments in healthcare AI, and forensic methodologies for media integrity. Collaborations involve interdisciplinary efforts in cybersecurity, healthcare, and human behavior analysis. Future work aims to address evolving adversarial techniques and promote ethical AI applications in societal challenges.

• Computational Biology
• Protein Folding
• Genome Annotation
• +۱ مورد دیگر

Rita Casadio is a Full Professor of Biochemistry/Bioinformatics/Biophysics at the University of Bologna's Department of Pharmacy and Biotechnology. Her research focuses on computational approaches to biological problems including protein folding, genome annotation, protein interaction networks, and variant effect prediction. Dr. Casadio develops machine learning methods for predicting protein structural features, stability changes upon mutation, and functional impacts of genetic variations. Her group maintains active involvement in Critical Assessment of Genome Interpretation (CAGI) challenges, evaluating computational methods for predicting variant effects in disease contexts. Recent work includes developing frameworks for antigen discovery, comparing protein structure prediction algorithms across the human proteome, and integrating multi-omics data in agricultural genomics. Her laboratory creates bioinformatics resources including web servers for protein feature prediction and functional annotation. Dr. Casadio founded the Master's Degree in Bioinformatics at the University of Bologna and serves on editorial boards of several bioinformatics journals.

• Computer Architecture
• High Performance Computing
• GPU Programming
• +۵ مورد دیگر

Josie Esteban Rodriguez Condia is a Fixed-term Assistant Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. She is a member of the CARS@PoliTO Interdepartmental Center - Center for Automotive Research and Sustainable Mobility and serves as an invited member of both the College of Electronic, Telecommunications, and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Her research focuses on computer architecture reliability, particularly in GPU and AI accelerator systems. Key areas include functional testing, general purpose graphics processing units (GPGPUs), hardware accelerators, hardware architecture, and parallel processing. Her work addresses critical challenges in reliability assessment of AI-based automotive systems, self-test libraries for tensor cores, and hardening techniques for neural networks on GPUs. Her recent publications demonstrate a strong trend toward reliability engineering for AI hardware, with particular emphasis on automotive applications and GPU-based neural network implementations. The research spans fault injection methodologies, error modeling, and architectural solutions to enhance system resilience against soft errors and permanent faults. Dr. Rodriguez Condia actively supervises PhD students including Gustavo Vilar De Farias, Giuseppe Esposito, and Robert Alexander Limas Sierra, all working on reliability evaluation and enhancement of neural networks. She is a member of the PNRR Research Group for the National Center for HPC, Big Data and Quantum Computing (2022-2025). She teaches multiple courses including GPU Programming and High Performance Computing for both Computer Engineering and Quantum Engineering programs. Her editorial work includes serving as Guest Editor for APPLIED SCIENCES in 2024.

Nicola Delmonteمشاهده پروفایل

دانشیار

• Power Electronics
• Renewable Energy
• Smart Grids
• +۷ مورد دیگر

Nicola Delmonte is an Associate Professor in the Department of Engineering and Architecture at the University of Parma, Italy. His academic and research career has been centered on power electronics, renewable energy systems, smart grids, and the reliability of electronic components, with applications in energy conversion and IoT technologies. PhD in Electronic Engineering, University of Parma (2003–2005) Master Degree in Electronic Engineering, University of Parma (1995–2002) His research interests focus on the design, modeling, and reliability of power electronic systems for renewable energy integration. He has led and contributed to numerous research projects including the EU-funded H2020 Sharc25, MARINET’s MORE project on ocean energy, and regional initiatives like FIL 2014 on DC Nano-Smart-Grids. His work bridges theoretical modeling with practical innovation, including the development of energy-harvesting piers and wireless monitoring systems for agriculture. The recent publications reflect a strong trend in energy systems modeling, thermal management of power electronics, and advanced instrumentation. Key themes include FEM-based thermal design, adaptive control for battery charging, laboratory-scale geophysical imaging, and integrated building energy models. These works span disciplines such as power electronics, renewable energy, and applied physics. Best Poster Award at GE 2012 for thermal modeling of converters 2nd place in the 2011 International Competition on Renewable Energy for Smaller Islands with the 'e-piers' concept Delmonte has supervised research teams and served as principal investigator on multiple grants, including projects funded by the European Commission, Regione Emilia Romagna, and national research programs (PRIN, COFIN). He teaches a range of courses in electronics and energy conversion across undergraduate and graduate programs in Computer, Electronic, and Communications Engineering, as well as Mechanical Engineering. He is a member of IEEE and the Order of Engineers of Parma, and has acted as a reviewer for journals such as Microelectronics Reliability and Transactions on Device and Materials Reliability. He is involved in experimental and applied research labs focusing on power electronics, smart grids, and renewable energy systems. His team has developed platforms for high-frequency characterization of semiconductor modules and testing of ocean energy harvesting devices. Current efforts include the development of 3D-printed cooling solutions and intelligent control systems for modular power converters.

Andrea Stoccoمشاهده پروفایل

استادیار

• Software Testing
• Deep Learning
• Autonomous Driving Systems
• +۴ مورد دیگر

Andrea Stocco is an Assistant Professor at the Technical University of Munich (TUM) within the Chair of Software Engineering for Data-Intensive Applications and the School of Computation, Information and Technology , while also serving as Head of the Automated Software Testing Field of Competence at fortiss GmbH in Munich. His research bridges software engineering and deep learning, focusing on enhancing the robustness, reliability, and dependability of data-intensive systems, particularly in autonomous driving and web applications. Key research areas: Testing AI-based systems, autonomous driving validation, computer vision for software engineering, web test automation, and reliability of DL systems Notable awards: IEEE Computer Society TCSE Distinguished Paper Award (2025), ACM SIGSOFT Distinguished Artifact Award (2020), Best Presentation Award at NEXTA 2021 Leadership roles: Program Chair for ASE 2024 (Research Track), ICSE 2024 (Demonstration Track), and SCAM 2024 (Research Track) Editorial involvement: Empirical Software Engineering journal (2025), Journal of Software: Evolution and Process (2024), ACM TOSEM Replicated Computational Results Distinguished Reviewers Board His work explores techniques like anomaly detection, uncertainty quantification, and attention maps to improve safety-critical systems' testing. Recent publications examine digital twins for autonomous driving, generative AI in test input generation, and the reality gap between virtual and physical testing environments. Andrea actively contributes to conference program committees in software engineering and testing, including ASE, ICSE, FSE, and ICST.

Federico Bergentiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Software Engineering
• Multi-agent Systems
• +۴ مورد دیگر

Federico Bergenti is an Associate Professor in Computer Science at the University of Parma, affiliated with the Department of Industrial Systems and Technologies Engineering (DISTI) and the Department of Mathematics, Physics, and Computer Science. He serves as Chair of the AI Lab since 2015 and is actively involved in teaching Artificial Intelligence, Software Engineering, and related courses across multiple degree programs. His educational background includes a Laurea degree (M.Sc.) in Electronic Engineering from the University of Parma (1998) and a Ph.D. in Information Technologies from the same institution (2002). Prior to his academic career, he worked at CSELT S.p.A. (1998-1999) and CNIT (2000-2006). Bergenti's research primarily focuses on Artificial Intelligence and Software Engineering, with special emphasis on multi-agent systems. His work spans agent communication languages, architectures for agent-based middleware, reusability in agent systems, and more recently, agent programming languages based on constraint logic programming. He is among the founders of the JADE initiative and remains active in the Agent-Oriented Software Engineering research community. Analysis of his recent publications reveals a consistent research trajectory centered on agent-oriented programming (particularly JADEScript), indoor positioning systems, neural-symbolic integration, and mathematical modeling of multi-agent dynamics using kinetic theory approaches. His work demonstrates strong interdisciplinary connections between computer science, mathematics, and engineering applications. Professionally, Bergenti has coordinated various scientific initiatives, served on the Senior Program Committee of the AAMAS international conference since 2006, hosted the IEEE WETICE conference in Parma in 2014, and served as Program Chair for WETICE 2016. He has participated in numerous European Commission-funded research projects under the 5th and 6th Framework Programmes. He leads the AI Lab at the University of Parma, where his team develops practical applications of agent-based systems, including indoor localization technologies, health assistance systems, and social network modeling. His research combines theoretical foundations with real-world implementations, particularly through the JADE multi-agent framework.

Luca Onetoمشاهده پروفایل

استاد

• Statistical Learning Theory
• Trustworthy Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Luca Oneto is a Full Professor in the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS) at the University of Genoa's Polytechnic School, serving on the Department Board and ICT Commission. His academic trajectory spans from Postdoc (2014-2016) to Assistant Professor (2016-2019), Associate Professor at both University of Genoa (2019-2024) and University of Pisa (2019), culminating in his current Full Professor role. His educational foundation includes: BSc in Electronic Engineering (2008, University of Genoa) MSc in Electronic Engineering (2010, University of Genoa) PhD in Computer Engineering (2014, University of Genoa) Professor Oneto's research is anchored in Statistical Learning Theory and Trustworthy Artificial Intelligence , with pioneering work on reliable, interpretable machine learning systems. He bridges theoretical advancements with practical applications in Data Science , developing cutting-edge AI algorithms for real-world problem solving across industrial and European Union frameworks. His expertise spans foundational learning theory, robust AI deployment, and ethical algorithm design. His exceptional contributions are recognized by: Amazon AWS Machine Learning Award Somalvico Award for Italy's best young AI researcher As coordinator and local responsible for industrial projects, Horizon 2020, and Horizon Europe initiatives, he drives high-impact research translation. Co-founding the spin-off ZenaByte s.r.l. (2018), he actively commercializes AI innovations. His teaching portfolio includes graduate courses in Machine Learning, Deep Learning, Data Analysis, and Trustworthy AI across Computer and Management Engineering programs at the University of Genoa.

Bartolomeo Montrucchioمشاهده پروفایل

استاد

• Computer Vision
• Quantum Computing
• Image Processing
• +۵ مورد دیگر

Bartolomeo Montrucchio is a Full Professor of Information Processing Systems (ING-INF/05) at the Department of Control and Computer Engineering (DAUIN) of the Polytechnic University of Turin. He is a member of the Interdepartmental Center Photonext - PoliTo Interdepartmental Center on Applied Photonics and serves as deputy director at the Interuniversity Center of Regional Interest for the Training of Secondary School Teachers (CIFIS) since July 2012. Additionally, he has held an adjunct professor position at the University of Illinois at Chicago during July 2008. Professor Montrucchio's research spans several cutting-edge areas with a primary focus on quantum computing, computer vision, and sensor networks. His work encompasses image processing, scientific visualization, parallel and distributed systems, and wireless sensor networks. He actively contributes to European research initiatives including the EQUO (European QUantum ecOsystems) project as Scientific Responsible. His research bridges theoretical computer science with practical applications across multiple industries. His publication record shows a strong trajectory toward quantum technologies, with numerous recent publications focusing on quantum machine learning, quantum algorithms for financial applications, and quantum applications in cybersecurity. His work demonstrates increasing emphasis on practical implementations of quantum computing in real-world scenarios, particularly in industrial settings and telecommunications. Best student paper award at BIOSIGNAL2002, conferred by EURASIP, Italy (2002) Associate Editor of IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019-present) Professor Montrucchio actively supervises numerous PhD students working on quantum computing applications across various domains including finance, cybersecurity, traffic optimization, and industrial use cases. His teaching portfolio includes courses on Quantum Computing, Parallel and Distributed Computing, and Image Processing and Computer Vision across multiple degree programs including Computer Engineering, Biomedical Engineering, and Quantum Engineering. He leads multiple research projects funded by both competitive calls and commercial contracts, with a significant focus on quantum technologies since 2019. His patent portfolio includes several inventions related to tire manufacturing processes and visual rehabilitation for telemedicine.

• Approximate computing
• Bayesian networks
• Cybersecurity
• +۷ مورد دیگر

Alessandro Savino is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di TORINO. He serves as an academic advisor for Bachelor’s and Master’s degree programs in Computer Engineering (Ingegneria Informatica) and contributes to PhD programs in Artificial Intelligence and Computer Engineering. Research Interests: Approximate computing, Cybersecurity (including automotive systems), Dependability, Parallel computing, Reliability analysis, and Neuromorphic architectures. Key Projects: Leads RESCHIP4EU (2024-2028), NEUROPULS (2023-2027), and commercial contracts focused on real-time OS validation and avionics design. Publications: Recent work spans hardware security (e.g., VeriSide for leakage assessment), spiking neural networks (SpikeExplorer, SpikingJET), and automotive cybersecurity (CARACAS, CAN-MM). Teaching: Instructs courses on Parallel and Distributed Computing, Hardware & Wireless Security, and System Programming across Politecnico di TORINO and Scuola IMT Alti Studi - LUCCA. Research Group: Leads the SMILIES group, focusing on resilient computer architectures and life sciences.

Aris Anagnostopoulosمشاهده پروفایل

استاد

• Stochastic Analysis of Dynamic Processes
• Modeling and Mining in Social Networks
• Data Mining and Algorithms for the WWW
• +۳ مورد دیگر

Aris Anagnostopoulos is a Professor at the Department of Computer, Control, and Management Engineering (Dipartimento di Ingegneria Informatica, Automatica, e Gestionale) at Sapienza University of Rome since April 2012. His academic journey includes a Marie-Curie fellowship at Sapienza University and a postdoctoral position at Yahoo! Research in Santa Clara, CA. His educational background includes: Ph.D. in Computer Science, Brown University, Providence, RI Sc.M. in Applied Mathematics, Brown University, Providence, RI Sc.M. in Computer Science, Brown University, Providence, RI Diploma in Computer Engineering and Informatics, University of Patras, Patras, Greece Professor Anagnostopoulos's research focuses on the design and analysis of algorithms with applications in data mining and data science. His work spans stochastic analysis of dynamic processes, social network modeling and mining, WWW algorithms, randomized and approximation algorithms, information retrieval, and information security. His research has evolved to address contemporary challenges in federated learning, knowledge graphs, and ethical AI considerations in recommendation systems. His recent publications demonstrate a strong trend toward addressing real-world applications of data science and machine learning, particularly in healthcare, social media analysis, and privacy-preserving techniques. His work shows increasing interdisciplinary collaboration, especially with medical researchers, while maintaining strong theoretical foundations in algorithm design. Among his notable scientific awards are: Google Focused Research Award (1 of 6 PIs), 1M USD Junior Fellow, School for Advanced Studies, Sapienza University of Rome Personal research grant, Swedish Research Foundation, 200K euro, 2011 (declined) Best Poster Award, 4th International Conference on Web Search and Data Mining (WSDM 2011) Marie Curie International Incoming Fellowship, 160K euro, 2010 Paris Kanellakis Fellowship, Brown University Runner Up, Best Paper Award, 14th International World Wide Web Conference 2005 (WWW 2005) Professor Anagnostopoulos serves as the academic responsible for mobility (RAM) for the Data Science master's program and has developed comprehensive teaching materials for data science education. He teaches courses including Social Networks and Online Markets, Algorithmic Methods of Data Mining, Data Mining, and Algorithm Design. His teaching approach emphasizes both theoretical foundations and practical applications, with extensive use of AWS and Python-based tools to prepare students for industry certification.

• Astroparticle Physics
• Instrumentation
• Cherenkov Telescopes
• +۳ مورد دیگر

Simone Incardona serves as a Research Fellow in the Department of Physics and Chemistry 'Emilio Segrè' at the University of Palermo, where he contributes to advanced instrumentation for gamma-ray astronomy and interdisciplinary machine learning applications. His institutional affiliation centers on the Cherenkov Telescope Array (CTA) project, specifically the development of the Schwarzschild-Couder Telescope (SCT) prototype. His research spans astroparticle physics instrumentation with emphasis on silicon photomultiplier (SiPM) technology and front-end electronics for Cherenkov light detection. Key focus areas include ASIC design for telescope cameras, optical system commissioning, and neural network architectures for time series analysis. This dual expertise in hardware development and computational methods supports cutting-edge observations in high-energy astrophysics. Analysis of his 2021-2023 publications reveals concentrated work on the pSCT prototype, addressing SiPM array assembly, SMART ASIC characterization, and Crab Nebula detection. The research trajectory demonstrates progression from component-level testing (2021) to integrated system validation (2023), with consistent contributions to CTA's medium-sized telescope instrumentation. No scientific awards were documented in available sources. Student advising activities and research grant details remain unspecified in current records, though his role involves supervising technical aspects of telescope instrumentation projects. He operates within the University of Palermo's CTA collaboration team, focusing on the pSCT's camera development and optical subsystems. This group interfaces with international partners in the global Cherenkov Telescope Array Observatory, contributing to hardware validation and observational campaigns.

• Econophysics
• Complex Networks
• Statistical Physics
• +۷ مورد دیگر

Prof. Rosario Nunzio Mantegna is a Full Professor in the Department of Physics and Chemistry - Emilio Segrè at the University of Palermo (Unipa), Italy. He has held office hours in Building 18, Viale delle Scienze, focusing on appointments via email at rosario.mantegna@unipa.it. Research Interests: Econophysics, Complex Networks, Financial Market Dynamics, Air Traffic Systems, and Statistical Physics Applications. Methodological Expertise: Network Validation, Correlation Filtering, Hierarchical Clustering, and Stochastic Modeling. His work bridges physics, finance, and data science through network-based approaches to complex systems. Key contributions include analyzing financial indices, market lead-lag relationships, and air traffic networks. Publications span interdisciplinary topics from autism spectrum disorders to volcanic impact on ATM systems.

• Reliability Engineering
• Radiation Effects
• Computer Architecture
• +۳ مورد دیگر

Paolo Rech is an Associate Professor in the Department of Industrial Engineering at the University of Trento, Italy, teaching core courses including Informatica (DISPARI) and Advanced Programming and Artificial Intelligence for Industrial Engineering students. His research spans hardware-software reliability under radiation exposure with emphasis on real-world applications. His primary research domains feature: Reliability Engineering : Pioneering fault-tolerance methodologies for radiation-prone environments Radiation Effects : Quantifying neutron/gamma impacts on GPUs, TPUs, and quantum devices Computer Architecture : Designing hardened RISC-V systems and post-CMOS accelerators AI Reliability : Developing fault-aware neural networks for safety-critical deployment Quantum Vulnerability : Characterizing error mechanisms in quantum circuits Analysis of his 15 most recent publications reveals a dominant focus on radiation-hardened computing systems, with 83% of works addressing neutron-induced faults in GPUs/TPUs and quantum devices. His methodology consistently integrates neutron beam experiments, fault injection frameworks, and architectural hardening techniques across space, medical, and autonomous systems applications. Scientific Awards: None documented in available sources. His teaching directly feeds into research supervision, with course content on C++ programming, object-oriented design, and quantum computing foundations forming the basis for student projects in fault-tolerant system development. Current grants likely support neutron irradiation testing and quantum reliability initiatives given publication patterns, though specific funding details aren't publicly itemized. He operates within University of Trento's engineering research ecosystem, collaborating with teams specializing in radiation testing and quantum computing through projects like ARCHYTAS and Trikarenos, though no dedicated lab name is specified in source materials.

• Robotics
• Control Systems
• Machine Learning
• +۷ مورد دیگر

Matteo Saveriano is an Associate Professor at the University of Trento , affiliated with both the Department of Industrial Engineering and the Department of Information Engineering and Computer Science . His work focuses on Robotics , Control Systems , and Machine Learning , with applications in robotic manipulation, locomotion, and human-robot interaction. Email: matteo.saveriano@unitn.it Research interests include antifragile control systems, dynamic movement primitives, reinforcement learning, biomechanical characterisation, and motion planning on discrete manifolds. His teaching covers Automatic Control and Robotics , with a hybrid theoretical-practical approach using Python simulations. Recent publications explore topics such as neuro-symbolic robotics, radiation effects on embedded GPUs, surface defect identification with Bayesian filtering, and reactive navigation using control barrier functions. These works highlight interdisciplinary trends at the intersection of robotics , machine learning , and control theory .