Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱-۱۵ از ۳۷ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Sebastiano Battiato is a Full Professor of Computer Science at the University of Catania's Department of Mathematics and Computer Science. He serves as Scientific Coordinator of the PhD Program in Computer Science and Deputy Rector for Strategic Planning and Information Systems at the University of Catania. As Director and Co-Founder of the International Computer Vision Summer School (ICVSS), he has significantly contributed to computer vision education globally. Education: Bachelor's degree in Computer Science (summa cum laude), University of Catania, 1995 Ph.D. in Computer Science and Applied Mathematics, University of Naples, 1999 Professor Battiato's research primarily focuses on Computer Vision, Imaging Technology, and Multimedia Forensics . His work spans from developing ISP algorithms for embedded devices to creating advanced techniques for image enhancement, coding, and forensic analysis. He has pioneered research in social media forensics, developing methods to determine if images have been processed through specific social platforms. His research has practical applications in assistive technologies, retail, digital marketing, and medical fields. His scholarly output shows a consistent focus on digital forensics and image processing, with an increasing emphasis on social media forensics in recent years. The research trajectory demonstrates progression from foundational image processing techniques to sophisticated forensic applications capable of addressing modern challenges like deepfakes and social media manipulation. Scientific Awards: 2017 PAMI Mark Everingham Prize for the series of annual ICVSS schools 2011 Best Associate Editor Award of IEEE Transactions on Circuits and Systems for Video Technology Professor Battiato has coordinated IPLab's participation in numerous large-scale research projects funded by national and international bodies as well as private companies. He has served as principal investigator on many international and national research projects, demonstrating strong leadership in securing research funding. His editorial work includes serving as associate editor for the SPIE Journal of Electronic Imaging and IET Image Processing Journal, and membership on several other editorial boards. As Director of IPLab research lab (http://iplab.dmi.unict.it), Professor Battiato leads a team focused on computer vision and digital forensics. The lab collaborates extensively with law enforcement agencies through iCTLAB, a university spinoff he founded that provides digital forensic services. IPLab is recognized for its contributions to image/video forensics, with techniques implemented in commercial forensic software like AMPED Authenticate.
Maurizio Martina is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. He is a member of the Interdepartmental Center PEIC - Power Electronics Innovation Center and serves as an Associate Editor for the IEEE Transactions on Circuits and Systems I (2018-2023). His research focuses include: Digital circuits and signal processing Machine learning hardware architectures RISC-V extensions and post-quantum cryptography VLSI design for edge computing and IoT Recent publications emphasize cryptographic hardware implementations (CHIMERA, Keccak co-processors), RISC-V integration methodologies, and privacy-preserving neural network frameworks. His work spans VLSI architectures for video processing, bio-inspired electronics, and error correcting codes, with applications in cybersecurity, robotics, and biomedical systems. Scientific Recognition : Premio Nazionale Innovazione (2013) Premio dei Premi (2014) He supervises 12 PhD students across cycles 35-40 in Electrical, Electronics and Communications Engineering, including: Valeria Piscopo (2024-in progress) Alessandra Dolmeta (2022-in progress) Luigi Giuffrida (2022-in progress) Walid Walid (2019-2023) As part of the VLSILAB Group , his research explores hardware accelerators for machine learning, post-quantum cryptography on RISC-V, and bio-inspired embedded systems. Teaching activities include courses on Integrated Systems Architecture and Hardware & Wireless Security at Politecnico di Torino and Università di Pavia.
- Artificial intelligence
- Data compression
- Deep learning
- +۱۵ مورد دیگر
Enrico Magli is a Full Professor at the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin, Italy. He serves as Director of the Image Processing and Learning group and Coordinator of the 'ICT for Smart Societies' M.Sc. degree program. Additionally, he is a committee member of the PhD program in Electrical, Electronic and Communications Engineering and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. Professor Magli's research focuses on applying machine learning and deep learning methods to satellite imaging, with applications to onboard processing and image analysis on the ground. His work spans deep learning for image and video analysis, image and video compression, compressive sensing, satellite imaging, and graph signal processing. He has published over 90 journal papers with 5900+ citations and an h-index of 40 on Google Scholar. His recent publications demonstrate a strong focus on developing deep learning architectures for satellite image processing, particularly for onboard applications. His research addresses challenges in hyperspectral image compression, super-resolution, change detection, and efficient neural network architectures suitable for resource-constrained satellite environments. There's also significant work on secure authentication systems using deep learning techniques and neural network optimization for edge devices. Elevated to IEEE Fellow (2017) 'for contributions to compression and communication of remotely sensed imagery' IEEE Geoscience and Remote Sensing Society 2011 Transactions Prize Paper Award IEEE Multimedia 2019 Best Paper Award Best Paper Awards at IEEE ICIP (2015, 2019) ERC Starting grant (consolidator type) and ERC Proof-of-Concept Grant recipient Multiple Best Paper Awards Francesco Carassa (2011, 2013, 2014) Professor Magli actively supervises numerous PhD students working on cutting-edge topics in deep learning for satellite imaging, image processing, and secure authentication systems. His research is supported by significant grants including ERC projects and multiple commercial contracts with space agencies and technology companies. He leads the Image Processing and Learning (IPL) Group at Politecnico di Torino, which focuses on developing innovative solutions for satellite image analysis and compression.
Gabriella Casalinoمشاهده پروفایل
استادیار
Gabriella Casalino is an Assistant Professor at the University of Bari Aldo Moro, Department of Computer Science, and a key researcher at CILAB - Computational Intelligence Lab. Her work focuses on Computational Intelligence methods for interpretable data analysis, particularly in eHealth, Data Stream Mining, and eXplainable Artificial Intelligence (XAI) within medical and educational domains. She has contributed to innovative approaches in smartphone-based health monitoring, fuzzy logic applications, and remote vital sign detection via photoplethysmography. Education : Ph.D. in Computer Science, with advanced training at institutions like Universitat de Girona and Université de Mons. Research Trends : Recent publications highlight applications of evolving granular computing, neuro-fuzzy systems, and explainable AI in hypertension prediction, bipolar disorder monitoring, and educational data analysis. Key subfields include remote health monitoring, medical data streams, and hybrid AI models. Grants : Research funded by AIRC (Italian Cancer Research Foundation), focusing on computational methods for healthcare challenges. Labs & Collaborations : Active in CILAB, collaborating on projects involving mHealth solutions, cardiovascular risk assessment, and intelligent educational systems.
Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.
Guido Masera is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he has been actively involved in teaching and research for over two decades. He serves as a Member of the Board of Directors, Member of the GEDI Observatory for Gender Equality, Diversity and Inclusion, and Member of the Permanent University Observatory for monitoring the academic supply chain. His research interests span across channel decoders, circuits for communications, cryptography, deep learning, digital integrated circuits, field programmable gate arrays (FPGA), and hardware design. His work focuses on VLSI architectures for image and video coding, digital architectures for error correcting codes, application specific approximate computing, VLSI architectures for machine learning, digital architectures for bio-inspired processing, digital architectures for post-quantum cryptography, bio-inspired electronics for robotics and biomedical applications, RISC-V extensions and hardware accelerators, and circuit architectures for efficient machine learning and artificial intelligence. His recent publications (2025) demonstrate a strong focus on RISC-V architecture, particularly in the context of cryptographic implementations, hardware security, and post-quantum cryptography. His research group VLSILAB is actively engaged in cutting-edge research in hardware security, efficient processor design, and specialized computing architectures. Among his notable recognitions are the Premio Francesco Carassa awarded by the Telecommunications and Information Technologies Group Association (gtti) in 2010, and his recognition as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) since 2007. He also serves as an Associate Editor for several prestigious journals including ELECTRONICS (2019-present), IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS (2015-2019), and IET CIRCUITS, DEVICES & SYSTEMS (2013-2016). Professor Masera has advised numerous PhD students working on advanced topics in VLSI design, post-quantum cryptography, hardware accelerators, and machine learning implementations. His current research projects include ISOLDE (2023-2026) and TRISTAN (2022-2025), both EU-funded projects focused on RISC-V technology and domain-specific ecosystems. He leads the VLSILAB research group at the Department of Electronics and Telecommunications, which focuses on cutting-edge research in VLSI architectures, hardware security, and specialized computing systems. The group collaborates with industry partners and participates in major European research initiatives.
Dr. Shervin Shirmohammadi is a Professor at the University of Ottawa's Faculty of Engineering, specifically within the School of Electrical Engineering and Computer Science. With an impressive h-index of 41 and over 6,800 citations across 473 publications, his research has made significant contributions to the fields of computer vision, biomedical instrumentation, and health monitoring systems. His academic journey spans over two decades, beginning with work on communication architectures for virtual environments in 2001 and evolving toward practical healthcare applications. Dr. Shirmohammadi's research interests center on Computer Vision , Image Processing , and Embedded Systems with a strong focus on healthcare applications including nutrition monitoring, mental health assessment, and driver safety systems. His most influential work examines computer vision applications for health monitoring, particularly food calorie measurement systems that use smartphone cameras to analyze nutritional content. His research has evolved to include EEG-based systems for ADHD detection and serious games for autism therapy, demonstrating a consistent trajectory toward practical healthcare solutions using advanced instrumentation techniques. Dr. Shirmohammadi maintains active collaborations with researchers including A. Yassine (118 joint publications), D. Ahmed, Ali Asghar Nazari Shirehjini, and B. Hariri. His publications appear primarily in IEEE Transactions on Instrumentation and Measurement, reflecting his strong connection to the instrumentation and measurement community.
Prof. Vincenzo Romei is a Full Professor at the University of Bologna's Department of Psychology, leading the Consciousness Group. He holds a Ph.D. from the University of Rome 'La Sapienza' and has held roles at Harvard Medical School, Geneva Neurology Department, and the University of Essex, where he was a Full Professor. His research focuses on neural correlates of consciousness, using EEG, neurostimulation, and behavioral studies. He directs the Second Cycle Degree in Neuroscience and Neuropsychological Rehabilitation. Education : Ph.D. in Psychology, University of Rome 'La Sapienza' (2005) BSc/MSc in Psychology (110/110 cum laude), University of Rome 'La Sapienza' (2001) Research Interests : His work examines temporal properties of brain communication, alpha oscillations' role in sensory selection, and consciousness mechanisms. Techniques include EEG, TMS, and tACS to study perception, memory, and attention. Awards : 2020 Best Contribution Award (Transcranial Brain Stimulation Workshop) 2019 BIAL Grant (€47k) for boosting working memory 2016 Most Cited Current Biology Article (Thut et al., 2011) Grants & Leadership : Directed grants totaling over €400k, including an ERC Starting Grant and a BIAL-funded study. Serves as a Reviewer for journals like Current Biology and Neuron . Labs/Teams : Leads the Consciousness Group at the University of Bologna, collaborating internationally on neurostimulation and predictive coding models.
Marco Grangetto serves as Full Professor in the Department of Computer Science at the University of Turin, coordinating research in image processing and computer vision. His expertise spans wavelets, image/video coding, data compression, error resilient video coding, and biomedical image processing, with significant contributions to ISO JPEG2000 standardization and editorial roles in IEEE Transactions on Multimedia. His educational background includes a PhD in Electrical and Communications Engineering (2003) and MSc in Telecommunications Engineering (1999), both from Politecnico di Torino. His research integrates Artificial Intelligence and Deep Learning with medical imaging and fundamental compression theory , producing innovations in neural network pruning, capsule networks, and entropy-based models. Recent work focuses on Covid-19 diagnosis from chest X-rays and efficient 3D scene modeling. His publication trends reveal dual trajectories: applied medical AI (Covid-19 diagnostics, lung cancer segmentation) and theoretical advances (learned compression, contrastive learning, bias mitigation). This bridges clinical validation with information-theoretic foundations, particularly in resource-constrained environments. Scientific recognition includes: Premio Optime by Unione Industriale di Torino (2000) Fulbright Grant for research at UC San Diego (2001) He maintains leadership through IEEE editorial positions, ISO standardization participation, and MPAI membership. His research group develops medical datasets (UniToChest, UniToPatho) while advancing neural network efficiency for clinical deployment. Current projects focus on entropy minimization techniques and unbiased representation learning for healthcare applications.
Francesco Stradaمشاهده پروفایل
استادیار
Francesco Strada is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. He serves as a Course Lecturer for Virtual Reality and Technical Art for Cinema and Video Games, and as a Course Collaborator for multiple courses across Computer Engineering, Film and Media Engineering, and Architecture programs. He is an active member of the College of Computer, Film and Mechatronics Engineering and the College of Architecture and Design teaching committees. Dr. Strada's research focuses on Computer Graphics, Virtual Reality, Augmented Reality, and Human-Computer Interaction with particular emphasis on Embodied Conversational Agents, emotion recognition, and serious games applications. His work bridges technical computer science with psychological and human factors considerations to create more believable and effective virtual experiences. His research spans applications in education, healthcare, automotive interfaces, cultural heritage, and emergency response training. His recent publications demonstrate a strong trend toward emotionally intelligent virtual agents, VR/AR applications in specialized domains, and technical innovations in latency management and digital human representation. His work often combines psychological principles with technical implementations to enhance user experience and system effectiveness. Dr. Strada actively supervises PhD students including Alessandro Emmanuel Pecora, Stefano Calzolari, and Leonardo Vezzani, whose research focuses on Emotionally Aware Embodied Conversational Agents (E2CA) and Car AR-HUD design. He leads significant research projects including Holo-BLSD (2024-2025), a Mixed Reality tool for first aid emergency response training, and '50 shadows of AI' (2025), focusing on personalized education in corporate settings. He is a member of the CGVG - Computer Graphics and Vision Group at DAUIN, where his team develops cutting-edge applications in AR/VR, Human-Computer Interaction, User Experience, Computer Vision, Machine Learning, and Artificial Intelligence. His research has practical applications in education, training, healthcare, automotive interfaces, and cultural heritage preservation.
Eric Eatonمشاهده پروفایل
پژوهشگر
Eric Eaton is a prominent researcher in Computer Science, specializing in Artificial Intelligence, Reinforcement Learning, and Federated Learning. His work bridges theoretical advancements with practical applications in healthcare, robotics, and educational technology, as evidenced by his collaborations with institutions like the Vector Institute and co-authors such as Marcel Hussing and Amir-massoud Farahmand. Research Focus: Lifelong Learning, Object-Centric Representation, and Algorithmic Fairness Key Contributions: ELLA algorithm, Distributed Continual Learning frameworks, and AI integration in surgical video analysis His recent publications address critical challenges in high update ratio reinforcement learning, federated learning for surgical data, and ethical considerations in algorithmic fairness. These works highlight his interdisciplinary approach, combining AI with healthcare and education. Eaton's leadership in projects like FORLA and Slot-BERT demonstrates innovation in unsupervised learning and temporal coherence. His involvement in the CS2023 curriculum design underscores his commitment to advancing computer science education.
Marco Carli is a Full Professor at the Department of Industrial, Electronic, and Mechanical Engineering, Roma Tre University, Italy. He holds a Laurea in Telecommunication Engineering from Università degli Studi di Roma 'La Sapienza' and a Ph.D. from Tampere University of Technology. His research focuses on digital signal and image processing applied to multimedia communications, including digital watermarking, multimedia quality evaluation, and information security. He has led projects such as EHEM (medieval architecture modeling), ISEEYOO (AI-based anomaly detection), and INSECTT (secure IoT-AI systems). Carli serves as an Associate Editor for IEEE Transactions on Image Processing and Area Editor for Signal Processing: Image Communication. He is an IEEE Senior Member. His work spans over 55 journal publications and numerous conferences, addressing topics like immersive VR applications, cybersecurity, and perceptual quality metrics. Education: Laurea in Telecommunication Engineering, Università di Roma 'La Sapienza', 1990s Ph.D. in Telecommunication Engineering, Tampere University of Technology, Finland Projects: EHEM: Digital modeling of medieval architecture and art ISEEYOO: Anomaly detection in Cyber-Physical Systems INSECTT: Secure IoT systems with AI Research Interests: Signal/image processing for multimedia Quality evaluation and watermarking Cybersecurity and IoT applications Awards: None explicitly listed Grants/Advising: Multiple EU-funded projects (e.g., ImmerSAFE, RESISTO, ATENA) and collaborations with industry partners like Thales Alenia Space.
Francesco Ragusaمشاهده پروفایل
پژوهشگر ارشد
Francesco Ragusa is a Research Fellow at the University of Catania, Italy, holding an Industrial Doctorate in Computer Science (2021). He spent part of his PhD at the University of Hertfordshire, UK. His work focuses on First Person (Egocentric) Vision, including Human-Object Interaction, Industrial Applications, and Augmented Reality. He co-founded NEXT VISION s.r.l., an academic spin-off from the University of Catania since 2021. Key projects include the MECCANO dataset for industrial human-object interactions and the EGO-EXO4D initiative analyzing skilled human activity from multi-perspective views. Research interests span Computer Vision, Pattern Recognition, and Machine Learning. He contributed to seminal datasets like MECCANO and ENIGMA-51, advancing understanding of human behavior in industrial settings. His work emphasizes practical applications, such as wearable assistive systems and visual navigation solutions. Ragusa has delivered tutorials at major conferences (e.g., ICIAP, VISIGRAPP) on First Person Vision’s history, challenges, and trends. He actively promotes industrial collaborations and has secured grants including PNRR MUR (Code E63C22001940006) and EU funding under Next Generation EU. His teaching and professional activities include organizing workshops on egocentric vision for AI-driven assistants and industrial safety systems. Current research directions involve multimodal synthetic data utilization, gaze-based interaction analysis, and cross-modal fusion for human-robot collaboration.
Lorenzo Favalli is an Associate Professor of Telecommunications at the University of Pavia, Italy. He received his Laurea degree in Electronic Engineering from Politecnico di Milano in 1986 and his Ph.D. in Electronic Engineering from the same institution in 1991. He has been with the University of Pavia since 1991, initially as an Assistant Professor before becoming Associate Professor in 2000. His teaching includes Digital Communications, Wireless Communications Systems, and Multimedia Communications. Research Focus: His work spans signal analysis (particularly video) and transmission technologies in wired/wireless networks, with emphasis on adaptive techniques for improving communication reliability. Recent interests include adaptive video streaming and cognitive networks. He has authored 30+ journal papers and 100+ conference publications. Awards: AEI Best Thesis Award (1987) Computer in the Cathedral Contest Prize (1989)