Valeria Seidita is a Professor in the Department of Computer Engineering at the University of Palermo, affiliated with the Polytechnic School. She specializes in robotics and artificial intelligence, with research focusing on Human-Robot Interaction, Healthcare Robotics, and Quantum Computing applications in robotic systems. Her work emphasizes ethical considerations, swarm intelligence, and smart city technologies. She teaches courses such as Software Engineering and Artificial Intelligence, contributing to both undergraduate and graduate programs. Dr. Seidita has authored numerous publications, including studies on quantum-driven robotic swarms, ethical AI frameworks, and humanoid robotics in healthcare. Her research bridges technical innovation with societal impact, particularly in medical assistance and environmental monitoring. Her recent work explores quantum computing’s role in optimizing swarm robotics and enhancing human-robot trust through explainability. She collaborates on projects like the ATeN Center and ASCENT, advancing interdisciplinary research in robotics and cognitive systems.
Daniele Berardini is a Research Fellow at the Department of Information Engineering (DII) of Università Politecnica delle Marche in Ancona, Italy. He is also a PhD student under Prof. Emanuele Frontoni, focusing on Edge Artificial Intelligence and real-time human behavior analysis through video surveillance. His work emphasizes lightweight Deep Learning methods for resource-constrained devices, with applications in healthcare monitoring, security systems, and environmental surveillance. Education: Bachelor's degree (cum laude) in Computer Science (2017), University of L'Aquila Master's degree (cum laude) in Computer Science (Network and Data Science) (2019), University of L'Aquila PhD in progress at Università Politecnica delle Marche (since 2020) Research Interests: His research integrates Machine Learning and Deep Learning techniques for developing efficient monitoring systems. Key areas include Edge AI for real-time analysis, human behavior detection in indoor/outdoor environments, and ethical considerations in AI deployment for healthcare and surveillance. His methodologies often combine optimization frameworks with neural networks to enhance computational efficiency. Labs/Teams: He is part of the Vision, Robotics and Artificial Intelligence (VRAI) research group at DII, focusing on interdisciplinary projects such as neonatal care monitoring, weapon detection in video surveillance, and sustainable AI for medical applications. Grants/Advising: No specific grants or advising roles explicitly mentioned in the text.
Prof. Paolo Crippa is an Associate Professor at the Department of Information Engineering (DII) of the University of Ancona (Università Politecnica delle Marche), Italy. His research focuses on biomedical signal processing, embedded systems, and wearable technology for healthcare applications. He specializes in neural networks, sensor design, and nanoelectronics, with notable contributions to graphene-based biosensors and real-time gesture recognition systems. His work bridges electronics, machine learning, and healthcare, addressing challenges in disease diagnosis, activity monitoring, and assistive living technologies. Prof. Crippa’s publications emphasize the development of low-power, high-accuracy systems for applications such as EEG-based disease classification, wearable sensors for activity recognition, and SARS-CoV-2 detection using advanced materials. His recent work includes optimizing LSTM neural networks for embedded platforms and integrating multimodal sensors (PPG, IMU, sEMG) for health monitoring. His research trends reveal a strong emphasis on applying machine learning to biomedical signals, improving sensor synchronization, and leveraging nanotechnology for diagnostic tools. He also explores open-source hardware/software co-design frameworks for system-on-chip (SoC) development. Prof. Crippa’s contributions extend to international collaborations and interdisciplinary projects, reflecting his role in advancing both theoretical and applied aspects of information engineering.
Monica Marconi Sciarroni is a Research Fellow at the Department of Information Engineering (DII) of the Polytechnic University of Marche. Her current research focuses on defining platform architectures and advanced query mechanisms for industrial Internet-of-Everything environments under Prof. Emanuele Storti's supervision. Education: Bachelor's Degree in Management Engineering (2021) Master's Degree in Computer and Automation Engineering (2023) Research Interests: Data gathering and management for IoE networks Integration strategies and querying mechanisms Augmented Reality applications for Industry 5.0 Text mining and semantic analysis Thesis Work: Analyzed a company call center using business intelligence tools and text mining techniques for descriptive/semantic analysis under Prof. Domenico Potena's supervision. Contact: Room Q166_143 | +39 071 2204480
Lucia Migliorelli is a Research Fellow at the Polytechnic University of the Marche, Italy. She completed her Master of Science in Biomedical Engineering (cum laude) in 2018 and has been pursuing a PhD since 2018 under Prof. Emanuele Frontoni. Her research focuses on AI-driven monitoring systems for healthcare applications, leveraging multimedia data analysis without wearable sensors. Key areas include human action recognition, medical record analysis, and non-invasive patient monitoring for populations like preterm infants and elderly patients. Education highlights include a Master’s thesis on machine learning for diabetes management and ongoing PhD work on intelligent spaces for automated behavior analysis. Current projects involve federated learning for medical imaging (e.g., MRI-to-CT synthesis) and edge AI for real-time surveillance systems. She is based at the Polytechnic University of the Marche, contributing to interdisciplinary research at the intersection of biomedical engineering and artificial intelligence. Her publications span medical image analysis, AI in digital humanities, and ethical considerations in healthcare AI. She actively develops prototypes for neonatal intensive care units, emergency vehicle detection, and groundwater level prediction. No scientific awards are explicitly listed, though her work reflects strong contributions to AI-driven healthcare innovation. Current advising and grants are not detailed in the text, but her research aligns with lab efforts in environmental AI, rehabilitation robotics, and telemonitoring systems for neurological disorders. She collaborates with multidisciplinary teams to advance ethical, sustainable AI solutions for clinical and societal challenges.
Prof. Aldo Franco Dragoni is an Associate Professor at the Department of Information Engineering, Polytechnic University of Marche (UNIVPM). He specializes in artificial intelligence applications for healthcare, cybersecurity, and smart systems. His research spans machine learning, computer vision, and multi-agent systems, with notable projects like CLAUDIA (Alzheimer's diagnosis via 3D MRI) and Cloud-YLung (lung cancer histology classification). He leads initiatives in medical imaging analysis, violence detection, and IoT-based systems. Research interests include AI-driven medical diagnostics, cyber-physical systems, and BDI agent architectures for ambient assisted living (e.g., Virtual Carer project). His work integrates cloud computing, neural networks, and multi-agent reasoning for healthcare solutions. Publications focus on AI applications in medical imaging, surveillance, and smart environments. He contributes to academic publications and conference proceedings, co-authoring papers on topics like deep learning for violence detection, face recognition systems, and blockchain in multi-agent negotiations.
Prof. Laura Falaschetti is a Researcher at the Department of Information Engineering, Polytechnic University of Marche (Ancona, Italy). Her work focuses on embedded systems, neural networks, biomedical engineering, and signal processing. She develops lightweight machine learning models for resource-constrained devices, with applications in healthcare monitoring, environmental sensing, and wearable technology. Key projects include real-time gesture recognition systems, EEG-based disease classification, and low-power IoT devices for disaster early warning. Her research integrates hardware-software co-design (e.g., QEMU/GHDL) and emphasizes practical deployment of AI algorithms on microcontrollers. She holds office hours every Friday 10:00-13:00 at Ufficio docente Q165 DII/Microsoft Teams. Contact: l.falaschetti@staff.univpm.it Publications highlight contributions to embedded vision systems, wearable sensor networks, and multimodal signal fusion for clinical applications. Her work bridges theoretical machine learning with practical embedded system constraints, addressing challenges in energy efficiency, real-time processing, and medical accuracy.
Prof. Lorenzo Palma is a Researcher at the Department of Information Engineering, Faculty of Engineering, Università Politecnica delle Marche. His work focuses on interdisciplinary research at the intersection of IoT, wearable sensors, and biomedical engineering. Key areas include earthquake early warning systems, smart healthcare solutions, and embedded machine learning applications. Research Interests: Prof. Palma’s research spans IoT protocols optimization, wearable sensor development for clinical applications (e.g., diabetes monitoring, fall detection), and real-time signal processing for disaster preparedness. He has contributed to projects like seismic sensor networks, AAL (Ambient Assisted Living) systems, and AI-driven healthcare diagnostics. His work emphasizes low-cost, resource-efficient solutions for both industrial and medical domains. Publications Trends: Recent articles highlight advancements in AIoT systems for disaster response, embedded vision for disease classification, and BLE mesh network optimizations. He frequently explores the integration of machine learning with wearable devices for personalized healthcare and industrial predictive maintenance. Professional Activities: Active in academic-industry collaborations, Prof. Palma has developed prototypes for smart home automation, seismic monitoring tools, and clinical assessment systems. His lab specializes in cross-protocol IoT solutions and real-world sensor validation. Office hours are held Monday 9:00-12:00 at Via Brecce Bianche 12.
Prof. Paola Pierleoni is a Researcher at the Department of Information Engineering of the University of Ancona and Marche Polytechnic (UNIVPM) . Her work focuses on IoT, telecommunications, and wearable sensor systems applied to healthcare, disaster management, and industrial automation. She leads projects in real-time data processing , embedded machine learning , and cross-protocol communication , with notable contributions to earthquake early warning systems and diabetes therapy optimization. Her research combines telecommunications engineering with health monitoring applications , including gait analysis for Parkinson’s disease, stress assessment via wearable sensors, and underwater diver monitoring. She has developed low-cost IoT solutions for infrastructure monitoring (e.g., water leak detection) and AI-driven algorithms for medical diagnostics and industrial predictive maintenance. Key projects include: Earthquake Early Warning systems using MEMS accelerometers AIoT frameworks for ambient assisted living (AAL) Bluetooth mesh network optimization for latency-sensitive applications Machine learning models for diabetes therapy personalization Her work emphasizes interdisciplinary collaboration , integrating engineering, computer science, and medical expertise. Office hours are held on Mondays 9:00–13:00 at the Department of Information Engineering, Via Brecce Bianche.
Guido Giuliani is an Associate Professor of Optoelectronics at the University of Pavia's Department of Industrial and Information Engineering. His research spans semiconductor lasers, silicon photonics, optical sensors, and non-contact laser measurement techniques. Giuliani co-founded Julight Srl, a photonics technology start-up developing sensor solutions. Research focuses on: Semiconductor laser dynamics and applications Silicon photonic devices and circuits Laser interferometry and vibrometry systems THz generation and detection techniques Optical methods for biomedical diagnostics His technical contributions include all-optical switching devices using semiconductor ring lasers, silicon micro-resonator filters, terahertz spectroscopy systems, and non-contact physiological monitoring techniques. Giuliani's work has been implemented in EU projects including FABULOUS (silicon photonics for optical access networks). He develops practical photonic solutions bridging fundamental research and industrial applications.
Eleonora Balliana is a University Researcher at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. Her work focuses on the chemistry of environmental and cultural heritage materials, combining analytical methods with innovative material solutions for preservation. She leads laboratory supervision and contributes to interdisciplinary research initiatives. Research Interests: Development of nanomaterials for cultural heritage conservation Analysis of degradation processes in art and architectural materials Innovative solutions for historic masonry and paper artifacts Funding: FISR - ISMEE Project (MUR-funded, 2021-2022): Investigating anti-COVID sanitation impacts on heritage sites TEMART Project (Veneto Region, 2018-2021): Materials for artistic and architectural heritage preservation Professional Activities: Collaborates with research groups on heritage vulnerability assessment, modern art degradation studies, and archaeological site preservation. Proficient in English and French, with native Italian fluency.
Massimo Tagliavini is a tenured Professor at the Free University of Bozen-Bolzano, holding appointments in the Faculty of Agricultural, Environmental and Food Sciences. He specializes in the physiology and ecology of tree ecosystems, focusing on carbon, nutrient, and water exchanges between trees, soil, and atmosphere under climate change and management pressures. His research integrates micrometeorology, stable isotopes, and modeling to develop sustainable agricultural practices. Education: Ph.D. (1991), Postdoc (1991–1997), Associate Professor at University of Bologna (1998–2017), Full Professor at UNIBZ since 2007. Leadership roles include Dean of the Faculty of Science and Technology (2008–2014), President of the Italian Society of Horticultural Science (2016–2022), and Vice-President of EURAC Research (2016–present). Research emphasizes climate change impacts on tree ecosystems, water-use efficiency, and adaptation strategies. Techniques include isotope tracing, micrometeorology, and field experiments. His work bridges fundamental science and applied solutions, such as optimizing irrigation and mitigating heat stress in orchards and vineyards. Publications exceed 200 articles, with over 100 in peer-reviewed journals. He serves on editorial boards of European Journal of Agronomy and Tree Physiology , and has organized numerous international conferences. Current research focuses on multi-decadal tree-ring analysis to trace climatic history and biochar applications in vineyards. Teaching includes courses on agricultural ecology, tree ecophysiology, and statistical methods for environmental research at the bachelor’s and master’s levels, as well as a PhD program in Sustainable Agricultural Production Systems.
Peter FERRARA is an Associate Professor in Computer Science at Ca' Foscari University of Venice, Italy. He joined the university in November 2019 as a tenure-track assistant professor and transitioned to his current rank. His primary affiliation is with the Department of Environmental Sciences, Computer Science and Statistics (D.A.I.S.) and the Research Institute for Complexity. He is part of the Software and System Verification group and maintains an active role in the Temporary Center Innovation Ecosystem Project. Education: Holds a PhD in Computer Science (2009) from École Polytechnique (Paris) and Ca' Foscari University of Venice, advised by Radhia Cousot and Agostino Cortesi. Completed his MA (2005) and BA (2003) in Computer Science from Ca' Foscari. Defended his thesis at École Normale Supérieure in May 2009. His research experience spans 15 years, with 50+ publications and 20 patents, focusing on static analysis for software reliability and security. Research Interests: Specializes in applying abstract interpretation theories to enhance software security, reliability, and performance. Recent work emphasizes static analysis of mobile and .NET systems, blockchain smart contracts, IIoT vulnerabilities, and automated policy enforcement. He bridges formal methods with practical software development, addressing challenges in precision-efficiency tradeoffs and industrial tool adoption. Industry Experience: From 2013-2019, worked in industry as Head of R&D at JuliaSoft SRL (2016–2019) and IBM Research (2013–2015). Developed commercial static analysis tools, managed research projects, and delivered technical presentations to clients. His work focused on transitioning research into deployable solutions. Teaching: Instructs courses in Object-Oriented Programming, Software Architectures, and Coding/Data Management. Engages students through practical LiSA framework experiences. Has taught at ETH Zurich (2009–2013) and supervised over a dozen students across PhD, Master's, and Bachelor's levels. Awards: No specific scientific awards listed, but recognized through extensive patent portfolio and impactful industry-academia collaborations. Holds 20 patents, including innovations in permissions extraction, privacy enforcement, and malware detection. Grants & Projects: Involved in multiple research projects from proposal to execution, including EU Data Act analysis, IoT security frameworks, and blockchain verification initiatives. Collaborates with institutions like IBM, Microsoft Research, and the University of Verona's JuliaSoft spin-off. Labs/Teams: Active in the Software and System Verification group at Ca' Foscari. Co-developed the LiSA static analysis framework. Engages in interdisciplinary projects combining robotics, IoT, and blockchain domains.
Francesco Driussi is an Associate Professor at the Polytechnic Department of Engineering and Architecture (DPIA), University of Udine, Italy. He received his Ph.D. in Electronics from the University of Udine in 2004 and has been affiliated with DPIA since 2005, initially as a Research Associate (2005-2018) before assuming his current role in 2018. He has also served as a Visiting Scientist at Philips Research Leuven (IMEC, Belgium) in 2003. His research focuses on nano/microelectronic device physics , specializing in characterization techniques and physics-based modeling for emerging technologies. Key areas include memory cells, CMOS transistors, sensors, 2D materials (e.g., MoS 2 ), ferroelectric memristors, and neuromorphic computing systems. His work bridges experimental design with theoretical simulations to advance semiconductor device architectures. Analysis of his 15 most recent articles (2022-2025) reveals dominant themes: ferroelectric devices (capacitors, tunnel junctions), 2D material interfaces , avalanche photodiodes for radiation detection, and high-frequency circuit modeling . Methodologies emphasize ab initio simulations, experimental characterization, and compact modeling for real-world applications. He maintains active collaborations with semiconductor industry leaders (NXP, ST Microelectronics) and European research institutions including CEA-Leti (France), KTH (Sweden), AMICA-AMO/NaMLab (Germany), IMEC (Belgium), and IMM-CNR/Elettra (Italy). His projects are funded by the EU and Italian Ministry for University Education and Research (MIUR). Driussi serves as Associate Editor for Frontiers in Electronics and reviews for 15+ international journals. He participates in technical committees for premier conferences like the International Electron Devices Meeting (IEDM) and International Conference on Microelectronic Test Structures (ICMTS).
Marco Pala is an Associate Professor at the University of Udine in the Department of Engineering and Architecture. He holds a PhD in Electronical Engineering from the University of Pisa and has held research positions at CEA-LETI and CNRS. His research focuses on quantum transport, nanoelectronics, and computational modeling of nanoscale systems. Research interests include spin-dependent transport, CMOS transistors, 2D materials, and ab-initio simulations. He leads projects on electronic properties of nanostructures and collaborates on European and national grants. Recent publications emphasize quantum confinement, 2D heterostructures, and Monte Carlo simulations. Trends show strong focus on material interfaces and device physics. Awards include Senior Member of IEEE (2022). He has supervised 15 PhD students and 6 post-docs, and led the computational electronics group at Centre for Nanoscience and Nanotechnology.
