Find Academic Supervisors

Raffaele Giancarlo is a Full Professor in the Department of Mathematics and Computer Science at the University of Palermo. His office hours are held on Mondays and Thursdays from 2:30 PM to 5:30 PM in Room 106 of the DMI (Dipartimento di Matematica e Informatica) or via TEAMS. He can be reached at raffaele.giancarlo@unipa.it. Research Focus: Computational Biology, Bioinformatics, Data Compression, and Algorithm Design. Key Contributions: Development of agile platforms for genomic data analysis, optimization of Bloom filters, and innovative text indexing techniques.

• Computational Biology
• Bioinformatics
• Data Compression
• +7 more

Rodolfo Metulini is a Researcher (RTD-B) in Statistics for Experimental and Technological Research (SECS-S/02) at the Department of Economics, University of Bergamo. He serves as Principal Investigator for the PRIN/PNRR project 'SIGNUM: Study of mobile phone signals for evaluating mobility-environment interconnections in Lombardy'. His career includes postdoctoral positions at the University of Brescia, Scuola Superiore Sant'Anna Pisa, and IMT Lucca. PhD in Statistical Methodology for Scientific Research (2013), University of Bologna Former Researcher at University of Salerno (RTD-A) Metulini's research spans three primary domains: travel flow analysis using gravity models and spatial interaction approaches for international trade studies; sports analytics focusing on player movement dynamics and marginal utility in football/basketball; and urban mobility modeling through mobile phone data with complex seasonality time series models. His methodological innovations combine matrix completion techniques with functional data clustering for environmental-socioeconomic applications. Recent research trends demonstrate cross-sectoral expertise in applying statistical learning to diverse domains: 1) environmental risk assessment using mobile network data for flood exposure forecasting; 2) urban policy analysis through counterfactual modeling of traffic restrictions; and 3) economic modeling for CO2 emissions prediction. His technical approach integrates dynamic harmonic regression with VARX models for mobility forecasting. As thesis advisor for Computer/Mechanical Engineering students, Metulini promotes data-driven approaches in mobility and sports domains. His publications in journals like Annals of Operations Research and Optimization Letters showcase interdisciplinary methodology combining statistical theory with practical applications in environmental risk management and sports performance analysis.

• Statistics for Experimental and Technological Research
• Urban Mobility Analysis
• Sports Analytics
• +3 more

Lorenzo Colace is an Associate Professor in the Department of Engineering at the University of Rome "Roma Tre", where he has been a faculty member since 2012. He received his MS in Electronic Engineering from "La Sapienza" in 1992 and his PhD from Roma Tre in 1997. He began as a researcher in 2005 and advanced to Associate Professor in December 2012. He teaches core courses including Electronics I and Photovoltaic Devices and Systems, and has also taught Solid State Electronics, Precision Analog Electronics, and Optoelectronics. His research spans optoelectronic devices compatible with silicon technology, with applications in optical communications, sensing, imaging, and photovoltaics. He specializes in Germanium-on-Silicon photodetectors, PbS colloidal quantum dots, CIGS solar cells, and near-infrared imaging systems. His work integrates materials synthesis, device fabrication, and characterization, aiming at high-performance, CMOS-compatible solutions. The recent publications highlight a strong trend in near-infrared optoelectronics, particularly using Ge/Si and colloidal quantum dots for photodetection in safety, security, and energy applications. There is also a significant focus on photovoltaic device modeling and fire detection systems, reflecting interdisciplinary innovation bridging materials science, electronics, and environmental monitoring. Institute of Electrical and Electronics Engineers (IEEE) European Technology Platform for Photonics (Photonics21) Materials Research Society (MRS) Istituto Nazionale di Fisica Nucleare (INFN) Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT) Prof. Colace has supervised numerous research projects and established key collaborations with institutions such as MIT, the University of Central Florida, CNR-IMM, CNR-IMEM, and companies like Agilent Technologies and Pirelli Labs. He serves on scientific and organizing committees for major conferences and acts as a referee for several international journals. He has authored over 200 publications, including 81 journal articles, 4 international patents, 10 book chapters, and numerous conference papers, with an h-index of 21 and over 1,500 citations (Scopus, 2017). His lab focuses on integrated optoelectronic systems, particularly for sensing and energy applications, and he leads a research team advancing silicon-compatible infrared technologies.

• Optoelectronics
• Silicon Photonics
• Near-Infrared Photodetectors
• +7 more

Giuseppe Migali is a Full Professor of Economics at the Department of Law, Economics and Sociology, Magna Graecia University, Catanzaro, Italy. He has held academic positions including Associate Professor (2015–2021) and Assistant Professor (2008–2015). He is also a Visiting Professor at Lancaster University, UK (since 2011). His research focuses on Applied Public Economics, Economics of Education, Taxation, and Microeconometrics. He has organized multiple International Workshops on Applied Economics of Education and holds editorial roles in journals like Education Economics . Education: - Ph.D. in Economics, University of Warwick (2008) - PhD in Public Finance, University of Pavia (2005) - MSc in Economics, University College London (2003) - Honors Degree in Economics, Bocconi University (2000) Research Interests: His work spans quasi-experimental methodologies, program evaluation, and policy analysis in education and public finance. Recent studies include the impact of the Great Recession on sports attendance, intergenerational health transmission in China, and youth unemployment patterns across Europe. Grants & Awards: - Principal Investigator for projects like ‘School Resources and Dropout Behavior in Italy’ (€101,000, 2011–2013) - ESRC Grant (GBP 172,995, 2009–2011) - Gold medal for ‘Best Graduates’ at Bocconi University Roles & Activities: - President of the Postgraduate Degree in Public Administration and Society (since 2021) - Co-founder and organizer of the International Workshop on Applied Economics of Education (since 2010) - Member of scientific committees for PhD programs in Law and Economics, and Economics Labs/Teams: Active in the Health Economics at Lancaster (HEAL) group and external affiliate of HEDG, University of York.

• Applied Public Economics
• Economics of Education
• Taxation
• +3 more

Federico Perali is a Full Professor of Economic Policy at the University of Verona's Department of Economic Sciences. He holds a Ph.D. from the University of Wisconsin - USA and has served in numerous leadership roles including Director of the Department of Economic Sciences (2006-2012) and Director of the Doctoral School in Legal and Economic Sciences (2014-2015). He founded the Economics Living Lab, an accredited spin-off of the University of Verona, in 2016. His research focuses on household economics, welfare analysis, and poverty measurement. Key areas include intrahousehold resource allocation, child and disability cost estimation, family policy evaluation, and regional economic disparities. His work employs advanced econometric techniques, particularly collective demand models, to analyze family decision-making processes and welfare outcomes. Perali's research bridges theoretical economic modeling with practical policy applications, with particular attention to Italian and international contexts. Perali's recent publications demonstrate a consistent focus on intrahousehold dynamics, welfare measurement, and regional economic analysis. His work spans theoretical contributions to social welfare functions, empirical studies on intrahousehold allocation, and applied regional economic modeling. The interdisciplinary nature of his research connects economics with sociology, public health, and development studies, particularly in analyzing how family structures, cultural factors, and economic policies affect well-being outcomes. Perali has served as a consultant for major international organizations including the World Bank, European Investment Bank, FAO, OECD, Pontifical Council for Justice and Peace, UNICEF, and Telecom Italia. He is a member of the scientific committee of several research centers including CHILD (Center for Household, Income, Labor and Demographics), ICID (International Center for Economic Development), and the 'Center for Studies and Research on the Family' at the Catholic University of Milan. His teaching responsibilities include Economic Policy, Development Economics, and Negotiation Theory at both master's and doctoral levels. He has coordinated the International Ph.D. Program in Economics and Finance and continues to be actively involved in numerous academic committees and research projects focused on economic development, family policy, and regional economics.

• Household Behavior and Family Economics
• Welfare and Poverty
• Demographic Economics
• +7 more

Marcello Pelillo is a **Full Professor** at the Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice. His research focuses on machine learning, pattern recognition, computer vision, and adversarial machine learning. He has contributed significantly to graph-based methods, clustering algorithms, and security in machine learning systems. Pelillo is affiliated with the European Center for Living Technology (ECLT) and the Research Institute for Complexity Communications . His work spans theoretical advancements in graph theory and practical applications in cultural heritage digitization, climate science (e.g., ice core analysis), and AI security. Recent projects include entropy-guided graph clustering, backdoor poisoning defenses, and benchmark datasets for puzzle-solving tasks. Publications emphasize interdisciplinary applications, such as AI-assisted historical document digitization and energy-latency attacks in networks. He has supervised multiple collaborative projects involving institutions like the Research Institute for Complexity and the European Interuniversity Research Center.

• Computer Science
• Machine Learning
• Pattern Recognition
• +7 more

Andrea Torsello is a Full Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. His research focuses on Computer Vision, Machine Learning, and Artificial Intelligence with applications in quantum computation, graph theory, and 3D modeling. He is actively involved in teaching courses on quantum computation, artificial intelligence foundations, and computer science fundamentals at both undergraduate and graduate levels. Prof. Torsello's research interests include graph neural networks, quantum machine learning, and structural pattern recognition. His work often bridges theoretical computer science with practical applications in cultural heritage digitization and environmental monitoring. His recent articles highlight advancements in graph generation via spectral diffusion, quantum lens-based 3D shape analysis, and interpretable graph neural networks. He serves on the editorial boards of journals like Pattern Recognition and has contributed to projects funded by the EU’s H2020 program, including the VEiL initiative for visualizing engineered landscapes. His teaching spans topics such as quantum computation, advanced algorithms, and machine learning across multiple engineering programs.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +6 more

Anil Jain is a University Distinguished Professor in the Department of Computer Science & Engineering at Michigan State University, where he also served as Department Chair from 1995 to 1999. His extensive career has been dedicated to advancing the fields of pattern recognition and biometrics. His educational background includes: B.Tech. from Indian Institute of Technology, Kanpur (1969) M.S. from Ohio State University (1970) Ph.D. from Ohio State University (1973) Professor Jain's research focuses on statistical pattern recognition , data clustering , texture analysis , document image understanding , and biometric authentication . He is renowned for his contributions to biometrics, holding six patents in fingerprint matching and authoring several authoritative books, including the Springer Handbook of Fingerprint Recognition which received the PSP award. His highly cited survey paper "Data Clustering: A Review" has been instrumental in shaping the field of data clustering. While the provided text does not list multiple recent articles, his 1999 survey paper remains one of the most influential works in computer science, demonstrating enduring impact in data clustering and machine learning. His accolades include: Multiple best paper and outstanding contribution awards from the Pattern Recognition Society (1976, 1979, 1987, 1991, 1992, 1997, 1998) IEEE Transactions on Neural Networks Outstanding Paper Award (1996) IEEE Computer Society Technical Achievement Award (2003) PSP award from the Association of American Publishers (2003) Fellow of IEEE, ACM, and IAPR Fulbright Research Award, Guggenheim fellowship, and Alexander von Humboldt Research Award Delivered the 2002 Pierre Devijver lecture Although specific details about his advisees and research grants are not provided in the text, his leadership as Editor-in-Chief of IEEE TPAMI and his extensive publication record indicate a strong history of mentoring and securing research funding. Professor Jain is currently serving on the National Academies study team on Whither Biometrics, reflecting his ongoing engagement in high-impact collaborative research initiatives in biometrics.

• statistical pattern recognition
• data clustering
• texture analysis
• +2 more

Pietro Belloni is a Researcher (RTDa) at the Department of Statistical Sciences, University of Padua, Italy. His primary role involves advancing statistical methodologies for drug safety and public health research through interdisciplinary projects like the Age-IT initiative. He holds a PhD in Statistics from the University of Padua, completed under Professors Giovanna Boccuzzo and Nicholas P. Tatonetti, with visiting research at Columbia University's Department of Biomedical Informatics. His academic journey includes a Master’s and Bachelor’s in Statistical Sciences from the University of Padua, complemented by an Erasmus exchange in Mathematics and Statistics at Århus University. Belloni’s research focuses on epidemiology, medical statistics, and social statistics, with particular emphasis on text mining, spatial epidemiology, and composite indicators for public health assessment. He actively contributes to research teams such as GLASS (a young Italian social statistics laboratory) and the Age-IT project addressing aging society challenges. Teaching responsibilities span epidemiology, medical statistics, and data analysis methods at both University of Padua and H-Farm College. His software contributions include R libraries like perla for mortality cluster analysis and MARMoT for statistical balancing techniques. Belloni’s work bridges theoretical statistics with practical applications in healthcare and social sciences, with publications in journals like Statistical Methods & Applications and Acta Otorhinolaryngol Italica , and book chapters on pharmacovigilance and text mining. His research has addressed topics ranging from cancer staging through NLP to pandemic sentiment analysis during the first wave of the COVID-19 crisis.

• Epidemiology
• Medical Statistics
• Social Statistics
• +7 more

Giuseppe Macchiarella is an Associate Professor in RF Systems at the Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano. His research focuses on microwave filter design, resonator configurations, and advanced RF system architectures. He actively contributes to the Cadence University Program, providing students access to tools like Microwave Office and VSS. Key research areas include inline filter topologies, frequency-variant couplings, and synthesis techniques for high-performance filters. His work emphasizes analytical methods for optimizing filter selectivity, compactness, and stability. Notable contributions involve star-junction multiplexers, quasi-inline filters with strongly coupled resonators, and extracted-pole filter designs. Recent publications highlight advancements in topology optimization, matrix-based synthesis, and filtenna array modeling. His work bridges theoretical analysis and practical applications in telecommunications and satellite systems.

• RF Systems
• Microwave Filters
• Electromagnetics
• +3 more

Marinella Sciortino is a Professor at the University of Palermo , affiliated with the School of Basic and Applied Sciences and the Department of Mathematics and Computer Science . She serves as Director of the CINI Research Unit and is a member of the Academic Senate (2022-2024). Sciortino contributes to editorial and scientific committees for journals and conferences, including Theoretical Computer Science and the GRIN Committee . Research focuses on: Combinatorics on Words String Algorithms Automata Theory Symbolic Dynamics Data Compression Biological Sequence Analysis Her work includes groundbreaking studies on the Burrows-Wheeler Transform (BWT) , extending its application to multiple sequences and improving compression efficiency. She has supervised PhD student Giuseppe Romana and participated in numerous conference program committees (e.g., SPIRE , ICTCS , CiE ). Recent scientific contributions (2022-2020): BWT teaching methodologies String attractors Variant discovery in genomics Algorithmic perspectives on alternating BWT Positional clustering for SNP detection Mental rotation effects on computational learning Teaching roles include Laboratorio di Algoritmi (Computer Science) and Teoria dell'Informazione e Compressione Dati (Master's in Computer Science). Contact: marinella.sciortino@unipa.it , +39-091-238-91080.

• Combinatorics on Words
• Algorithms on Strings
• Automata Theory
• +4 more

Ladislau Matekovits is an Associate Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin, Italy. He holds a PhD in Electronic Engineering from the same university (1998) and has been affiliated with DET since post-doctoral fellowship in 1995. Education: Electronic Engineering (1992) from Institutul Politehnic din Bucuresti, Romania PhD: Electronic Engineering (1998) from Polytechnic University of Turin Research Interests: His work focuses on advanced numerical analysis of printed antennas, metamaterials, cloaking, and reconfigurable antenna systems. He employs integral equation methods for full-wave analysis, optimization techniques, and biosensor development. Recent Publications Trends: Recent works address sub-THz metamaterials, bound states in continuum via Babinet principle, neural network modeling for antennas, and high-gain antenna designs. These span applications in 6G communication, satellite systems, and medical diagnostics. Scientific Recognition: Awardee of the 2018 Motohisa Kanda Award (IEEE EMC Society), 2015 IEEE Access Editor of the Month, and 2013 International Collaboration Award (Australian Research Council). Editorial Roles: Associate Editor for IEEE Antennas and Wireless Propagation Letters (2017-), IET Microwaves Antennas & Propagation (2016-), IEEE Access (2014-) Conference Leadership: General Chair of 11th International Conference on Body Area Networks (2016) Research Projects: Currently leads the CanDia project (Wireless Healthcare for Oral Cancer Diagnosis) funded under PNRR Mission 4 (2025-2028) and commercial projects on environmental monitoring systems.

• Antennas
• Metamaterials
• Cloaking Technology
• +6 more

Ennio Bilancini is a full Professor of Economics at the IMT School for Advanced Studies Lucca, where he serves as Director of the PhD program in Economics, Analytics and Decision Sciences and Director of the GAME Science Research Center. He is also a member of AXES and founder of the BEE group at IMT. His research spans cognitive and behavioral economics, evolutionary game theory, and game science. Key areas include social norms, health behaviors, game-based learning, policy evaluation, subjective well-being, social welfare, sustainable development, and the evolution of behaviors and social interactions. Recent work focuses on prosocial behavior, evolutionary selection of game equilibria, strategic skills measurement, dual process decision-making, and social determinants of well-being. His publication record demonstrates consistent contributions across multiple high-impact journals in economics, game theory, and well-being research. His work shows a clear trajectory from theoretical game theory toward applied behavioral economics with policy implications. Bilancini actively supervises numerous PhD students and has led significant research projects including SYNERGIC EFFICIENCY, ETER, European Game Science Lab, GAMEDON, and others focused on health policy, sustainability, and game-based interventions. He teaches Game Theory, Evolutionary Game Theory, and Behavioral Economics at the PhD level, along with specialized courses in game-based learning, nudging & boosting, and choice architecture.

• Behavioral Economics
• Game Theory
• Evolutionary Game Theory
• +8 more

Mircea Petrache is an Assistant Professor at the Department of Mathematics, Pontifical Catholic University of Chile. His research focuses on geometric deep learning, compositional learning, optimal transport, calculus of variations, and geometric measure theory, with applications to large point configurations and mathematical analysis. He holds a PhD in Mathematics from ETH Zürich (2013) and an MSc from Scuola Normale Superiore (2008). Education: PhD in Mathematics, ETH Zürich, 2013 MSc in Mathematics, Scuola Normale Superiore, 2008 Research Interests: Petrache explores the interplay between geometric principles and machine learning, particularly in equivariant networks and compositional systems. His work on optimal transport and calculus of variations addresses energy minimization and crystallization problems in materials science. Recent projects include symmetry-based structured matrices and topological pseudodistances for data analysis. Grants: Fondecyt Regular Grant (2021–2025) on rigidity and uniformity in large point configurations. Events & Organization: Co-organized workshops such as 'Theoretical and Mathematical Aspects of Deep Learning' (2022) and 'Calculus of Variations: A New Generation' (2024). Active in conferences including NeurIPS, ICIAM, and AIM workshops on discrete geometry.

• Geometric Deep Learning
• Compositional Learning
• Optimal Transport
• +4 more

Riccardo Marin is a Post-Doctoral Researcher at the University of Tuebingen, supported by the Humboldt Post-Doctoral Fellowship. He is part of the Real-Virtual Humans group led by Prof. Gerard Pons-Moll. Previously, he conducted post-doctoral research at Sapienza University of Rome in the GLADIA group under Prof. Emanuele Rodolà, contributing to the SPECGEO ERC project. He earned his Ph.D. in Computer Science from the University of Verona under Prof. Umberto Castellani, winning the Best PhD Thesis Award by EG-Italy. He holds a Master's degree in Computer Science and Engineering from the University of Verona (2017). His research focuses on Spectral Shape Analysis, Geometric Deep Learning, and Virtual Humans, with contributions to top-tier conferences and journals (NeurIPS, IJCV, CVPR). Key achievements include a Best Student Paper Award at 3DV 2020 and five Outstanding Reviewer Awards. He actively serves as a reviewer for leading journals and conferences (PAMI, TCVG, CVPR, NeurIPS) and has organized events like Siggraph RCD and 3DV 2018. Collaborations include institutions like École Polytechnique, Max-Planck Institute, INRIA Strasbourg, UCL, and the University of Milan. His work is supported by grants from Google and the European Research Council (ERC). His research bridges geometry processing with machine learning, emphasizing spectral methods and shape correspondence. Notable projects include MoMaS (real-time procedural texturing), FARM (3D human body registration), and contributions to latent space analysis for shape modeling. He maintains an active GitHub profile with repositories like NICP and InstantRecoveryFromSpectrum .

• Spectral Shape Analysis
• Geometric Deep Learning
• Virtual Humans
• +3 more