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Giuseppe ValloneView profile

Professor

• Quantum optics
• quantum communication
• quantum information
• +3 more

Giuseppe Vallone is a Full Professor at the Department of Information Engineering, University of Padova, where he has served since February 2024. Previously, he was an Associate Professor (May 2019-January 2024) and Assistant Professor (May 2011-April 2019) at the same institution. His career spans quantum optics, quantum communication, and quantum information, with a focus on practical implementations of quantum technologies. Born in 1979 in Vico Equense (Naples), Vallone earned his Master's degree in Physics from the University of Torino in 2002 with top honors ("110/110 lode e menzione"). He completed his Ph.D. in Theoretical Physics at the University of Torino in 2006, with a thesis on String Theory titled "Nonperturbative aspects of gauge theory from strings" under the supervision of Professor A. Lerda. During his Ph.D., he was awarded a Marie Curie Fellowship, which allowed him to conduct research at the Nordic Institute for Theoretical Physics (NORDITA) in Copenhagen for 11 months. Vallone's research focuses on quantum optics, quantum communication and information, and quantum key distribution. His work has advanced the experimental implementation of Quantum Random Number Generators and Quantum Key Distribution protocols, particularly for earth-satellite communication. He leads the Quantum Communications group (also known as QuantumFuture) at the University of Padova, which has developed expertise in practical quantum communication systems. His team has made significant contributions to time-bin encoding, device-independent protocols, and space-based quantum communication. His recent publications reveal a strong trend toward practical quantum communication systems, with emphasis on satellite-based quantum networks, integrated photonics for quantum applications, and field demonstrations of quantum key distribution. His work bridges fundamental quantum physics with real-world applications, particularly in secure communication. Recent projects include high-speed quantum random number generators, intermodal quantum key distribution systems that work across different communication channels, and experiments combining quantum mechanics with general relativity. 2008: "Vito Volterra prize for young master student graduated in Physics after May 2001" from Societa Italiana di Fisica (S.I.F.) 2003-04: "Marie Curie training site" fellowship at NORDITA institute (Copenhagen) 2003: "OPTIME 2002/03 prize" from Industrial Association of Torino 2003: "Best master thesis of each course (a.y. 2001/02)" from University of Torino Vallone has secured significant research funding as principal investigator, coordinating multiple European projects including QUDICE (Horizon-EU, 2023-2024), QUANGO (EU-H2020, 2021-2023), and QUASAR (CARIPARO, 2020-2023). He has also served as principal investigator for projects funded by ESA, EU-QUANTERA, and ASI. His research group, QuantumFuture, has conducted field trials of quantum key distribution in Padua's metropolitan area and has developed integrated photonic solutions for quantum communication. Current work focuses on satellite quantum communication, quantum-secured time transfer, and the intersection of quantum mechanics with general relativity. The QuantumFuture research group at Padova, led by Vallone, specializes in practical quantum communication systems. They have developed expertise in experimental implementations of Quantum Random Number Generators and Quantum Key Distribution protocols, with particular emphasis on earth-satellite communication. The group has successfully demonstrated quantum communication over classical network infrastructure in Padua and has made significant progress on integrated photonic solutions for quantum technologies. Their research spans from fundamental quantum physics to deployable quantum communication systems.

• Automata theory
• Formal language theory
• Combinatorics on words
• +2 more

Giuseppa Castiglione is a Researcher (INFO-01/A) in the Department of Mathematics and Computer Science at the University of Palermo's School of Basic and Applied Sciences. She maintains regular office hours on Tuesdays and Thursdays from 2:00 PM to 3:00 PM in Room 209, second floor, and teaches Theoretical Computer Science for both Computer Science and Mathematics degree programs. Her primary research interests span several interconnected areas within theoretical computer science and discrete mathematics. These include automata theory, formal language theory, combinatorics on words, enumerative combinatorics, and discrete two-dimensional structures. Her work demonstrates a consistent focus on the mathematical foundations of computer science, particularly in the analysis of string algorithms, word combinatorics, and discrete geometric structures. Analysis of her publication record from 2017-2025 reveals a strong concentration on combinatorial aspects of words and automata, with recent work expanding into isometric words, Fibonacci cubes, and Wheeler automata. Her research shows a progression from foundational work on polyominoes and automata minimization toward more complex combinatorial structures and their applications in string processing. Castiglione has participated in numerous significant research projects including the Prin 2010-11 project on mathematical aspects of automata and formal languages, the PO FESR 2007/2013 Neverlost project, PON Research and Competitiveness 2007/2013 SMART HEALTH initiative, and GNCS 2016 on combinatorial methods for handling large data sets. These projects demonstrate her ability to secure competitive research funding across multiple domains. She collaborates with researchers including Marinella Sciortino, Gabriele Fici, Chiara Epifanio, Sabrina Mantaci, and Antonio Restivio, forming a productive research network focused on theoretical computer science and combinatorics. Her extensive publication record in high-quality venues demonstrates her sustained contribution to the field over more than two decades.

Flavio De PaoliView profile

Associate Professor

• Semantic Web Technologies
• Data Enrichment
• Services-Oriented Computing
• +3 more

Flavio De Paoli is an Associate Professor affiliated with the Insid&s LAB. His research focuses on semantic web technologies, data enrichment, and interactive tools for data management. Key projects include the enrichMyData initiative and the development of frameworks like SemT and Protobject . His work spans geospatial data analysis, services-oriented computing, and scalable data solutions. Notable contributions include tools for semantic table interpretation (e.g., MantisTable ), API-based data enrichment, and event-driven analytics. He has also contributed to cloud computing frameworks and semantic wiki integration for knowledge management. His research emphasizes human-in-the-loop systems, automated data processing, and tool development for both academic and industrial applications. Projects like EW-shopp and BEEO demonstrate his focus on applying semantic technologies to real-world challenges in marketing, urban planning, and smart systems.

• Theoretical Physics
• Mathematical Physics
• Quantum Field Theory
• +3 more

Simone Giacomelli serves as a Research Fellow at the Department of Physics, University of Milano-Bicocca, specializing in Theoretical Physics (FIS/02) with emphasis on mathematical models and methods in high energy theory. His research focuses on fundamental aspects of quantum field theory and string theory, particularly: Duality transformations in supersymmetric gauge theories Mathematical structures of quantum gravity Discrete global symmetries and compactification mechanisms Non-perturbative analysis of 'bad' quantum field theories Recent work demonstrates significant contributions to dualization algorithms and symmetry analysis, with three 2024 publications in the Journal of High Energy Physics establishing new frameworks for probing non-standard quantum field theories and symmetry implementations. These studies reveal deep connections between duality, compactification, and symmetry in high-energy regimes. Contact is maintained through university channels with primary academic correspondence via institutional email.

Roberto GrossiView profile

Professor

• Algorithms and Data Structures
• Dynamic and External Memory Algorithms
• Algorithm Engineering
• +4 more

Roberto Grossi is a Professor of Algorithms and Data Structures at the University of Pisa's Dipartimento di Informatica. He is actively involved in editorial roles for journals like Theory of Computing Systems and RAIRO-Theoretical Informatics, and has served on program committees for conferences such as SWAT, IWOCA, ESA, FOCS, and SPIRE. His research focuses on algorithms, data structures, graph theory, and bioinformatics, with contributions to string processing, compressed data structures, and algorithm engineering. He advises Ph.D. students and collaborates on projects involving large-scale networks and community detection. Grossi has authored numerous publications, including works on clique enumeration, graphlet algorithms, and phylogenetic reconstruction. His teaching includes courses on Algorithm Design and Data Structures, and he maintains an active presence in academic networks through his research and editorial activities. Education: Not explicitly stated, but inferred from his role as a professor at a top Italian university. Research Interests: Dynamic algorithms, external memory methods, experimental algorithmics, pattern matching in strings and graphs. Grants/Awards: While no specific prizes are listed, his extensive publication record and editorial roles reflect sustained recognition in the field. Lab/Teams: Leads research groups focused on algorithmic foundations and applications, collaborating with international teams on projects like Zuckerli (compressed graph representations) and motif trie indexing. His work bridges theoretical computer science with practical applications in bioinformatics and network analysis.

• 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.

Giovanna RosoneView profile

Associate Professor

• Sequence Analysis
• Combinatorics on Words
• Bioinformatics
• +2 more

Giovanna Rosone is an Associate Professor at the University of Pisa (Università di Pisa) within the Department of Computer Science (Dipartimento di Informatica) . Her research focuses on Sequence Analysis , Combinatorics on Words , Bioinformatics , and Algorithms and Data Structures , with a strong emphasis on applications leveraging the Burrows-Wheeler Transform . She leads the CMACBioSeq project funded by the Italian MIUR-SIR grant, developing combinatorial methods for biological sequence analysis and compression. Her work includes tools like BCR_LCP_GSA and ebwt2InDel for efficient genome analysis, SNPs/indel detection, and alignment-free variation discovery. These tools are used in metagenomics, rare-variant identification, and genotyping.

France GheeraertView profile

Associate Professor

• Combinatorics on Words
• Symbolic Dynamics
• Numeration Systems
• +3 more

France Gheeraert is an Associate Professor in Mathematics at the University of Picardie Jules Verne, France, since September 2024. They are affiliated with the SymPA research team at the Laboratoire Amiénois de Mathématique Fondamentale et Appliquée (LAMFA) and organize the dyna-proba seminar. Previously, they were a Postdoctoral Researcher at Radboud University (Netherlands) and an FNRS Research Fellow at the University of Liege (Belgium), focusing on combinatorics on words and symbolic dynamics. Education Bachelor and Master in Mathematics with Computer Science focus from the University of Liege Research Interests Combinatorics on Words (core work on dendric words, generalizing Sturmian words) String Attractors in data compression Symbolic Dynamics and numeration systems Applications of morphisms in word structures Connections to group theory and algorithmic complexity Recent Publications 2024: String attractor-based complexities for infinite words 2024: String attractors in bi-infinite sequences 2023-2022: Studies on dendric words, S-adic systems, and morphic fixed points Scientific Awards FNRS Research Fellow (Belgium, 2020-2024) Labs & Teams SymPA team, LAMFA (University of Picardie) Discrete Mathematics team, University of Liege (2020-2024)

Francesco CauteruccioView profile

Assistant Professor

• Social and Complex Network Analysis
• Data Mining and Data Science
• Internet of Things (IoT)
• +3 more

Francesco Cauteruccio is a Tenure-Track Assistant Professor at the Department of Information Engineering, Electrical Engineering and Applied Mathematics (DIEM) at the University of Salerno, Italy. He is affiliated with the CORE and S 3 labs, focusing on interdisciplinary research at the intersection of social networks, IoT, and hybrid AI models. Ph.D. in Mathematics and Computer Science, University of Calabria (thesis: "Generalizing Identity-Based String Similarity Metrics: Theory and Applications") Italian National Scientific Qualification (ASN) for Associate Professor in Computer Science and Computer Engineering Visiting researcher at University of Klagenfurt (AI & Cybersecurity) and University of Lyon 1 (CERMEP/CREATIS) His research spans: Social & Complex Networks: Modeling cross-blockchain ecosystems, Reddit community dynamics, and sentiment propagation IoT & Hybrid Intelligence: Scope formalization, anomaly detection in MIoT networks, and air quality prediction systems Logic Programming: Integrating Answer Set Programming with machine learning for medical informatics and pattern mining Algorithm Design: Multi-Parameterized Edit Distance (MPED) for bioinformatics and network analysis Recent publications address network theory applications, hybrid reasoning frameworks, and high-utility pattern mining with formal constraint specification. He serves as guest editor for journals like Big Data and Cognitive Computing and Frontiers in Medical Engineering , and organizes international workshops on hybrid intelligence (HYDRA, VIPERC). Academic distinctions: Italian National Scientific Qualification for Associate Professor positions (2024) Guest Editor for 12+ special issues in data science and IoT journals Program/General Chair for 8 international workshops (2022-2024) His teaching portfolio includes courses on algorithms, distributed systems, and data analytics at University of Salerno, Polytechnic University of Marche, and University of Calabria.

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.

Giorgio Stefano GneccoView profile

Professor

• Optimization
• Machine Learning
• Game Theory
• +6 more

Giorgio Stefano Gnecco is a Full Professor in Mathematical Methods of Economics and of Actuarial and Financial Sciences at IMT School for Advanced Studies Lucca, where he works within the Analysis of compleX Economic Systems (AXES) research unit. His academic career spans multiple disciplines including optimization, machine learning, game theory, and their applications in economics, finance, and engineering. His research interests focus on optimization applied to actuarial sciences, economics, finance, and engineering; game theory; statistics; machine learning theory and applications; causal inference for economic policy evaluation; and environmental economics. His work demonstrates interdisciplinary connections between mathematical theory and practical applications across diverse fields, with particular emphasis on developing computational methods for complex economic systems. His publication record shows consistent output across multiple domains, with recent work spanning machine learning algorithms, image processing techniques, economic modeling, and applications in music performance analysis. The breadth of his research indicates strong methodological foundations in mathematical optimization and statistical learning, applied to problems ranging from flood hazard assessment to Parkinson's disease classification. Among his notable achievements are five Italian National Scientific Qualifications for professorial positions in various fields, demonstrating his recognized expertise across multiple academic disciplines. He serves as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems, Action Editor for Neural Networks, and Associate Editor for Neurocomputing. Professor Gnecco leads numerous research projects including the "PRIN PNRR 2022" project "MOTUS - Automated Analysis and Prediction of Human Movement Qualities," the "INdAM-GNAMPA 2023" project on machine learning methods for Shapley Value estimation, and the "ROBOFARM" project on edge computing for precision agriculture. He has coordinated multiple international research collaborations between Italy and France through the Galileo program. His research unit (AXES) focuses on complex economic systems analysis, with applications spanning environmental economics, financial systems, and human movement analysis. The collaborative nature of his work is evident through his extensive network of domestic and international collaborators across multiple universities and research institutions.

Adam Teodor PolakView profile

Assistant Professor

• Algorithms
• Fine-Grained Complexity
• Learning-Augmented Algorithms
• +3 more

Adam Teodor Polak serves as an Assistant Professor in the Department of Computing Sciences at Bocconi University, where his research centers on theoretical algorithms with dual emphases on fine-grained complexity and learning-augmented algorithms. His work investigates fundamental questions about computational hardness while developing prediction-enhanced algorithms that maintain worst-case guarantees. Polak earned his PhD from Jagiellonian University in 2019 under Paweł Idziak, including a research visit at MIT with Virginia Vassilevska Williams. He subsequently held postdoctoral positions at the Max Planck Institute for Informatics and EPFL before joining Bocconi. His research program addresses why computational problems resist efficient solutions and how imperfect predictions can robustly improve algorithmic performance. This manifests in two interconnected streams: establishing conditional lower bounds for problems like 3SUM and Orthogonal Vectors, and designing learning-augmented frameworks for dynamic graph problems, caching, and optimization that blend theoretical rigor with practical machine learning insights. Recent publications reveal accelerating momentum in algorithms with predictions, with over half of his 2023-2025 output appearing in top ML venues (ICML, NeurIPS, ICLR) alongside traditional theory conferences (STOC, SODA). This cross-pollination demonstrates how worst-case theoretical guarantees can coexist with data-driven performance gains across graph algorithms, scheduling, and combinatorial optimization. Scientific recognition includes: Best Paper Award at ESA 2024 for knapsack algorithm breakthroughs Bronze Medal at ACM ICPC World Finals (2011) 2nd Place in PACE 2018 Challenge for Steiner tree algorithms Polak actively shapes the field through program committee service (ESA, ICALP, SOSA) and community building, notably co-organizing the 2022 Workshop on Algorithms with Predictions (ALPS) and decade-long high-school algorithmics workshops. His industry collaborations with Teroplan and Google demonstrate real-world impact in route planning and distributed systems. Current teaching includes graduate Algorithms courses at Bocconi, while his experimental work on GPU-accelerated graph algorithms and medical computer vision continues to bridge theoretical insights with practical implementation challenges.

• Theoretical Physics
• Condensed Matter Physics
• Statistical Mechanics
• +3 more

Nicodemo Magnoli is an Associate Professor at the University of Genoa's Department of Theoretical Physics of Fundamental Interactions. His research focuses on statistical field theory, gauge theories, superconductivity, and interdisciplinary topics like turbulent odor plumes. He teaches courses in non-equilibrium statistical physics and thermodynamics at both bachelor's and master's levels. His work bridges theoretical physics with applications in materials science and condensed matter systems. Recent publications explore confining strings in gauge theories, superconductivity destruction mechanisms in thin films, and hydrodynamic descriptions of cuprate strange metals. He collaborates with institutions like INFN (National Institute for Nuclear Physics). No scientific awards are explicitly listed, but his active research is indicated by multiple recent publications. He advises thesis proposals on dynamic critical phenomena and superconductors in strong electric fields. Teaching responsibilities include Fisica Statistica dei Sistemi Fuori Equilibrio (Statistical Physics of Non-Equilibrium Systems) and Termodinamica (Thermodynamics), with course details available via provided university links. His research page includes a complete publication list via IRIS.

• Bioinformatics
• Algorithmic Biology
• Natural Computing
• +4 more

Simone Avesani serves as a Researcher in the Department of Computer Science at the University of Verona's School of Science and Engineering. His academic sector is INFO-01/A - Informatics, where he contributes to the university's research infrastructure through specialized computational approaches to biological data. His research spans Bioinformatics, Algorithmic Biology, and Natural Computing with focus on developing graph and string algorithms for systems biology, advanced data structures for sequence analysis, distance measures for biological sequences, and machine learning applications in biomedical contexts. Avesani is actively involved in the Algorithmic Bioinformatics and Natural Computing research group where he applies theoretical methods to model biological information processes, as well as the InfOmics laboratory which specializes in efficient biomedical data analysis. Currently leading the project 'Defining Clinical and Molecular Phenotypes of Multi-Drug Resistance in difficult to treat Rheumatoid Arthritis - MDR-RA' (started January 1, 2025), his work develops novel methods for mining biological networks, integrating heterogeneous data, analyzing omics, reconstructing pangenomes, and patient classification using interdisciplinary approaches from machine learning, data science, mathematics, and graph theory. He is affiliated with the INFOMICS laboratory among several specialized research facilities including IRIS, ISLa, and STARS laboratories within the department.

• 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.