Find Academic Supervisors

• Transport Systems
• Rail Transport Systems
• Urban Transport Systems
• +12 more

Bruno Dalla Chiara is a Full Professor in the Department of Environment, Land and Infrastructure Engineering (DIATI) at the Politecnico di Torino, where he has been a faculty member since 1999, progressing from university researcher to associate professor and full professor since 2019. He is affiliated with the Interdepartmental Center CARS@PoliTO for Automotive Research and Sustainable Mobility and serves as the Mobility Manager of the university since 2013. His leadership extends to coordinating the Mobility group within the RUS network (Network of Universities for Sustainable Development) for 2023–2026. Education: He earned his M.Sc. in Mechanical Engineering from the Polytechnic of Turin in 1993 and a PhD in Transport Engineering (administrative seat: University of Trieste) in 1997, specializing in technological innovation and telematics for transport. Research Interests: Bruno Dalla Chiara’s research focuses on sustainable and intelligent transport systems. His key areas include: Rail, urban, and cable-driven transport systems Intermodal and freight logistics Intelligent Transport Systems (ITS) Transport data analytics and modeling Electrification and energy efficiency in transport Mobility as a Service (MaaS) His work integrates engineering, policy, and sustainability, aligning with SDG Goals 9, 11, and 12. Publication Trends: His recent publications (2023–2025) emphasize sustainable urban mobility, rail innovation, MaaS governance, and data-driven transport solutions. There is a strong focus on decarbonization, electrification, and safety technologies like ADAS. His work spans journals and conference proceedings in transportation engineering, sustainability, and railway technology, often combining technical analysis with socioeconomic impact assessment. Scientific Awards: The IET Premium Awards (2014) Best Article Award from Ingegneria Ferroviaria (2014) Start Up Torino Piemonte (2006) Advising and Grants: He supervises PhD students in the Energetica program, including Flavio Cappelli and Simona Gurri’. He has led numerous research projects funded by national (PRIN), regional, EU (PNRR, Horizon), and corporate sources. He is the Scientific Director of multiple commercial and non-commercial research agreements, including the TorinoMaaS4Italy project. His grants focus on sustainable transport, intelligent systems, and infrastructure innovation. Labs and Teams: He leads the Transport Systems and Mobility research laboratory at DIATI and is a key member of CARS@PoliTO. His team works on simulation, data analytics, and technological innovation in transport, collaborating with industry and public agencies on real-world mobility challenges.

• Artificial Intelligence
• Deep Learning
• Image Analysis
• +9 more

Lia Morra is a fixed-term Researcher at the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where she is also a member of the SmartData@PoliTO – Big Data and Data Science Laboratory. She is actively involved in research, teaching, and editorial roles, focusing on artificial intelligence and its applications in vision and data science. She teaches in the College of Computer, Film and Mechatronics Engineering and the College of Management and Production Engineering. Research Interests: Her work centers on artificial intelligence, deep learning, image analysis, and neural-symbolic integration. She applies these techniques to medical imaging, satellite data, autonomous systems, and human-computer interaction. Her research bridges symbolic reasoning with neural networks, emphasizing explainability, robustness, and real-world deployment. Publication Trends: Her recent publications (2023–2025) show a strong focus on neuro-symbolic AI, explainable models, medical imaging, and efficient deep learning. She frequently publishes in top-tier journals and conferences such as Medical Image Analysis , IEEE ACCESS , and IJCNN, with applications in healthcare, autonomous driving, and privacy-preserving AI. Scientific Awards and Recognition: Open badge RIMINI SCHOOL 2025 “SUCCESSFULLY PARTICIPATE IN CALLS FOR RESEARCH FUNDING” Learning to Teach (L2T) Advising and Grants: She supervises multiple PhD students in Computer and Systems Engineering, including Pietro Basci, Rosario Milazzo, Alessandro Sebastian Russo, and Luca Piano. She is the Scientific Responsible for several research projects, including EU-funded CAMOUFLAGE and multiple commercial contracts on AI for medical imaging, satellite data, and digital transformation. She also serves on editorial boards for Frontiers in Medical Engineering and IEEE Consumer Electronics Magazine . Labs and Teams: She is a core member of the GRAINS (GRAphics and INtelligent Systems) research group at DAUIN, focusing on intelligent systems, computer vision, and data science.

Luca MaianoView profile

Research Fellow

• Computer Vision
• Deep Learning
• Machine Learning
• +7 more

Luca Maiano is a Research Fellow at AlcorLab (Vision, Perception, and Learning Laboratory) within the Department of Computer Science at Sapienza University of Rome. He holds a PhD in Data Science and both bachelor's and master's degrees in Computer Engineering from the same institution. Research Interests: Computer Vision Deep Learning and Continual Learning Media Forensics and Deepfake Detection AI Security and Adversarial Machine Learning Fake News and Disinformation Detection Urban Mobility AI Systems His recent work focuses on detecting synthetic media through multimodal and feature-fusion approaches, adapting models to evolving generative techniques, and securing AI systems against data poisoning. He has contributed to cutting-edge research in deepfake detection, ground-to-aerial image matching, and cooperative urban mobility ecosystems. Recent Publication Trends: His publications from 2024–2025 span top venues in computer vision and AI, showing a strong focus on the security and robustness of AI systems in detecting disinformation. The work integrates deep learning with forensic analysis, emphasizing continual adaptation and multimodal fusion for real-world deployment. Scientific Contributions: Active contributor to media forensics and AI security Published in Pattern Recognition Letters, Computer Vision and Image Understanding, ECIR, IGARSS, and LNCS Guest editor for special issue on disinformation detection Advising and Grants: While no formal students or grants are listed, his role as a research fellow under Prof. Irene Amerini suggests involvement in funded research projects and potential mentorship within the AlcorLab research group. Laboratory Affiliation: Member of AlcorLab (Vision, Perception, and Learning Laboratory) at Sapienza University, a research group focused on computer vision, machine learning, and perception systems.

Gianluca CostaView profile

Associate Professor

• Emergency Surgery
• Trauma Surgery
• Minimally Invasive Surgery
• +5 more

Gianluca Costa is an Associate Professor of General Surgery at Link Campus University , with a concurrent role as Adjunct Professor of General Surgery at University of Rome "Sapienza" since 2006. His clinical and academic focus spans Emergency Surgery, Trauma Surgery, Minimally Invasive Surgery, and Robotic Surgery, informed by leadership positions in national health authorities and editorial contributions to clinical guidelines. Education: MD from University of Rome "La Sapienza" (1987) PhD in Experimental Methodologies and Technologies Applied to Surgery (VIII Cycle) Specialization in General Surgery from University of Rome "Tor Vergata" Research Interests center on surgical innovation in emergency contexts, including: Frailty assessment in elderly surgical patients Robotic and 3D-guided minimally invasive techniques Colorectal cancer surgical outcomes Open abdomen management for complex trauma Scientific Contributions include the FRAILESEL Study and leadership in the International Register of Open Abdomen (IROA) . His awards include the 2011 Research Grant for Best Poster at the GREAT International Network Congress. Academic Leadership: He has directed training programs in Emergency Surgery, served as co-supervisor for surgical theses, and organized emergency surgical activities at the Campus Bio-Medico University's Surgery Center since 2020.

Christian MicheloniView profile

Associate Professor

• Pattern Recognition
• Active Vision
• Neural Networks
• +3 more

Christian Micheloni is an Associate Professor at the University of Udine's Department of Mathematics and Computer Science. He holds a Laurea (cum Laude) and Ph.D. in Computer Science from the University of Udine (2002 and 2006 respectively). His research focuses on Active Vision, Pattern Recognition, and Resource Aware Networks. He has been involved in European projects like MUSAS (2008-2010) and HAMLet (2006-2008), and collaborates with international research centers and industry. Key research areas include person re-identification using neural networks, trajectory analysis, and camera network optimization. He has received the Best Paper Award at the International Conference on Distributed Smart Cameras (2014) and serves as an editor for the IEEE Journal of Selected Topics in Signal Processing. His work emphasizes real-time surveillance systems and adaptive sensor networks to manage computational and power constraints. Micheloni teaches courses like Artificial Vision and advises post-doctoral researchers. He maintains an active lab (AVires Lab) and offers post-doctoral positions. His publications span journals like IEEE Transactions on Pattern Analysis and Machine Intelligence, and conferences such as CVPR and ICCV.

• 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).

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.

• Thermal Engineering
• Industrial Energy Systems
• Machine Learning Applications in Energy
• +3 more

Luca Bergamasco is a Fixed-term Tenure-Track Assistant Professor at the Department of Energy (DENERG) , College of Electrical and Energy Engineering , Politecnico di Torino. His academic career spans multiple teaching roles across Electrical, Energy, Mechanical, Aerospace, and Automotive Engineering colleges, with a focus on computational heat transfer and solar energy technologies. Faculty of Electrical and Energy Engineering Member of Mechanical, Aerospace, and Automotive Engineering College Dr. Bergamasco's research centers on thermal engineering and industrial energy systems , combining machine learning with traditional thermal analysis. Key projects involve optimizing phase change materials for energy storage and developing neural network models for industrial applications. His recent publications (2023-2025) reveal a strong emphasis on thermal conductivity enhancement , CO2 reduction , and machine learning integration in energy systems. Collaborative work with Alessandro Ribezzo on metal wool-phase change composites demonstrates practical applications of his research. Teaching activities include Advanced Solar Energy Technologies and Computational Heat and Mass Transfer courses at both PhD and Master's levels. He actively supervises PhD students and contributes to courses like Machine Learning for Energy Applications .

Vincenzo BonniciView profile

Associate Professor

• Bioinformatics
• Artificial Intelligence
• Computational Biology
• +3 more

Vincenzo Bonnici is an Associate Professor in Informatics at the Department of Mathematical, Physical and Computer Sciences , University of Parma, Italy. His academic career includes a PhD in Computer Science from the University of Verona (2015), preceded by a master’s degree from the University of Catania (2011). He has held research positions at prestigious institutions, including the Institute for Genomics and Bioinformatics (IGB) , University of California, Irvine (2013–2014). Education BSc/MSc in Computer Science from University of Catania (2008/2011) PhD in Computer Science from University of Verona (2015) His research focuses on bioinformatics and computational biology , with a strong emphasis on subgraph matching algorithms for biomedical graphs, genomic sequence analysis using information theory, and parallel computing for biological networks. His work spans pangenomics, phylogenomics, and non-coding RNA studies, with applications in GPU and SMP architectures. The article trends reflect his core expertise in graph algorithms and computational genomics. Key contributions include MULTI-GRAPHMATCH (2025) for multigraph analysis, ARC-MATCH (2024) for edge domain-based graph querying, and foundational work on pangenome discovery (e.g., PANDELOS series, 2023). Parallel computing and information theory are recurring themes across his publications. Scientific awards include the ICPR 2014 international graph-matching contest and a best poster award at the Jacob T. Schwartz International School for Scientific Research. He has served as a speaker at 12 international conferences. Teaching includes courses on Artificial Intelligence Algorithms (2025/2026), Artificial Intelligence Laboratory , and Software Engineering at the University of Parma. His work integrates algorithmic innovation with biological data analysis.

• Microwave Engineering
• Millimeter-Wave Circuits
• Numerical Methods
• +7 more

Luca Perregrini is a Full Professor at the University of Pavia, specifically within the Department of Industrial and Information Engineering. His academic career is deeply rooted in microwave and millimeter-wave engineering, where he has established himself as a leading expert in numerical methods for circuit design and electromagnetic analysis. As head of the Microwave Laboratory Ric.Stud., he directs significant research efforts in waveguide technologies and their applications. Professor Perregrini's research spans multiple cutting-edge domains in electromagnetic engineering. His primary focus involves numerical methods for designing microwave and millimeter-wave circuits, including waveguide circuits, frequency-selective surfaces, microwave integrated circuits, and antennas. He also investigates new materials and technologies for microwave applications, with particular interest in industrial and medical implementations. His work bridges theoretical electromagnetic analysis with practical engineering solutions, evidenced by his extensive publication record in top-tier journals and conference proceedings. The research demonstrates a clear trajectory toward increasingly sophisticated electromagnetic modeling techniques, with recent work emphasizing meshless methods, substrate integrated waveguide (SIW) technologies, and applications in medical imaging and space systems. Professor Perregrini has made substantial contributions to the field of electromagnetic simulation, particularly through the development and application of the MoM/BI-RME method for analyzing periodic structures and waveguide components. His work has significant practical applications in satellite communications, radar systems, and medical diagnostic technologies. The research group he leads at the University of Pavia maintains strong international collaborations, as evidenced by co-authorships with researchers from institutions across Europe and beyond.

Andrea CutilloView profile

Adjunct Professor

• Education Economics
• Economic Inequality
• Poverty
• +4 more

Andrea Cutillo is an Adjunct Professor at the European University of Rome , affiliated with the School of Economics . His primary research areas include Education Economics , Economic Inequality , and Poverty , with a focus on labor market dynamics and household consumption patterns. Current role: Professor of Tecniche di Marketing e Ricerche di Mercato (Marketing Techniques and Market Research) Institutional affiliation: ISTAT (National Institute of Statistics) as a Senior Researcher His work encompasses poverty measurement , data fusion methodologies , and gender wage gaps , often analyzing socioeconomic surveys and policy impacts. Recent publications highlight trends in poverty analysis (2020), data integration (2020), and labor economics (2017-2015). While no explicit awards are listed, his roles at ISTAT and the European University of Rome underscore his expertise in statistical and applied economic research.

Simone FaroView profile

Associate Professor

• Algorithmic solutions for text-processing
• Natural language processing
• Algorithmics in quantum domain
• +12 more

Simone Faro is an Associate Professor at the University of Catania , affiliated with the Department of Mathematics and Computer Science . He has held this position since 2015, after serving as a University Researcher from 2006 to 2015. Teaches Algorithms and Laboratory (Bachelor's L31) and Quantum Computer Programming (Master's LM18) Also teaches Computer Science (Bachelor's L20) and previously held Computational Linguistics (Master's LM49) at the Department of Humanities Research Focus : Algorithmic solutions for text-processing and natural language processing Combinatorial algorithms on graphs and networks Privacy-preserving text processing Bit-parallel automata simulations Quantum domain algorithm design Research Projects : Co-Principal Investigator for STORAGE (2020), University of Catania Responsible for Scientific Degrees Plan (PLS 2019/21) Component in Godscapes project (2020) and COMPACT project (2015) Principal Investigator for multiple string matching and secure text processing projects Editorial Roles : Guest Editor for Algorithms journal (MDPI) special issues Editor for String Processing and Combinatorial Algorithms (Springer Nature) Member of Le Matematiche editorial team Contact: faro@dmi.unict.it | simone.faro@unict.it

Luca TeseiView profile

Associate Professor

• Computational Structural Bioinformatics
• RNA Secondary Structure Analysis
• Topological Data Analysis
• +5 more

Luca Tesei is an Associate Professor in the Department of Computer Science at the University of Camerino's School of Science and Technology, Italy. His research focuses on computational structural bioinformatics, particularly RNA secondary structures and their functional implications. Current Projects: Principal Investigator of PRIN 2022 PNRR Project RNA2Fun (RNA Secondary Structures & Function in non-coding RNAs) Editorial Roles: Guest Editor for BMC Bioinformatics' RNA Prediction Collection; Editorial Board Member of BMC Bioinformatics Luca's work integrates topological data analysis with biological systems modeling, spanning RNA structure alignment, pseudoknot detection, and machine learning applications in biomedical fields. He has received the Italian National Scientific Qualification as Associate Professor in INF/01 (Computer Science) and ING-INF/05 (Information Systems Engineering) in 2017. Recent Trends: His publications emphasize RNA computational modeling (2016-2025), with growing integration of topological methods (persistent homology, entropy analysis) and machine learning techniques for structural comparisons and biomedical applications like seizure detection and stock market modeling. Scientific Awards: Italian National Scientific Qualification as Associate Professor (2017)

Anton DignösView profile

Associate Professor

• Temporal Databases
• Time Series Data
• Data Analytics
• +3 more

Anton Dignös is a tenured Associate Professor at the Free University of Bozen-Bolzano, Faculty of Engineering, where he leads the Database Systems Research Group. He holds a PhD from the University of Zurich (2014) and has been a faculty member since 2014. His research focuses on temporal databases, time series data, and data analytics, with contributions to indexing, query optimization, and benchmarking tools like TSM-Bench and SEER. Education : BSc and MSc (Computer Science) - Free University of Bozen-Bolzano (2008, 2010) PhD (Dr. sc. in Computer Science) - University of Zurich (2014) Research Interests : Dignös specializes in temporal database systems, time series management, and efficient query processing. He develops novel indexing techniques (e.g., RD-INDEX) and tools for benchmarking time series systems (SEER, TSM-Bench). His work addresses challenges like anomaly detection, sparse data summarization, and parallel join algorithms. Awards : Best Paper Award at SSDBM 2023 Best Paper Award at ADBIS 2022 ACM Computing Reviews Best of Computing (2017) Teaching & Advising : Teaches Data Management and Applied Informatics courses at both BSc and MSc levels. Advises ~25 students (PhD/MSc/BSc) on topics like temporal databases and machine learning applications. Active in thesis supervision and course development. Labs/Teams : Leads the Database Systems Research Group, collaborating on projects like the Period Index for temporal data and VISOR for data visualization tools.