Find Academic Supervisors

Martino BanchioView profile

Assistant Professor

• Microeconomic Theory
• Market Design
• Mechanism Design
• +2 more

Martino Banchio is an Assistant Professor at the Department of Economics of Bocconi University and an Affiliate of the Innocenzo Gasparini Institute for Economic Research (IGIER). He concurrently serves as a part-time Research Scientist at Google Research. His work bridges microeconomic theory, market/ mechanism design, and computer science. His PhD thesis earned an honorable mention in the 2023 ACM SIGecom Doctoral Dissertation Award. Research interests focus on market design, industrial organization, and computer science applications in economics. Notable contributions include studies on credible auctions, AI-driven collusion, and dynamic pricing mechanisms. He frequently publishes in top venues like the ACM Conference on Economics and Computation (EC) and the ACM Web Conference (WWW). His awards include the Research Paper Competition at MIT Sloan Sports Analytics Conference 2020 and the Exemplary AI Track Paper Award. His research explores cutting-edge topics such as AI ethics in market design and algorithmic game theory, reflecting a strong interdisciplinary approach. No student advising records are explicitly listed. His work bridges academic theory and industry applications, as seen through collaborations with Google Research and affiliations with leading economic institutes.

• GPU Acceleration
• Embedded Systems
• Autonomous Vehicles
• +6 more

Nicola Capodieci is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia, specializing in Information Processing Systems (IINF-05/A). He actively teaches multiple courses including Object-Oriented Programming, Web Technologies, and General Computer Science across Computer Science and Mathematics degree programs. His research interests focus on GPU acceleration for embedded systems, autonomous vehicles, and real-time computing. Dr. Capodieci's work addresses critical challenges in heterogeneous computing platforms, particularly for automotive applications and smart city infrastructure. His research bridges theoretical computer science with practical applications in autonomous driving and urban mobility systems. Analysis of his recent publications reveals a strong focus on optimizing GPU performance for latency-sensitive applications, particularly in autonomous vehicles. His work spans path planning algorithms, memory interference management, and real-time scheduling on heterogeneous platforms. A significant portion of his research addresses practical implementation challenges in embedded systems where computational resources are constrained but timing predictability is critical. Dr. Capodieci's teaching portfolio demonstrates expertise in both foundational programming concepts and advanced topics in web technologies. His courses emphasize practical implementation skills while covering theoretical foundations of object-oriented programming, web development frameworks, and computational thinking.

Li LiView profile

Professor

• Mobile Software Engineering
• Intelligent Software Engineering
• Software Security
• +6 more

Li Li is a Professor of Software Engineering at Beihang University , China. Previously, he served as an ARC DECRA Fellow and Senior Lecturer at Monash University , leading the SMart software Analysis and Trustworthy computing (SMAT) research lab at the Department of Software Systems and Cybersecurity. His academic journey includes a Ph.D. in Software Engineering from the University of Luxembourg (2016), supervised by IEEE Fellow Prof. Yves Le Traon and Dr. Jacques Klein. Research Interests Li's research focuses on Mobile Software Engineering (Mobile Security, Quality Assurance) and Intelligent Software Engineering (SE4AI, AI4SE). He applies static code analysis , dynamic program testing , and machine/deep learning to enhance software security and reliability. Key areas include Android API evolution, automated patch validation, and multi-language code analysis frameworks like Scalpel for Python. Scientific Recognition ARC DECRA Fellowship Rising SE Research Star Top-5 Most Impactful Early Career SE Researchers (2020, 2017) 5 Best/Distinguished Paper Awards across PLDI, WWW, ASE, MSR, and SANER Academic Contributions He has contributed to foundational Android analysis tools (e.g., AndroZoo++, DroidRA) and developed scalable systems for distributed program analysis (Seads). His work appears in top venues like ICSE, ESEC/FSE, ASE, ISSTA, POPL, and TSE.

• Human-Centered Systems
• Human-Computer Interaction
• Artificial Intelligence
• +9 more

Alessio Malizia is a Professor of User Experience Design at the University of Hertfordshire, UK, and concurrently holds a full Professorship at the Computer Science Department of the University of Pisa, Italy. His research focuses on Human-Centered Systems, Human-Centered AI, and Design Fictions, emphasizing ethical AI, user participation, and the integration of visual programming languages. He has held roles at institutions including Sapienza University of Rome, IBM, Silicon Graphics, and Xerox PARC, where he researched neural networks and gestural interfaces. His work bridges academia and industry, addressing challenges in healthcare, agriculture, and education. Malizia’s career includes visiting research at Xerox PARC, associate professorship at the University Carlos III of Madrid, and senior lecturer roles at Brunel University London. He is an ACM Distinguished Speaker and actively promotes democratizing AI through tools like BlocklyBias and PyFlowML. His research spans touchless interfaces, collaborative design methodologies, and AI explainability. Key contributions include frameworks for socio-technical process modeling in agriculture, tools for bias detection in AI data, and visual languages fostering user participation in ML systems. His work on telemedicine and healthcare AI emphasizes co-design and trusted AI systems. Recent studies explore end-user development for smart environments, digital agriculture, and computational thinking education through tools like TAPASPlay. Awards: ACM Distinguished Speaker Key Interests: Human-AI Interaction, UX Design, AI Ethics, IoT Ecosystems, and Co-Creation Methodologies Notable Projects: Figmant, ModeLLer, and the Chatbot Usability Scale validation His grants and collaborations focus on improving AI transparency, user-centered design processes, and participatory innovation in technology adoption across sectors.

• CAT Tools
• Machine Translation (MT)
• Neural Machine Translation (NMT)
• +5 more

FIORENZA MILETO is a tenured Lecturer at the Università degli Studi Niccolò Cusano (UNINT) since 2004, teaching specialized English translation, computer-assisted translation, and machine translation. She concurrently serves as a tenured teacher of English language and literature at the Liceo Scientifico 'Aristotele' in Rome since 2013. Since March 2020, she has been pursuing a PhD in machine translation at Dublin City University. Her professional career includes roles as a freelance translator for ITP Italia (SDL), Berlitz, and UNICEF, followed by editorial work on the Oxford-Paravia dictionary in Turin. She transitioned into project management and technical training at STAR in Alessandria, Keywords Italia, and SDL Italia, specializing in CAT tools (SDL Trados Studio) and machine translation systems. She was an authorized SDL Trados trainer for Italy (2009–2011) and a Network Office Machine Translation Champion. Her research focuses on computational linguistics tools, translation technology optimization, terminology systems, and quality assurance protocols. She has extensive experience in localization workflows and post-editing strategies for MT systems.

Gian Pietro PiccoView profile

Professor

• Building Automation
• Pervasive Computing
• Software Engineering
• +12 more

Gian Pietro Picco is a Full Professor at the Department of Information Engineering and Computer Science (DISI) at the University of Trento, Italy. His research focuses on wireless networks, particularly ultra-wideband (UWB) technology, wireless sensor networks, and cyber-physical systems. He teaches courses including Distributed Systems, Low-power wireless networking for the Internet of Things, and Programming 2. Professor Picco's research interests span several interconnected domains in pervasive computing and networking: Ultra-wideband (UWB) technology for precise localization and communication Wireless sensor networks and Internet of Things (IoT) systems Cyber-physical systems and networked control Energy-efficient networking protocols Distributed systems and middleware Software engineering approaches for networked embedded systems His recent publications demonstrate a strong focus on ultra-wideband technology applications, particularly in localization, ranging, and concurrent transmissions. His work bridges theoretical foundations with practical implementations, often addressing real-world challenges in human-robot interaction, contact tracing, and infrastructure monitoring. A notable trend is the increasing application of UWB technology for precise positioning in complex environments, with significant contributions to understanding and mitigating human occlusion effects on ranging accuracy. Professor Picco has received numerous prestigious awards for his research contributions: Best Paper Award at IPSN'23 for "Network On or Off? Instant Global Binary Decisions over UWB with Flick" Best Paper Award at IPIN 2019 for "TALLA: Large-scale TDoA Localization with Ultra-wideband Radios" Best Paper Award at EWSN 2018 for "Concurrent Ranging in Ultra-wideband Radios" Best Paper Award at IPSN 2015 for "Geo-referenced Proximity Detection of Wildlife" Best Paper Award at IPSN 2011 for "Wireless Sensor Networks for Adaptive Lighting in Road Tunnels" Best Paper Award at IPSN 2009 for "Monitoring Heritage Buildings with Wireless Sensor Networks" Mark Weiser Best Paper Award at PerCom 2012 Professor Picco actively advises numerous PhD and Master's students, with several of his advisees becoming prominent researchers in wireless networking. His laboratory has secured significant funding for research projects in wireless sensor networks, IoT systems, and cyber-physical systems. His work has practical applications in heritage building monitoring, wildlife tracking, road tunnel lighting systems, and pandemic contact tracing. His research group maintains the Cloves large-scale ultra-wideband testbed and has developed several middleware systems for wireless sensor networks, including Lime and TeenyLIME. The group collaborates extensively with international research institutions and has made significant contributions to standardization efforts in IoT networking protocols.

Agostino CortesiView profile

Professor

• Software Engineering
• Static Analysis
• Cybersecurity
• +5 more

Agostino Cortesi is a Full Professor at Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Informatics and Statistics. He serves as Rector's Delegate for Research Quality Assessment and Deputy Coordinator of the Scientific Committee for the Innovation Ecosystem Project. His academic career includes a PhD in Applied Mathematics and Informatics from the University of Padova (1992), a postdoctoral fellowship at Brown University, and visiting professor roles at institutions such as the University of Illinois and École Normale Supérieure Paris. Research interests focus on software engineering , static analysis , security applications , and abstract interpretation . He has pioneered techniques for formal verification of software systems and explored cybersecurity in e-Government and robotics. His work spans over 200 publications in top journals and conferences (e.g., ACM TOPLAS, IEEE TSE, POPL, PLDI). Key contributions include advancements in abstract domains for behavioral property verification and security-oriented analysis frameworks. He has held leadership roles including Vice-Rector at Ca' Foscari, Dean of Computer Science programs, and Chair of the Department of Computer Science. Cortesi coordinates EU Horizon 2020 projects (e.g., Families_Share €1.6M) and regional initiatives like CEVID (€360K). He founded Factors , a university spin-off focused on robotic systems verification, which won the 2020 Veneto SmartCup ICT Prize. Education: PhD in Applied Mathematics and Informatics (1992, University of Padova) Editorial Roles: Co-Editor-in-Chief of Springer’s 'Services and Business Process Reengineering', and member of editorial boards for 'Computer Languages' and others Grants: Over €3M in EU and regional funding for projects in cybersecurity, Industry 4.0, and digital innovation Teaching includes courses on Software Correctness , Data Programming , and Computer Networks across Computer Science and Management programs. His research lab actively engages in industrial partnerships with Cisco, Leonardo, and AGID (Italy’s Digital Agency).

• Cognitive Neuroscience
• Functional Neuroimaging
• Brain Mapping
• +3 more

Sabrina Pitzalis is an Associate Professor at the University of Rome 'Foro Italico', Department of Human Motor Sciences and Health. She serves as Delegate for Gender Budget and Head of the SACS (Student Counselling and Help Desk). Her research focuses on cognitive neuroscience, functional neuroimaging, and brain mapping, with specializations in neural mechanisms of perception, sensorimotor functions, and brain plasticity induced by motor activity. She leads projects like the 2019 study on neuromuscular electrical stimulation effects. Her work integrates neuroimaging techniques to explore topics such as anticipatory brain activity and motion perception. Pitzalis teaches courses in sport psychology, neuroscience, and pedagogy, emphasizing the interplay between cognitive and motor systems. Her research highlights neural adaptations to sensory and motor interventions, including multifocal contact lenses and exoskeleton-assisted rehabilitation. Research Themes: Neural basis of perceptual and sensorimotor functions Brain plasticity and motor learning Anticipatory neural processing during action preparation Integration of visual and motor signals in spatial navigation Recent Contributions: Her articles (2022–2025) reveal insights into how brain circuits process self-motion, adapt to sensory interventions, and modulate during complex cognitive-motor tasks. These studies use advanced neuroimaging and electrophysiological methods to map functional brain dynamics. Ongoing work explores neurocognitive trade-offs in dual-task scenarios and the role of parietal cortex in visuomotor integration. Teaching and Leadership: Pitzalis contributes to degree programs in Sports Sciences (L22), Preventive Motor Activities (LM67), and Sports Technology (LM68). She promotes interdisciplinary approaches, combining neuroscience with sport pedagogy. Her leadership roles emphasize institutional quality assurance and student support initiatives. Labs/Teams: Collaborates within university labs specializing in motor neuroscience and neuroimaging, contributing to projects on neural adaptation mechanisms and clinical applications in rehabilitation.

• Biomolecular Sciences
• Cellular Biology
• Computational Biology
• +1 more

Maulana Ariefai serves as a Research Fellow at the Department of Cellular, Computational, and Integrative Biology (CIBIO) within the University of Trento, Italy, where he concurrently pursues his PhD in the Biomolecular Sciences Doctoral Program (DM226/2021). His research spans interdisciplinary domains including Biomolecular Sciences, Cellular Biology, Computational Biology, and Integrative Biology, reflecting CIBIO's mission to merge experimental and computational methodologies for biological discovery. This work emphasizes systems-level understanding through quantitative and molecular approaches.

• Big data
• Data science
• Data analytics
• +12 more

Paolo Garza is an Associate Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he also serves as Coordinator of the College of Computer, Film and Mechatronics Engineering. He is a member of the DBDM research group and the SmartData@PoliTO laboratory, and actively contributes to academic governance through roles in teaching coordination and PhD program committees. Education: Bachelor’s in Computer Engineering, Polytechnic University of Turin (2001) PhD in Computer and Systems Engineering, Polytechnic University of Turin (2005) His research centers on data science, big data analytics, data mining, and machine learning , with applications in emergency management, real-time communications, Earth observation, and cybersecurity. He has led and participated in numerous national and commercial research projects, including AI4CTI and NODES (PNRR), and has collaborated with industry partners like Cisco Systems. His work bridges theoretical algorithm development and practical deployment in critical systems. The recent publications reflect a strong trend toward multimodal AI, crisis informatics, and intelligent networking . Articles span computer vision for environmental monitoring (e.g., burned area detection, canopy estimation), ML for real-time communication quality, multimodal document understanding, and crisis response systems. His team leverages deep learning, transformers, and vision-language models across diverse domains. Scientific Service: Associate Editor, Knowledge and Information Systems (2024–) Associate Editor, Expert Systems with Applications (2022–) General Co-Chair, IEEE AICT Conferences (2022, 2023) He mentors several PhD students and leads funded research initiatives focused on AI for sustainable industry and cyber threat intelligence. His teaching includes graduate courses on big data processing, distributed architectures, and data science lab methods. He has also directed commercial training programs and research contracts in machine learning and cybersecurity. Research Labs & Teams: DBDM - Database and Data Mining Group (DAUIN) SmartData@PoliTO - Big Data and Data Science Laboratory LAB 5 - Research Laboratory (DAUIN)

Michel RiveillView profile

Professor

• Medical Data Analysis
• Computer Science
• Machine Learning
• +3 more

Michel Riveill is a Professor of Computer Science at Côte d'Azur University, affiliated with the Polytech Nice department. He is a computer science researcher in the MAASAI team shared by Inria and the I3S Laboratory, with a focus on medical data analysis. His teaching includes concurrent programming, machine learning, and distributed systems. Professor since 2000 at University of Nice Sophia Antipolis (now Côte d'Azur University) Director of I3S Laboratory (2012-2016) UNS Vice President for Sophia Antipolis (2010-2016) Part-time affiliation with Inria-LIRMM Zenith team (2017-2019) His research centers on medical data analysis, leveraging expertise in computer science foundations such as algorithms, operating systems, and component-based programming. While his publications are not explicitly listed, they span topics in computer science and medical data applications. Michel Riveill has held significant administrative roles, including Director of the I3S Laboratory, Vice President for Sophia Antipolis at the University of Nice Sophia Antipolis, and various board memberships in academic and innovation organizations.

• Asymptotic statistics
• Bayesian inference
• Biostatistics
• +9 more

Enrico Bibbona is an Associate Professor at the Department of Mathematical Sciences (DISMA) at Politecnico di Torino, where he contributes to the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. His academic profile spans statistics, mathematical modeling, and data science applications across multiple engineering disciplines. His primary research interests include: Asymptotic statistics Bayesian inference Biostatistics Industrial statistics Mathematical biology and modeling in life sciences Statistical inference for stochastic processes Stochastic modeling His specific research lines focus on Reaction Networks approximation and inference, Statistical modeling of animal calls, Statistics and modeling for the SmartPad system (in collaboration with ITT), and Statistics for deterministic and stochastic dynamical models. His work bridges theoretical statistics with practical applications across various scientific domains, particularly in biological systems, industrial applications, and data science. His notable recognition includes the Elsevier/SPA Travel Award presented by Elsevier and Bernoulli Society, Denmark (2011). Professor Bibbona actively mentors PhD students across multiple programs, currently supervising Daniele Poggio and Saeed Sani in Mathematical Sciences, and has previously guided Elena Sabbioni (thesis: Statistical Methods for Complex Biological and Clinical Data) and Hiu Ching Yip (thesis: Statistical models for understanding biomedical data). His teaching spans Mathematical Engineering, Data Science and Engineering, and Communications Engineering programs, where he teaches courses including BioQuants, Statistical methods in data science, and Project: Software-defined communication systems. He is a key member of the Statistics and Data Science research group at DISMA and has contributed to practical applications through patents including "BRAKING SYSTEM TEMPERATURE ESTIMATOR" and "A method for estimating the wear of a vehicle brake element," demonstrating his ability to translate theoretical work into real-world solutions.

• Business Model Design
• Web3 Technologies
• Cultural Heritage Management
• +4 more

Chiara Vandoni is a PhD candidate in Management and Production Engineering at the Polytechnic University of Turin's Department of Management and Production Engineering (DIGEP) for the 39th cycle (2023-2026), concurrently serving as an external teacher and teaching assistant for the Master's Degree Course Challenge@PoliTo by Firms - Municipality of Turin in the 2024/25 academic year. Her academic foundation includes: Bachelor's degree in Management Engineering from Polytechnic University of Turin (2020) Master's degree in Management Engineering from Polytechnic University of Turin (2022) Her research centers on digital transformation across organizational and individual contexts, with specialized focus on innovation management and emerging technologies . Her doctoral work investigates how Web3 technologies can create sustainable business models for cultural heritage institutions, specifically aligning museum operations with visitor engagement through decentralized solutions. Additional interests encompass business model innovation, technology economics, and transformative applications in traditional sectors. Publication analysis reveals concentrated expertise in technology-culture intersections, particularly blockchain/NFT implementations in museums and BPMN-driven legal process optimization. Her work demonstrates consistent interdisciplinary methodology bridging computer science, cultural management, and legal frameworks, with recent emphasis on qualitative barriers to Web3 adoption and data-driven judicial improvements. No scientific awards or fellowships were documented in the source materials. Supervised by Guido Perboli and Maria Elena Bruni, she maintains an industry partnership with TIM SpA for market research under her doctoral project. Her funding derives from PhD enrollment and prior DIGEP research fellowship, though specific grants remain unspecified. She operates within DIGEP's research ecosystem at Polytechnic University of Turin, engaging cross-functional teams that merge technical engineering with managerial strategy, particularly through her TIM SpA collaboration on cultural heritage digitization initiatives.

• Robotics
• Manufacturing Engineering
• Mechanical Engineering Design
• +5 more

Fabio Pini is an Associate Professor at the University of Modena and Reggio Emilia's Department of Engineering 'Enzo Ferrari'. His research focuses on robotics, manufacturing engineering, and advanced design methodologies. He leads the IDEALab (Intelligent Design, Engineering, and Automation Laboratory) and teaches courses in Smart Robotics, Automotive Design, and Additive Manufacturing. Education: Not explicitly stated in provided texts. Research Interests: Collaborative robotics and human-robot interaction Computer-aided design (CAD) and topology optimization Additive manufacturing processes and sustainability Automotive component design and lightweighting Robotics in medical applications (e.g., surgical navigation) Manufacturing process integration and automation Teaching: Smart Robotics (Master's in Electronics/Computer Engineering) Formula SAE Vehicle Design (Mechanical Engineering) Integrated Computer-Based Design (Mechanical Engineering) Automotive Computer-Aided Design (Advanced Automotive Engineering) Labs/Teams: IDEALab focuses on intelligent design systems, robotic automation, and advanced manufacturing solutions. Collaborations include industry partners for automotive and medical robotics projects.

• Formal Methods
• Formal Verification
• Binary Decision Diagrams
• +7 more

Paolo Enrico Camurati is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at the Polytechnic University of Turin, where he contributes to research and teaching in formal methods and hardware verification. He is a member of the Formal Methods (FM) research group and has been actively involved in PhD supervision in the Computer and Systems Engineering program. His research interests include formal verification, binary decision diagrams, SAT solvers, electronic CAD, and the formal verification of hardware design correctness. These areas align with theoretical computer science and cyber-physical systems, contributing to advancements in reliable computing systems. Recent publications (2022–2024) show a strong focus on model checking techniques, interpolation-based learning, and optimization of binary decision diagrams for machine learning applications, indicating active and impactful research in formal methods and EDA. He has taught core computer engineering courses such as Specification and Simulation of Digital Systems , Algorithms and Data Structures , and Programming Techniques at both bachelor's and master's levels, supporting quality education in computing disciplines. He has no listed scientific awards in the provided material. Prof. Camurati advises PhD students in the Computer and Systems Engineering program and has taught extensively across multiple academic years. While specific grants are not mentioned, his ongoing research output suggests active funding and project involvement. He is a key member of the FM - Formal Methods Group (DAUIN), which drives research in formal verification and automated reasoning. The FM - Formal Methods Group (DAUIN) serves as his primary research lab, focusing on theoretical and applied aspects of formal verification, model checking, and decision diagram technologies.