Find Academic Supervisors

• Data Compression
• Indexing Data Structures
• Algorithms
• +7 more

Giovanni Manzini is a Professor of Computer Science at the University of Pisa's Department of Computer Science. He holds a PhD in Mathematics from the Scuola Normale Superiore di Pisa and has held visiting roles at MIT, Johns Hopkins University, and the University of Melbourne. Previously, he served as Assistant Professor at the University of Torino and Associate Professor at the University of Eastern Piedmont. His research focuses on designing algorithms and data structures for data compression, indexing massive datasets, and computational biology. Notable contributions include advancements in the Burrows-Wheeler Transform (BWT), grammar-based compression, and matrix operations optimization. He received the ACM Paris Kanellakis Theory and Practice Award (2022) and the 2023 Test-of-Time Award from the European Symposium on Algorithms. His recent work explores two-dimensional string repetitiveness, BWT-based indexing, and green computing techniques for matrix operations. Manzini has contributed to over 100 conference program committees since 2020, including DCC, ALENEX, and SPIRE. His teaching spans courses on algorithms, programming languages, and numerical analysis. Current courses include Algorithms and Data Structures for Data-intensive Applications and an undergraduate laboratory course on programming fundamentals. He leads software projects such as MMRepair (grammar-compressed matrix multiplication), BigBWT (BWT construction via prefix-free parsing), and EZcount (microRNA quantification tools). He also mentors the Scuola Ortogonale under the Elicsir Foundation, promoting STEM education.

• Experimental Economics
• Behavioral Economics
• Public Economics
• +3 more

Luca Panaccione is an Associate Professor at the Department of Economics and Law within the Faculty of Economics at Sapienza University of Rome. His work focuses on experimental and behavioral economics, with particular interest in public economics, financial literacy, and institutional design. He has conducted extensive research on topics such as coordination failures in banking systems, moral hazard in contractual relationships, and the impact of social influence on economic decisions. His research employs controlled laboratory experiments to explore mechanisms like fairness, cooperation dynamics, and behavioral spillovers in public good provision. Notable studies include analyzing how lockdowns affected fairness norms during the pandemic and investigating gender differences in social conformity scenarios. His experimental methods often combine theoretical models with empirical testing to uncover behavioral patterns in strategic interactions. Panaccione’s publications span from 2000 to 2024, reflecting a consistent focus on behavioral mechanisms in economic systems. While no specific awards are listed, his output demonstrates sustained academic engagement in core areas like experimental design and policy-relevant behavioral insights. No advising or grants information is provided in the source text.

Leonardo MarianiView profile

Professor

• Software Engineering
• Automated Testing
• GUI Testing
• +3 more

Leonardo Mariani is a Professor at the University of Milan Bicocca, specializing in software engineering with a focus on software testing and analysis. He actively leads and participates in European and national research projects such as the ERC-funded 'Learn' and 'AST' projects, as well as H2020 NGPaaS. His research spans automated testing, GUI testing, AI-based code assistants, and cloud system monitoring. He has contributed to improving software testability, runtime enforcer testing, and AI-driven development tools. His work emphasizes practical applications in mobile and edge computing environments. Recent publications highlight innovative approaches to test case generation, energy-efficient AI systems, and ethical/legal implications of AI-generated code. Mariani's scientific achievements include the ERC Consolidator Grant 2014 and Proof of Concept funding, alongside senior memberships in IEEE and ACM. As principal investigator in multiple projects, he bridges academic research with industry needs, focusing on Kubernetes testing, Android compatibility, and formal methods in software quality. His collaborative efforts involve advising students and coauthoring over 233 publications.

Zsuzsanna LiptákView profile

Associate Professor

• String Algorithms
• Combinatorics on Words
• Algorithmic Bioinformatics
• +18 more

Zsuzsanna Lipták is an Associate Professor in the Department of Computer Science at the University of Verona, Italy, where she has been a faculty member since November 2011. Her research is centered on string algorithms, combinatorics on words, and algorithmic bioinformatics, with a particular focus on the Burrows-Wheeler Transform (BWT) and its applications in data compression and biological sequence analysis. She is an active member of the Algorithmic Bioinformatics and Natural Computing Group and the Algorithms Group at the university. She leads research within the PRIN-funded project 'PINC – Pangenome Informatics: From Theory to Practice' and collaborates internationally with institutions in South Africa, Finland, Chile, and the USA. Her research interests include string indexing, suffix trees, suffix arrays, data compression, computational biology, and combinatorial properties of permutations and BWT. She has made significant contributions to the theory and application of BWT variants, matching statistics, and de Bruijn sequence construction. Her recent publications reflect a consistent focus on improving the efficiency and understanding of text indexing and compression methods, particularly in the context of genomic data. These works often involve both theoretical analysis and experimental validation, bridging the gap between pure theory and practical implementation. Lipták actively supervises PhD and master’s students, including Davide Cenzato, Sara Giuliani, Francesco Masillo, and Martina Lucà. She teaches advanced courses such as 'Fundamental Algorithms for Bioinformatics,' 'Computational Analysis of Genome-Scale Sequences,' and 'Advanced Data Structures for Textual Data.' She has also supervised numerous bachelor’s theses and student projects. She has secured research funding through national projects like PRIN and has collaborated on international initiatives, including a Marie Curie IEF fellowship during her postdoctoral work. She is deeply involved in the academic community, having served as PC chair for SPIRE 2024, PC co-chair for CPM 2023, and a member of the Steering Committee of SPIRE since 2024. She has served on the program committees of major conferences such as ESA, DLT, WABI, and IWOCA. She co-organizes the weekly 'Monday Meetings' seminar series for the Algorithms Group and has co-edited special issues and conference proceedings in journals like Theory of Computing Systems , Discrete Applied Mathematics , and European Journal of Combinatorics . She earned her Diplom in Mathematics from Freie Universität Berlin and her PhD in Computer Science from Bielefeld University, Germany, where her thesis addressed algorithmic problems in mass spectrometry. She has held research positions at ETH Zurich, Bielefeld University, and Salerno University, and has been a visiting researcher at the Rényi Institute (Hungary), University of the Witwatersrand, and SANBI (South Africa). She is the scientific coordinator for Erasmus+ exchanges with Bielefeld and Jena Universities.

• Computational Physics
• Molecular Dynamics
• Tribology
• +7 more

Mauro Ferrario is a Full Professor at the Department of Physical, Computer and Mathematical Sciences (former Physics campus) within the University of Modena and Reggio Emilia . His academic leadership is evident through dual roles in Computational Physics Laboratory (Physics degree program) and Physics teaching for Biological Sciences . Research Pillars: Non-Equilibrium Molecular Dynamics (NEMD/D-NEMD) Quantum-informed machine learning potentials Green lubricant additive development 2D material tribology (graphene, phosphorene) Multi-scale modeling from atomistic to continuum Surface passivation and chemical reactivity under stress Methodological Expertise: Ab initio/DFT simulations QM/MM hybrid approaches Constraint dynamics and thermostat algorithms High-throughput interface characterization Transient transport phenomena analysis The 2025-2024 publications reveal cutting-edge work on machine learning-enhanced simulations for green lubricants, NEMD melt-front modeling, and superlubricity mechanisms. His 2023-2022 studies on phosphorene oxidation, tribochemical constraints, and friction reduction through nanoscale patterning demonstrate sustained innovation across 15 recent articles . Teaching Impact: He develops computational physics curricula emphasizing Python programming, numerical algorithms, and interdisciplinary applications. His Computational Physics Laboratory course integrates DataCamp tools, while Physics for Biological Sciences bridges classical mechanics with life science applications through digital whiteboard instruction. Contact: Office MO-17-04-011 , Via Campi 213/A. Reception: Mondays 9:00-10:00 or by email appointment.

Michela QuadriniView profile

Assistant Professor

• Bioinformatics
• Computational Biology
• RNA Secondary Structures
• +3 more

Michela Quadrini is an Assistant Professor at the University of Camerino with expertise spanning Bioinformatics , Computational Biology , and Graph Neural Networks . Her academic work focuses on RNA structure analysis, human activity recognition, and formal methods for collective adaptive systems. Research Interests include: RNA pseudoknots comparison and classification Machine learning applications in biomedical signal processing Spatial logics for complex system modeling Protein-protein interaction site prediction Ontology-based frameworks for activity recognition Publications demonstrate methodological innovation across: RNA structure alignment and translation tools (TARNAS) Graph neural network programming languages (μG) Stress detection from wearable sensor data Formal verification of collective systems Immunoinformatics feature engineering Technical Expertise combines computational biology with advanced machine learning techniques, evidenced by contributions to: Topological data analysis for RNA structures Convolutional neural network architectures Semantic ontologies in mechatronic systems Integral equation numerical methods

Luciano GamberiniView profile

Professor

• Human-Computer Interaction
• Ergonomics
• IoT in Workplace Safety
• +5 more

Luciano Gamberini is a Full Professor at the University of Padova, Italy. His research focuses on Human-Computer Interaction (HCI), Ergonomics, and the integration of IoT and AR technologies in industrial and workplace environments. He leads projects like DANTE (digital transformation for SMEs) and DOMHO (smart co-housing for disabled individuals). His work emphasizes human-centered design, safety, and sustainable development in Industry 5.0 contexts. Research Interests: Human-Robot Collaboration Augmented Reality (AR) and Virtual Reality (VR) Applications IoT in Workplace Safety and Sustainability Age-related Technology Use in Industry 5.0 Employee Well-Being and Mental Health in Digital Workspaces Key Projects: CO-ADAPT: Cobots for Ageing Workers SAFE TALK: m-Health for Isolation Support SHIP: Inclusive Urban Park Design His recent articles explore topics such as VR-based teleoperations, trust in collaborative robots, and IoT security in smart workplaces. He actively contributes to the advancement of human-centric technologies through mixed-methods studies and interdisciplinary collaborations.

• Algorithmic Bioinformatics
• String Algorithms
• Theoretical Computer Science
• +3 more

Zsuzsanna Liptak is an Associate Professor in the Department of Computer Science at the University of Verona, Italy, specializing in algorithmic bioinformatics and string algorithms within the INFO-01/A Informatics academic sector. Her research focuses on: Algorithmic solutions for biological data String and sequence algorithms Mass spectrometry data interpretation Non-alignment based sequence comparison Applications to EST genomic sequences and nanopore technologies Dr. Liptak actively contributes to research projects including 'Securing Decentralized Finance and Remote Healthcare Systems - SHIELD' (starting October 2024) and 'Novel Methodologies and Tools for Next Generation Cyber Ranges - NOMEN' (starting May 2024), working at the intersection of theoretical computer science and practical bioinformatics applications. She serves on scientific committees for major international conferences: WABI (Workshop on Algorithms in Bioinformatics) CPM (Combinatorial Pattern Matching) SPIRE (String Processing and Information Retrieval) IWOCA (International Workshop on Combinatorial Algorithms) Her teaching portfolio spans multiple programs: Computational Analysis of Genome-Scale Sequences (Medical Bioinformatics Master's) Discrete Biological Models (Bioinformatics Bachelor's) Fundamental algorithms for Bioinformatics Advanced Data Structures for Textual Data (PhD program) She conducts research within the Algorithms and Algorithmic Bioinformatics research groups at the University of Verona, with connections to the INdAM Research Unit.

• Temporal Data Mining
• Biomedical Decision Support Systems
• Temporal Logics
• +5 more

Pietro Sala is an Associate Professor at the University of Verona , Department of Computer Science. His research intersects Temporal Data Mining , Biomedical Decision Support Systems , and Formal Verification of temporal logic specifications. Key Research Areas: Interval Temporal Logic and Model Checking Temporal BPMN for healthcare processes Data fusion in clinical environments Algorithm design for repetitive task automation Notable Projects: Dioxin impact analysis on cardiovascular development Open-source clinical data warehousing (DW-SAN) Real-time system verification frameworks Teaching: Lecturer for Biomedical Decision Support Systems (Master's) Instructor for Data Mining and Software Engineering courses The articles highlight his work in temporal logic verification (2025), clinical process modeling (2024-2025), and data integration for NLP pipelines (2023). His publications span theoretical computer science conferences (LICS, ICALP) and healthcare informatics journals (ICHI, CBM).

• Hardware Design for Network Devices
• Fault Tolerance
• Error Correction Codes
• +3 more

Salvatore Pontarelli is a Researcher at CNIT (Italian National Inter-University Consortium for Telecommunications), affiliated with the University of Rome Tor Vergata. He holds a Master's in Electronic Engineering from the University of Bologna (2000) and a PhD in Microelectronics and Telecommunications from the University of Rome Tor Vergata (2003). His work focuses on hardware design for network devices, fault tolerance, error correction codes, and high-speed packet processing. He contributed to EU-funded projects and received a CISCO Research Award (2011) for work on Bloom filters and Ternary CAM. Research interests include hash-based structures (e.g., Bloom filters, hash tables), stateful programmable data planes, and FPGA-based network intrusion detection systems. He led the Defect and Fault Tolerance Group (DFTGroup) under Prof. Adelio Salsano and has extensive experience in collaborative projects with academic and industry partners. Publications highlight innovations in flow monitoring, data plane optimization, and efficient memory management. His work often bridges theoretical algorithms (e.g., cuckoo hashing) with practical hardware implementations, emphasizing real-world applications in networking and telecommunications.

Claudio Sacerdoti CoenView profile

Associate Professor

• Mathematical Knowledge Management
• Interactive Theorem Proving
• Logical Frameworks
• +14 more

Claudio Sacerdoti Coen is an Associate Professor in Computer Science at the Department of Computer Science and Engineering , University of Bologna. His research focuses on Mathematical Knowledge Management , Interactive Theorem Proving , and their applications to functional programming languages and markup languages like XML and MathML. He has led the DAMA project for didactic applications of theorem provers. Employment: Associate Professor (2017–present), previously Lecturer (2007–2017) Education: Ph.D. in Computer Science (University of Bologna, 2004), Master’s in Computer Science (2000) Research Interests include: Integration of XML-based Mathematical Knowledge Management with Interactive Theorem Provers (e.g., Coq, Matita) Reduction strategies in the Calculus of (Co)Inductive Constructions Formal verification of algorithms and compilers Constructive analysis and formal topology User interface design for proof assistants Publications over the last decade highlight advancements in: Efficient substitution mechanisms for lambda calculi Formalization of mathematical theorems (e.g., Lebesgue’s Dominated Convergence Theorem) Development of proof assistant frameworks (Matita kernel, ELPI interpreter) Mathematical document structuring and search engine design

• Biometrics
• Fingerprint Recognition
• Security Systems
• +3 more

Raffaele Cappelli is an Associate Professor at the Department of Computer Science and Engineering, University of Bologna. His research focuses on fingerprint biometrics, emphasizing anti-spoofing, segmentation, and synthetic data generation. He contributes to the Fingerprint Verification Competition (FVC) and has pioneered tools like SFinGe for synthetic fingerprint databases. His work addresses security vulnerabilities in biometric systems and forensic applications. Education and affiliations include roles at the University of Bologna, with expertise in computer science and engineering. His research integrates machine learning, pattern recognition, and hardware acceleration to enhance biometric system performance and reliability. Key areas of study include presentation attack detection, fingerprint orientation estimation, and large-scale database management. He has authored over 70 publications, with notable contributions to forensic science and secure authentication protocols.

• Bayesian inference
• Biostatistics
• Clinical trials
• +7 more

Mauro Gasparini is a Full Professor at the Department of Mathematical Sciences (DISMA) of Polytechnic University of Turin. He serves as Director of DISMA since 2019, Member of Academic Senate, and co-leader in the SmartData@PoliTO Big Data Laboratory. His career spans academia and industry, including roles at Purdue University (Assistant Professor 1992-1996) and Novartis (Senior Statistician 1996-1998). He has been Editor of Biometrical Journal (2012-2015) and maintains referee activities across international journals. PhD from University of Michigan (1992, Dirichlet process applications) Academic leadership: Department Director, Editorial boards, ISTAT Advisor Research spans Bayesian methodology with biomedical applications Maintains collaborations with Novartis, Chiesi, and research centers His research interests focus on Bayesian inference , Biostatistics , and Clinical trials methodology, particularly addressing issues in pharmaceutical development, genomic data analysis, and medical decision-making. Recent work includes vaccine efficacy modeling, optimal imaging timing for cancer diagnostics, and adaptive trial designs. Key publication trends show interdisciplinary applications in Statistics in Medicine , Biometrics , and Statistical Methods in Medical Research , with emphasis on biomedical data science, Bayesian adaptive methods, and clinical decision support systems. Scientific contributions include: Editor, Biometrical Journal (2012-2015) Advisor, Italian National Institute of Statistics (2020-2024) Leadership in multiple research projects (NODES, SORGENTE, IDEAS) As PhD advisor, he supervises students in: Shaoshi Tang (Clinical trial modeling) Saeed Sani (Biomedical data analysis) Marco Ratta (Genomic statistics) Luca Rondano (Bayesian methods) Vittorio Zampinetti (Tumor DNA sequencing) Fulvio Di Stefano (Evidence-based decision statistical methods) He leads research projects in pharmaceutical statistics, genomic surveillance, and spatial risk assessment frameworks, with recent emphasis on SARS-CoV-2 analysis and cancer progression modeling.

• Finite Element Analysis
• Biomechanics
• Mechanical Design
• +6 more

Bartolomeo Trentadue is an Associate Professor in the Department of Mechanics, Mathematics and Management at the Polytechnic University of Bari, Italy. His research focuses on mechanical design and machine construction (ING-IND/14), with specialization in finite element analysis (FEA) applied to biomechanical systems and medical implants. He maintains active collaborations through institutional research platforms like IRIS and can be contacted via email or phone at his departmental office. Research Interests: Professor Trentadue's work spans computational biomechanics, implant design optimization, and material science. Primary areas include: Finite element modeling of orthopedic/dental prostheses Stress-shielding reduction in joint replacements Biomechanical interactions in bone-implant interfaces Material behavior of biomaterials (PEEK, titanium alloys, ceramics) Clinical translation of FEA for surgical planning Publication Trends: His 15 most recent articles (2023-2025) demonstrate consistent focus on FEA applications in medical devices. Key themes include: optimization of dental/orthopedic implant geometries, material selection for stress distribution, biomechanical validation of surgical techniques, and development of patient-specific solutions using 3D printing. Over 80% involve direct clinical applications in prosthodontics, arthroplasty, and spinal reconstruction. Awards & Recognition: No scientific awards or honors are documented in available sources. Academic Activities: While specific student advising or grant details aren't provided, his publication record indicates leadership in collaborative research. Departmental responsibilities include contributions to institutional research infrastructure. Laboratory Affiliations: Based in the Mechanics division at Polytechnic University of Bari, his work likely utilizes computational modeling facilities and biomechanics laboratories, though specific lab names are unspecified.

Jlenia ToppiView profile

Associate Professor

• Biomedical Signal Processing
• EEG Signal Processing
• Brain Connectivity
• +6 more

Jlenia Toppi is an Associate Professor at the Department of Computer, Control and Management Engineering, Sapienza University of Rome. With a background in Biomedical Engineering (B.Sc. and M.Sc. summa cum laude from University of Rome, Ph.D. from University of Bologna), she leads research at the Neuroelectrical Imaging and BCI Laboratory, IRCCS Fondazione Santa Lucia, focusing on EEG signal processing, brain connectivity modeling, and graph theory applications in cognitive and clinical neuroscience. Education: B.Sc. Clinical Engineering (2006), M.Sc. Biomedical Engineering (2009), Ph.D. Biomedical Engineering (2013) Awards: IEEE EMBC Student Paper Finalist (2012), Young Bioingegneria Award (2012), IEEE EMBS Best Poster (2011) Her research develops advanced EEG methodologies for brain mapping and dynamic connectivity estimation , applied to disorders of consciousness, stroke rehabilitation, and social neuroscience. She pioneered hyperscanning EEG for interpersonal brain-to-brain analysis and contributed to BCI systems like RECOM and The Promotoer. Recent publications highlight her work on hybrid BCI rehabilitation , muscle synergy extraction , and multi-modal assessment of therapeutic interventions . She serves as editor for Computation and Mathematical Methods in Medicine and collaborates with international projects including Horizon 2020.