Find Academic Supervisors

• Bioinformatics
• Algorithms
• Genomics
• +3 more

Roles & Affiliations: Professor at the Department of Computer Science, University of Pisa since at least 2005. Active in teaching and research in Bioinformatics and Algorithms. Collaborative roles at University of Siena for Bioinformatics master programs. Affiliations: University of Pisa (primary), University of Siena (visiting roles). Education Background: PhD in Computer Science (implied via academic rank) Advanced training in Computational Biology and Algorithm Design Research Interests: Focuses on string algorithms with applications in bioinformatics , including genomic sequence analysis, variant discovery, and algorithmic foundations. Specializes in elastic-degenerate string processing, pangenome graphs, and efficient data structures for large-scale genomic data. Develops tools like WhatsHap for haplotype assembly and RettDb for disease genomics. Teaching Contributions: Core courses in Algorithms, Bioinformatics, and Programming for undergrad/graduate students Master's courses in Bioinformatics and Data Science (University of Pisa/Siena) PhD-level workshops on genomic algorithms Recent Trends in Articles: Recent work emphasizes deep learning applications in genomics , efficient string indexing methods , and pangenome analysis . Explores new paradigms for comparing elastic-degenerate strings and managing genomic variation data at scale. Active in algorithmic foundations and interdisciplinary applications. Grants & Labs: Leads research teams in bioinformatics algorithm development. Involved in EU-funded projects on computational genomics and algorithmic methods. Collaborates with medical institutions on translational research (e.g., Rett syndrome genomic database).

• Decentralized Online Social Networks
• Blockchain Technology
• NFTs and the Metaverse
• +3 more

Barbara Guidi is an Associate Professor at the Department of Computer Science, University of Pisa. Her research focuses on Decentralized Online Social Networks, Blockchain Technology, NFTs, and the Metaverse. She is a founding member of IEEE METASIG (IEEE SIG on Metaverse) and collaborates with the IEEE Social Networks Technical Committee. Dr. Guidi has led projects like HELIOS under the H2020 initiative and serves on editorial boards for journals such as Plos One and IEEE Access. Her work explores blockchain applications in social media, economic dynamics in decentralized platforms, and bot detection in Web3 environments. Education: She studied at the Department of Computer Science, University of Pisa. Research interests include peer-to-peer networks, decentralized storage, and social network analysis. She has advised students on topics like Blockchain Technology applied to Social Media and NFT/Metaverse integration. Key contributions include frameworks like AWESOME for Web3 social media analysis and studies on Axie Infinity's economic models. She actively participates in workshops like OASIS, addressing challenges in online social networks. Her work emphasizes ethical blockchain applications and decentralized systems for social good. Labs/Teams: She contributes to the IEEE METASIG community and collaborates with institutions like the University of Bicocca - Milan on text-mining in decentralized social media.

Andrea MichienziView profile

Assistant Professor

• Decentralized Social Networks
• Blockchain Technology
• Metaverse
• +3 more

Andrea Michienzi is an Assistant Professor in the Department of Computer Science at the University of Pisa. His research focuses on decentralized social networks, blockchain technology, and the metaverse, with an emphasis on improving privacy, security, and economic dynamics in Web3 environments. He has contributed to frameworks like AWESOME for analyzing Web3 social media and has explored challenges in NFT security, P2E gaming economies, and community management in decentralized systems. Teaching: He instructs the course Basi di dati e Laboratorio di programmazione Web within the Bachelor of Digital Humanities program, emphasizing practical coding and database applications. Research awards: He received a Best Paper Award in 2018 for work related to dynamic community detection in decentralized networks. His publications span topics like bot detection in blockchain games, wealth distribution analysis, and cryptographic protocols for secure messaging. His work integrates computer science, economics, and sociology to address scalability, trust, and ethical challenges in emerging decentralized platforms.

Francesco TosoniView profile

Research Fellow

• Lossless Data Compression
• String Indexing
• Big Data Analytics
• +4 more

Francesco Tosoni is a Research Fellow at the University of Pisa's Department of Computer Science, affiliated with the Acube Laboratory (A³), directed by Prof. P. Ferragina. He holds a PhD in Computer Science from the University of Pisa, completed in 2024, and an MSc in Computer Science and Networking from the University of Pisa and Sant’Anna School of Advanced Studies (2020). His research focuses on lossless data compression, string indexing, big data analytics, and energy-efficient algorithms. He has conducted collaborative work with the Software Heritage team and was a visiting researcher at the University of Chile in 2022. Awards include the Con.Scienze 2020 Best Thesis Award and recognition as the top graduate in his MSc program. Recent projects include developing compressed formats for matrices and trie structures, with applications in green computing and efficient storage systems. Education: PhD in Computer Science, University of Pisa (2024), advisors: P. Ferragina and G. Manzini MSc in Computer Science and Networking, University of Pisa & Sant’Anna School (2020) BSc in Computer and Electronic Engineering, University of Perugia Research Interests: Lossless data compression techniques, energy-efficient algorithms, matrix and trie compression, stringology, big data analytics, and urban mobility platforms. Recent work emphasizes environmental sustainability in computing through optimized compression formats. Key Contributions: Developed the CoCo-trie compression method for efficient string storage Proposed novel compressed formats enabling direct matrix operations without decompression Recipient of grants for urban mobility algorithms and software heritage projects Awards: Con.Scienze 2020 Best Thesis Award (MSc thesis) Best Graduate in MSc Computer Science and Networking (2018/19) Advising & Grants: Supervised Federico Ramacciotti's MSc thesis on compression techniques in key-value stores Recipient of a 2020 research grant on algorithms for urban mobility platforms Labs & Teams: Core member of the Acube Laboratory, collaborating with global teams such as the Software Heritage initiative and Prof. Gonzalo Navarro's group in Chile.

• Cloud Computing
• Fog Computing
• SDN Microservices
• +7 more

Giuseppe Di Modica is an Associate Professor at the Department of Computer Science - Science and Engineering, University of Bologna. His research focuses on cloud computing, edge/fog systems, IoT, and digital twins for industrial applications. He has contributed to frameworks like IoTwins and H2F, addressing challenges in distributed computing, microservice orchestration, and latency optimization in SDN architectures. His work spans containerized application management, geo-distributed big data processing, and security in serverless environments. Key research themes include: Cloud-edge continuum orchestration IoT service placement in fog environments SDN microservice architecture design Lightweight virtualization for Industry 4.0 Validation of performance models for microservices His publications emphasize practical implementations, such as the Torch orchestrator for multi-cloud deployments, and frameworks for fault-aware cloud provisioning. Ongoing work explores digital twin platforms for manufacturing and smart facility management, leveraging edge-cloud synergy and real-time data analytics. He holds a permanent academic position with no part-time designation noted. Contact: giuseppe.dimodica@unibo.it, +39 051 20 9 3866.

Gabriel E. HineView profile

Researcher

• Biometrics
• Signal Processing
• Information Security
• +13 more

Gabriel E. Hine is a Postdoc researcher at the Biometric Systems and Multimedia Forensics Lab within the Department of Engineering at Roma Tre University, Italy. He is actively engaged in research at the intersection of signal processing, biometrics, and information security, and contributes to teaching in advanced signal processing and biometric systems. Bachelor’s Degree in Electronic Engineering, Roma Tre University (2013, cum laude) Master’s Degree in Information and Communication Technology Engineering, Roma Tre University (2015, cum laude) PhD in Applied Electronics, Roma Tre University (2018) Research collaboration at Telefonica I+D, Barcelona (2016) Research involvement in EU H2020 ENCASE and PRIN 2011/2012 projects His research focuses on biometric cryptosystems, template protection, and privacy-preserving biometric recognition, with significant contributions to fingerprint, palmprint, EEG, and signature-based systems. He has also conducted influential work on online social media dynamics, particularly analyzing 4chan’s /pol/ forum. The analysis of his recent publications reveals a strong trend in developing secure and unlinkable biometric templates using deep learning, sparse signal representations, and zero-leakage frameworks. His work spans both theoretical formulation and experimental validation on real-world data, particularly in finger-vein and palm-vein recognition. He also explores novel biometric modalities such as in-air 3D signatures and resting-state EEG. Best Paper Runner-Up, ICWSM-17 (2017) Selected as 'Best of Arxiv' paper Widely covered in Nature , MIT Technology Review , The Independent , Vice , and Italian media Hine has served as a lecturer and teaching assistant for courses including 'Biometric Systems' and 'Signal Theory' at Roma Tre University. He has led a didactic laboratory on biometric systems, guiding students in implementing and analyzing biometric recognition solutions. His research is supported by major grants such as EU H2020 ENCASE and PRIN 2011/2012. He collaborates extensively with Prof. Patrizio Campisi and other researchers in the BioMedia4n6 lab. He is a core member of the BioMedia4n6 research group, which specializes in biometrics, data hiding, and blind deconvolution, applying advanced signal processing techniques to multimedia forensics and security challenges.

Florin Silviu ManeaView profile

Professor

• String Algorithms and Combinatorics
• String Solving
• Efficient Algorithms and Data Structures
• +6 more

Florin Silviu Manea is a Professor for Theoretical Computer Science at the Institute of Computer Science, University of Göttingen, Germany. He has held this W3-Professor position since 2022, funded by the Heisenberg programme of the DFG. Prior to this, he was a W2-Professor for Fundamentals of Computer Science at the same university (2019-2022). His academic career includes research positions at Kiel University (2011-2019) and an Alexander von Humboldt fellowship at the University of Magdeburg (2009-2011). Dr. Manea received his PhD in December 2007 from the University of Bucharest with the distinction Summa cum Laude. His PhD thesis was titled "Networks of bio-processors" and was supervised by Victor Mitrana. He also earned a Master of Science (2005) and Bachelor of Science in Computer Science (2003) from the University of Bucharest, both with perfect GPA scores of 10/10. Professor Manea's research focuses on the theoretical foundations of computer science, with particular emphasis on string algorithms and combinatorics. His work explores the intricate relationships between formal language theory, automata theory, and practical applications in string solving. He has made significant contributions to understanding pattern matching with variables, combinatorial properties of strings, and the computational aspects of word equations. His research bridges theoretical concepts with practical applications in areas like bioinformatics and programming language theory. Analysis of Professor Manea's recent publications reveals a strong focus on string algorithms, particularly in the areas of pattern matching, word equations, and combinatorics on words. His work often explores the computational complexity of string problems while developing efficient algorithms to solve them. A recurring theme is the investigation of repetitions, palindromes, and gapped structures in strings, with applications ranging from DNA sequence analysis to programming language design. His research demonstrates a consistent pattern of advancing both the theoretical understanding and practical applications of string algorithms. Professor Manea has received several prestigious awards for his contributions to computer science: Lehrpreis 2020 (Teaching Award) by CS-students from Göttingen The "Tudor Tanasescu" Prize of the Romanian Academy (2009) Honorable Mention at ACM International Collegiate Programming Contest World Finals (2004, 2007) As an advisor, Professor Manea has successfully supervised multiple PhD students to completion with highest honors, including Maria Kosche (2023), Stefan Siemer (2024), and Tore Koß (2024), all achieving Summa cum Laude distinctions. He currently leads a research group focused on theoretical computer science at the University of Göttingen. His research is supported by significant funding, including a DFG grant for "String Constraint Solving: Combinatorial, Algorithmic, and Language-Theoretic Approaches" and continued Heisenberg-programme funding until 2027 for his project "Combinatorial String Solving." Professor Manea leads the Theoretical Computer Science research group at the University of Göttingen, which focuses on string algorithms, combinatorics, and computational models. His group actively collaborates with researchers worldwide and has organized several major conferences including DLT 2024, NCMA 2024, and CSL 2022. The group offers supervision for BSc and MSc theses on both theoretical and applied topics related to their research areas.

• Renewable Energy
• Mechanical Engineering
• Environmental Engineering
• +3 more

Piofrancesco Barone is affiliated with the University of Calabria (UNICAL) as a researcher, focusing on renewable energy systems and sustainable technology development. His work bridges mechanical engineering and environmental applications, particularly in marine energy solutions. Current research emphasizes wave energy converters and LNG regasification process optimization Collaborates on power conversion systems integration with electrical networks Active in thermodynamic analysis and energy efficiency improvements Recent publications demonstrate his specialization in hydraulic power take-off systems and exergy analysis for green ship technologies. His work explores control strategies for point-absorber wave energy converters, with field applications in coastal regions like Calabria. While specific educational details remain unspecified, his research trajectory clearly aligns with energy engineering disciplines. Analysis of his 2023-2024 publications reveals consistent focus areas including: Wave energy conversion optimization Hydraulic system design for marine applications Exergy analysis methodologies Grid integration of renewable systems LNG process efficiency Coastal energy harvesting

• Electrical Engineering
• Renewable Energy
• Smart Grids
• +5 more

Nicola Sorrentino is an Assistant Professor at the Department of Mechanical, Energy and Management Engineering of the University of Calabria since 2004. He teaches courses on Electrical Systems Engineering and Electricity Market for Management Engineering programs. A member of the Graduate School 'Archimedes' , he coordinates modules in the University Master in Energy Management and has served on technical committees for energy-related consortia. Education: PhD in Computer and Systems Engineering (1999), University of Calabria. His research focuses on electrical power systems control and management under market dynamics , particularly addressing smart grid technologies , renewable energy integration , and energy communities . Key projects include participation in COFIN, PRIN , and PON initiatives for distributed generation and grid optimization. Recent publications (2024-2025) emphasize renewable energy communities , machine learning for energy forecasting , and nanogrid control strategies . The work explores energy sharing , imbalance cost reduction , and storage optimization in decentralized systems. Scientific Award: 1999 scholarship for 'Integrated control systems for real-time control of the engines' (University of Salerno). As a co-founder of academic spin-off Crete Energie Speciali srl , he promotes renewable energy production in small municipalities through the Laboratorio di Sistemi Elettrici per l'Energia e le Fonti Rinnovabili (LASEER) , which develops power electronics , smart grid prototypes , and active filtering devices .

• Soil Hydrology
• Agricultural Engineering
• Environmental Science
• +3 more

Massimo Iovino is a Full Professor in Agricultural, Food, and Forestry Sciences at the University of Palermo, affiliated with the Department of Agricultural, Food, and Forestry Sciences. His research focuses on soil hydrology, irrigation systems, and hydraulic properties of soils, with emphasis on sustainable agricultural practices and environmental applications. He holds office hours on Thursdays at the Viale delle Scienze campus. Research interests include soil hydraulic conductivity, infiltration dynamics, water retention mechanisms, and the impact of organic amendments on soil quality. He has extensively studied the effects of biochar, compost, and microplastics on soil properties, as well as the optimization of irrigation methods in arid regions. His work integrates experimental field studies with computational modeling, such as Beerkan infiltration experiments and Hydrus-2D/3D simulations. Recent publications highlight advancements in soil parameterization (e.g., Haverkamp model), assessment of constructed wetlands, and innovations in irrigation technology. His research contributes to improving water management strategies and mitigating environmental challenges like soil erosion and nutrient leaching. Ongoing projects involve green roof substrates, sensor-based irrigation systems, and the effects of climate change on soil dynamics. Key collaborations include experiments at the Sparacia experimental area and the Villabate open-air laboratory. He has advised on PNRR-funded projects and contributes to the University of Palermo's research initiatives in hydrology and agro-environmental engineering.

• Multi-criteria analysis
• Problem structuring methods
• Decision-making processes
• +15 more

Isabella Maria Lami is a Full Professor at the Interuniversity Department of Territorial Sciences, Planning and Policies (DIST) , Polytechnic University of Turin , where she plays a key role in research, teaching, and institutional leadership. She is a member of the Board of Directors, the Student Contribution and Planning Commission (STUDI), the Student Team Commission, the Employers' Delegation, and the Future Urban Legacy Lab (FULL) Interdepartmental Center. She has been consistently involved in the Urban and Regional Development Doctoral College for over a decade, supervising PhD research and teaching advanced courses such as Problem Structuring Methods for facing urban uncertainty . Her educational background is not explicitly detailed in the provided texts, but her academic leadership and research output suggest a strong foundation in urban planning, evaluation, and decision sciences. Her research interests are deeply interdisciplinary, focusing on multi-criteria analysis , problem structuring methods (PSMs) , decision-making processes , and the evaluation of urban plans and projects . She integrates behavioral economics, operations research, and sustainability sciences to address complex urban challenges. Her work is closely aligned with SDG 11: Sustainable Cities and Communities , particularly through the development of indicators, serious games for education, and frameworks for urban regeneration. She emphasizes the integration of technical, value-based, and relational perspectives in planning. Her recent publications (2022–2025) reflect a strong trend toward urban sustainability , adaptive reuse of buildings , value creation in architecture , and innovative teaching methods such as serious games. She frequently collaborates with researchers like Elena Todella, Beatrice Mecca, and Francesca Abastante, publishing in high-impact journals such as European Journal of Operational Research , Sustainability , and Land , as well as in book chapters for Palgrave and Springer. Among her scientific recognitions is the Open Badge for Learning to Teach with Innovative Teaching Project (L2T_ITP) , highlighting her commitment to pedagogical innovation. She has also led competitive research projects such as LOTUS (2019–2022) and the earlier URBAX2 Erasmus+ project (2002–2004), demonstrating sustained funding success. In terms of teaching and advising , she supervises PhD students including Beatrice Mecca (thesis: Fostering value creation in architecture ) and Federica Rotondo (thesis: Reinterpreting Urban Transitions ). She teaches in both doctoral and master’s programs, including Economic Evaluation of Projects and Architecture and Urban Economics , across disciplines such as Architecture, Urban Planning, and Aerospace Engineering. She also led a course on promoting campus sustainability through serious games. She is a core member of the Future Urban Legacy Lab (FULL) , an interdepartmental research center dedicated to advancing sustainable urban transitions through integrated, multi-methodological approaches. Her work emphasizes collaborative, practice-oriented, and ethically grounded planning methodologies for resilient and inclusive cities.

Davide BrunelliView profile

Associate Professor

• Energy Harvesting
• Wireless Sensor Networks
• Internet of Things
• +18 more

Davide Brunelli is an Associate Professor in the Department of Industrial Engineering at the University of Trento, Italy. His research focuses on energy harvesting, ultra-low-power embedded systems, and wireless sensor networks, with applications in IoT, environmental monitoring, and smart infrastructure. He has led numerous EU-funded and industrial research projects and maintains active collaborations with institutions such as ETH Zurich and the University of Bologna. Education: Ph.D. in Electrical Engineering, Telecommunications and Computer Science, University of Bologna (2007) M.Sc. in Electrical Engineering (summa cum laude), University of Bologna (2002) His research interests include energy scavenging for embedded systems, low-power wireless sensor networks, energy-aware communication protocols, battery-less systems, indoor positioning, and IoT applications in agriculture, structural health, and smart buildings. His work bridges hardware and software optimization for sustainable, self-powered sensing systems. The most recent publications reflect a strong trend toward self-powered and transiently-operated systems, energy-neutral architectures, and intelligent sensing with applications in environmental monitoring, industrial IoT, and localization. Key themes include energy harvesting integration, ultra-low power communication, and real-time adaptive algorithms. Scientific Awards: Best Paper Awards at IEEE/ACM conferences (2011, 2014, 2016, 2017, 2018, 2020, 2021) Research.com Computer Science in Italy Leader Award (2024, 2025) Research.com Electronics and Electrical Engineering in Italy Leader Award (2025) Brunelli has supervised numerous research projects and advised EU and national funding agencies as an independent expert. He has led key initiatives such as IoT Proto Lab, GreenDataNet, and EnerViS, and has secured significant industrial partnerships with Telecom Italia, STMicroelectronics, and Hewlett-Packard. He serves as Editor-in-Chief of the journal Sensors and has organized major conferences including IEEE Metrology for Industry 4.0 and ACM ENSSys. He is actively involved in technology transfer, co-founding WISPES srl and transferring energy harvesting innovations to Telecom Italia. His lab supports a testbed for CPS and WSN applications, including deployments in tunnels and smart buildings.

• Artificial Intelligence
• Machine Learning
• Abstract Argumentation
• +2 more

Gianvincenzo ALFANO is a Researcher at the Department of Computer Engineering, Modelling, Electronics and Systematics (DIMES) at the University of Calabria. His work focuses on abstract argumentation frameworks, epistemic reasoning, and computational complexity. University: University of Calabria Department: Department of Computer Engineering, Modelling, Electronics and Systematics Academic Rank: Researcher Research Interests: Gianvincenzo specializes in abstract argumentation, exploring formal foundations, complexity analysis, and applications in artificial intelligence. His research spans epistemic reasoning, preference handling, and incremental computation in dynamic knowledge bases. Recent Publications: Over the past two years, he has published extensively on topics such as physics-informed neural networks in federated learning, credulous acceptance in high-order frameworks, and complexity of epistemic argumentation. His work emphasizes formal logic, algorithm design, and uncertainty handling in AI systems.

• Computer architectures and Computer aided design
• Data science
• Computer vision and AI
• +3 more

Walter Gallego Gomez is a PhD Student in Computer and Systems Engineering (39th cycle, 2023-2026) and an External Lecturer/Teaching Assistant at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. His academic and research journey is supported by an EBRAINS-Italy research grant. Bachelor's in Electronic Engineering (University of Antioquia, 2015) Master's in Computer Engineering (Polytechnic University of Turin, 2018) His research intersects life sciences and computer science, focusing on bioinformatics algorithms, neuromorphic hardware (Loihi2/Lava), and their implementation. He collaborates with the Electronic Design Automation (EDA) group and external entities like Candiolo Oncology Center and Telluride Neuromorphic Cognition Engineering workshop. Teaching roles include System-on-chip architecture (2024/25) and Applied AI and machine learning (2023/24-2024/25) as a course collaborator. Recent publications highlight trends in somatic structural variant detection and neuromorphic ecosystem benchmarking. His work spans automotive embedded systems (Marelli, 2018-2021), academic research assistantship (2021-2023), and interdisciplinary collaborations.

• Software Engineering
• Data Quality
• Automated Decision Making
• +7 more

Antonio Vetro is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Polytechnic University of Turin. He specializes in experimental methodologies for software engineering with focus on software and data quality improvement, algorithmic fairness, and socially sustainable technology design. His research interests span Responsible AI: From principles to industrial practices Data quality measurement and improvement Fairness in automated decision systems Public interest technology Technical debt management Generative AI applications His recent publications focus on bias detection in datasets, GDPR compliance tools, and technical debt analysis in industrial projects. Key trends include Algorithmic fairness in healthcare applications Automated compliance assessment Data quality for ethical AI Quantum computing research Scientific recognitions include BEST PAPER AWARD - IEEE AICT 2024 Best Paper Award EGOV-2020 Siebel Energy Institute - Smart Energy 2016 Best paper award at IDOESE 2010 He advises PhD students in responsible AI and data ethics, while also serving on editorial boards like ACM Journal of Data and Information Quality and International Journal of Technoethics. Current roles include membership in ISO/IEC JTC1 SC7/WG6 and UNINFO committees for software engineering standards.