Find Academic Supervisors

• Software Engineering
• Deep Learning
• Human-Computer Interaction
• +7 more

Prof. Dr. Chunyang Chen is a full professor in the Department of Computer Science at the Technical University of Munich (TUM) in Heilbronn, Germany, and an adjunct professor at Monash University, Australia. He is a core member of the Munich Data Science Institute, board member of Heilbronn Data Science Center, and fellow at Fortiss. His research spans Software Engineering, Deep Learning, and Human-Computer Interaction (HCI), focusing on AI/ML, NLP, and program analysis applications. PhD from Nanyang Technological University (NTU), Singapore His research explores three primary domains: AI-Driven Mobile App Development : Focused on requirement elicitation, UI design, code generation, and GUI testing using LLMs, NLP, and lightweight program analysis. Software Repository Mining : Involves library/API migration, collaborative editing, query reformulation, and thesaurus construction. Deep Learning Security : Examines robustness and security in mobile apps, including on-device model attacks, backdoor attacks, phishing attacks, and defense mechanisms. His recent publications highlight trends in LLM applications for software testing, bug replay, accessibility, and dataset construction. Awards include Best Paper Honorable Mention at CHI 2024, DECRA, ACM SIGSOFT Early Career Award, multiple Distinguished Paper Awards, and the Chinese Government Award for Outstanding Self-financed Students Abroad. PhD students: Shengcheng Yu, Yanqi Su, Mark Huasong Meng, Wenchao Gu, Zhen Tao, Kai Huang, Sidong Feng, Yujin Huang, Jian Gu Master/Bachelor students: Dustin Minh Duc Vu, Jason Siu, Ruiqi Dong, Minh Nguyen, An-Chieh Chang, Chao Wu, Yujin Huang, Ishan Joshi, Xinyan Li Chunyang Chen has supervised numerous students across institutions including TUM, Monash University, Chinese Academy of Sciences, ANU, and others. His teaching portfolio includes courses on Generative AI, software engineering, and programming foundations. He actively contributes to academic service as a guest editor, program committee member, and reviewer for top-tier conferences and journals.

Ting SunView profile

Associate Professor

• Urban climate modelling
• Climate change impacts and adaptation
• Extreme weather events in cities
• +5 more

Dr Ting Sun is an Associate Professor in Climate & Meteorological Hazard Risks at University College London , Department of Risk and Disaster Reduction. He earned his BEng (2009) and PhD in Hydrology (2013) from Tsinghua University , followed by a visiting period at Princeton University (2011–2012). After postdoctoral appointments at Tsinghua and the University of Reading , he held a NERC Independent Research Fellowship at Reading (2017–2022) before joining UCL in May 2022. Education PhD in Hydrology, Tsinghua University, 2013 BEng in Hydraulic Engineering, Tsinghua University, 2009 Visiting PhD Student, Princeton University, 2011–2012 Research Interests Dr Sun’s work converges on urban climate modelling across scales —from neighbourhood blocks to global grids—focusing on the impacts of weather and climate extremes such as heat waves and extreme rainfall in cities. He is the lead developer of the Surface Urban Energy and Water balance Scheme (SUEWS) and its Python wrapper SuPy , developed in collaboration with Prof Sue Grimmond’s micromet group. He also contributes as a core member of the Urban Multi-scale Environmental Predictor (UMEP) development team. His multidisciplinary expertise integrates hydro-climate dynamics, computational modelling, machine learning, built-environment processes, and public-health linkages . Research Trends from Recent Publications Across the 15 most recent articles, a clear trajectory emerges from high-resolution urban-process modelling toward integrated socio-environmental assessments . Studies published in 2024–2025 couple atmospheric models (WRF-SUEWS) with global building-morphology datasets (GLAMOUR) to quantify how cities alter rainfall patterns, temperature sensitivity, and heat-related mortality. Earlier works progressively refined SUEWS’s physical parameterisations and Python accessibility, while recent outputs leverage deep-learning remote-sensing tools (SHAFTS) and hybrid hydrological-neural architectures to deliver actionable insights for urban planning and climate adaptation. Scientific Awards & Fellowships NERC Independent Research Fellowship , University of Reading, 2017–2022 HEA Fellowship , University College London, 2023 Professional Service & Editorial Roles Topic Editor , Geoscientific Model Development (from 2025) Editorial Board Member , Scientific Data (from 2024) Peer review and consultancy for journals, conferences, and policy bodies Supervision of taught-course projects and research degrees External examining and mentoring Labs, Teams & Collaborations Dr Sun leads and collaborates within the UCL Department of Risk and Disaster Reduction , working closely with the micromet group at the University of Reading (Prof Sue Grimmond) on SUEWS/SuPy development. He is an active member of the UMEP consortium and maintains extensive international collaborations spanning Tsinghua University, Princeton, and numerous European research centres, underpinning a vibrant, interdisciplinary research network focused on urban climate resilience.

Diana Gratiela BerbecaruView profile

Associate Professor

• Cybersecurity
• Authentication
• Authorization
• +12 more

Diana Gratiela Berbecaru is an External Collaborator and External Lecturer at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, where she contributes to teaching and research in cybersecurity and digital identity. She is affiliated with the TORSEC Security Group and actively participates in EU-funded research projects such as Q-FENCE, focusing on quantum-resistant cryptography. She teaches core courses including Security and Privacy for Digital Identity Frameworks and Information Systems Security , and has been recognized with the Italian national scientific habilitation as Associate Professor in 2025, affirming her academic standing. Full Name: Diana Gratiela Berbecaru University: Politecnico di Torino Department: Department of Control and Computer Science (DAUIN) Academic Rank: Associate Professor (habilitated) Teaching Status: Part-time External Lecturer Email: diana.berbecaru@polito.it Her research focuses on cybersecurity, identity management, and trusted computing, with specific interests in authentication, authorization, data privacy, network security, and trusted computing in distributed and IoT environments. She investigates practical implementations of digital identity systems using the eIDAS infrastructure, certificate validation, TLS security, and post-quantum cryptography. Her work bridges theoretical security models with real-world deployment challenges. Her recent publications (2022–2025) reflect a strong focus on TLS security, X.509 certificate analysis, anomaly detection using AI, remote attestation for IoT, and post-quantum migration strategies. These works are published in high-impact venues such as IEEE Access, IEEE ISCC, and ARES, indicating active and influential contributions to the cybersecurity research community. The research trend shows a consistent emphasis on practical tools and frameworks for enhancing trust and security in digital systems. Scientific Awards and Recognition: Italian National Scientific Habilitation as Associate Professor (Abilitazione Scientifica Nazionale, II fascia), 2025 She serves as an Associate Editor for IEEE Transactions on Network and Service Management and IEEE Access , and as a Guest Editor for Electronics and Computer Networks . She chairs and co-chairs international workshops such as TrustAICyberSec and IMTrustSec, and is a frequent member of program committees for major conferences including ARES, IDC, and ISCC. These roles demonstrate her active engagement in academic leadership and knowledge dissemination. Labs and Research Groups: TORSEC - Security Group (DAUIN): Core research group focusing on cybersecurity, trusted systems, and digital identity.

• Numerical Linear Algebra
• Numerical Nonlinear Algebra
• Parallel Computing
• +7 more

Prof. Zhong-Zhi Bai is a Professor of Computational Mathematics at the Institute of Computational Mathematics and Scientific/Engineering Computing, part of the Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing. He is based at the State Key Laboratory of Scientific/Engineering Computing, a leading institution in applied mathematics and high-performance computing in China. His research spans a broad range of topics in computational mathematics, with a strong emphasis on numerical linear and nonlinear algebra , parallel computations , numerical optimization , and sparse matrix techniques . He has made significant contributions to the development and analysis of preconditioners and numerical methods for differential-algebraic equations and partial differential equations . His work is foundational in advancing iterative solvers and large-scale scientific simulations. The available publications, including the notable book Milestones in Matrix Computation (2007), reflect a long-standing engagement with matrix computation and numerical algorithms. The research trends indicate a deep focus on theoretical and practical aspects of numerical methods, particularly in the context of high-performance and scientific computing environments. Prof. Bai serves on the editorial boards of several leading journals in the field, including: Applied Numerical Mathematics Communications on Applied Mathematics and Computation Computational and Applied Mathematics East Asian Journal on Applied Mathematics Electronic Transactions on Numerical Analysis Journal of Computational and Applied Mathematics Journal of Mathematical Study Journal of Scientific Computing Numerical Algorithms Numerical Linear Algebra with Applications He has advised students and mentored researchers, though specific names are not listed. His work is supported by institutional affiliations and likely national research grants, given his position in a State Key Laboratory. He has developed software tools and delivered lecture series, contributing to both research and education in computational mathematics. Prof. Bai is actively involved in the numerical linear algebra community and maintains a comprehensive academic presence, including publications, editorial service, and software contributions. He leads or participates in research teams focused on advancing computational methods within the State Key Laboratory framework.

Andrea MorichettaView profile

Associate Professor

• Blockchain Technology
• Smart Contracts
• Business Process Management
• +4 more

Andrea Morichetta is an Associate Professor at the University of Camerino (UNICAM). His research focuses on blockchain technology, smart contracts, and business process management. He explores the integration of blockchain with choreography-based systems, model-driven engineering, and process mining. His work addresses challenges in smart contract testing, distributed systems coordination, and auditability in decentralized applications. Key research areas include: Blockchain-based execution frameworks for BPMN choreographies Mutation testing strategies for Solidity smart contracts Decentralized identity systems using blockchain Event log analysis for Ethereum applications His publications highlight advancements in: Smart contract security and testing methodologies Choreography-driven architectures for IoT and MLOps Formal analysis of business process collaborations He contributes to international conferences and workshops on blockchain, enterprise modeling, and business informatics research. His work bridges theoretical foundations with practical implementations in distributed systems and process automation.

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.

Michele GermaniView profile

Professor

• Industrial Engineering
• Ergonomics
• Sustainability
• +7 more

Prof. Michele Germani is a Full Professor at the Polytechnic University of Marche, Department of Industrial Engineering and Mathematical Sciences. His research focuses on ergonomics, sustainability, and human-centered design, with particular emphasis on industrial automation, wearable technologies, and circular economy principles. He leads projects on ergonomic risk assessment, environmental impact modeling, and smart manufacturing systems. Academic Background: Holds a position in the Faculty of Engineering, contributing to both teaching and research. His work integrates machine learning, sensor-based systems, and virtual reality to address challenges in manufacturing, healthcare, and sustainable design. Research Interests: Prof. Germani explores topics such as design for disassembly, eco-design tools, and the application of advanced technologies (e.g., exoskeletons, cobots) to enhance workplace safety and efficiency. His studies often bridge engineering and environmental science, aiming to reduce carbon footprints through innovative design methodologies. Key Projects: Development of decision support systems for fall risk detection, sensor-based ergonomic evaluation tools, and frameworks for circular economy implementation. He also investigates the impact of Industry 4.0 technologies on workforce dynamics and operator training via mixed reality simulations. Grants & Collaborations: Engaged in interdisciplinary collaborations focusing on sustainable manufacturing, healthcare technology, and smart systems. His research has led to tools like Durabot for durability analysis and Greenbuild for green building design. Labs & Teams: Oversees labs developing eco-design strategies, human-robot collaboration systems, and ergonomic assessment protocols, with a focus on real-world industrial applications.

• Digital Circuits and Systems
• Energy Efficiency
• Smart Cities
• +13 more

Enrico Macii is a Full Professor at the Politecnico di Torino, affiliated with the Interuniversity Department of Regional and Urban Studies and Planning (DIST) and the Department of Control and Computer Engineering (DAUIN). He leads the Electronic Design Automation (EDA) research group and holds key roles as Scientific Advisor for the Politecnico-STMicroelectronics partnership and Scientific Contact for the European Chips Joint Undertaking. Research Interests: His work spans digital circuits and systems, energy efficiency, smart cities, Industry 4.0, and smart manufacturing. He focuses on embedded and cyber-physical systems, low-power design, neuromorphic computing, AIoT, and sustainable urban development. Recent Publications: His recent research demonstrates strong trends in edge AI, neuromorphic computing, and smart energy systems. Articles highlight innovations in low-power hardware acceleration, federated learning, physics-informed AI, and digital twin applications for urban and industrial systems. There is a clear emphasis on deploying AI efficiently on constrained devices and integrating physical models with machine learning. J. William Fullbright Fellowship (1993) Best paper award IEEE European Design Automation Conference (1996) Best paper award ACM/IEEE Great Lakes Symposium on VLSI (2008) DAC Service Award (2014) IEEE Fellow (2006) DATE Fellow (2014) Advising and Grants: He has supervised over 25 PhD students in computer engineering, AI, and urban systems. His research is funded by major EU programs (Horizon 2020, PNRR, KDT JU), national (PRIN, FAR), and regional grants, as well as industrial contracts with STMicroelectronics, Michelin, and Cefriel. He leads numerous high-impact projects in smart manufacturing, energy efficiency, and digital twins. Labs and Teams: He is a core member of the EDA Group, an interdepartmental research team at Politecnico di Torino focusing on VLSI-CAD, bioinformatics, smart cities, and Industry 4.0. He also contributes to IAM@PoliTo (Integrated Additive Manufacturing) and leads multiple EU and national research consortia.

Shervin ShirmohammadiView profile

Professor

• Computer Vision
• Image Processing
• Health Monitoring Systems
• +4 more

Dr. Shervin Shirmohammadi is a Professor at the University of Ottawa's Faculty of Engineering, specifically within the School of Electrical Engineering and Computer Science. With an impressive h-index of 41 and over 6,800 citations across 473 publications, his research has made significant contributions to the fields of computer vision, biomedical instrumentation, and health monitoring systems. His academic journey spans over two decades, beginning with work on communication architectures for virtual environments in 2001 and evolving toward practical healthcare applications. Dr. Shirmohammadi's research interests center on Computer Vision , Image Processing , and Embedded Systems with a strong focus on healthcare applications including nutrition monitoring, mental health assessment, and driver safety systems. His most influential work examines computer vision applications for health monitoring, particularly food calorie measurement systems that use smartphone cameras to analyze nutritional content. His research has evolved to include EEG-based systems for ADHD detection and serious games for autism therapy, demonstrating a consistent trajectory toward practical healthcare solutions using advanced instrumentation techniques. Dr. Shirmohammadi maintains active collaborations with researchers including A. Yassine (118 joint publications), D. Ahmed, Ali Asghar Nazari Shirehjini, and B. Hariri. His publications appear primarily in IEEE Transactions on Instrumentation and Measurement, reflecting his strong connection to the instrumentation and measurement community.

Witold PedryczView profile

Professor

• Computational Intelligence
• Fuzzy Modeling
• Granular Computing
• +11 more

Witold Pedrycz serves as Professor and Canada Research Chair in Computational Intelligence within the Department of Electrical and Computer Engineering at the University of Alberta, Canada, and maintains affiliation with the Systems Research Institute of the Polish Academy of Sciences in Warsaw, Poland. His research expertise spans Computational Intelligence, fuzzy modeling, Granular Computing, knowledge discovery, data science, pattern recognition, knowledge-based neural networks, and control engineering, with additional exploration in Artificial Intelligence, Big Data, Data Engineering, Internet of Things, Complex Systems, and Software Engineering. Scientific Honors: IEEE Fellow (1998) Foreign member of the Polish Academy of Sciences (2009) Fellow of the Royal Society of Canada (2012) Norbert Wiener award (2007) IEEE Canada Computer Engineering Medal Cajastur Prize for Soft Computing Killam Prize Fuzzy Pioneer Award 2019 Meritorious Service Award Dr. Pedrycz holds editorial leadership as Editor-in-Chief of Information Sciences and WIREs Data Mining and Knowledge Discovery, Co-editor-in-Chief of the International Journal of Granular Computing and Journal of Data Information and Management, and serves on the Advisory Board of IEEE Transactions on Fuzzy Systems. The source material contains no details regarding his academic advising, research grants, laboratory affiliations, or educational background.

• Structural Health Monitoring (SHM)
• Smart / self-sensing cementitious composites
• Bridge engineering and life-cycle assessment
• +6 more

Filippo Ubertini is Professor of Civil and Environmental Engineering at the University of Perugia, Italy, where he coordinates the International Doctoral Programme in Civil & Environmental Engineering and represents the University inside the FABRE national bridge-research consortium. He leads the Structural Health Monitoring Laboratory ( SHM-Lab ) and is the primary contact for assignments linked to smart-infrastructure research. Education: While explicit degrees are not listed in the supplied text, his role as programme coordinator and full professor implies completion of a PhD and habilitation in Civil Engineering. Research focus: Ubertini’s work sits at the intersection of smart materials and data-driven infrastructure management . He develops self-sensing cementitious composites doped with carbon micro-fibers or graphene nano-platelets that can measure strain, cracking and moisture in real time, turning whole bridges and buildings into distributed sensors. Complementary research threads include low-cost acquisition electronics, UAV & InSAR remote sensing, Bayesian & adversarial machine-learning algorithms for damage detection, digital twins and life-cycle cost analysis of bridge networks. Publication trends (2024-2025): Roughly 30 peer-reviewed items per year concentrate on (i) AI-enhanced operational modal analysis and transfer-learning damage classification across bridge populations, (ii) experimental characterisation of 3D-printed and cast self-sensing concrete, (iii) full-scale validation on curved box-girder, masonry and railway bridges, and (iv) integration of satellite radar data with numerical collapse simulations to predict residual service life of landslide-affected viaducts. Scientific awards & recognition: No specific prizes or fellowships are mentioned in the provided text. Doctoral supervision & grants: The text does not enumerate individual students or funded projects; however, his coordination of an international PhD programme and numerous experimental campaigns imply sizeable supervisory and funding responsibilities. Laboratory & team: Ubertini heads the SHM-Lab at UniPg, maintaining facilities for material mixing, 3D concrete printing, electrical impedance tomography, UAV photogrammetry, and large-scale structural testing, while collaborating with the European FABRE consortium and multiple EU projects.

• New Product Development
• Knowledge Management
• Collaborative Work Environments
• +5 more

Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics

Joanna Cecilia da Silva SantosView profile

Assistant Professor

• Software Engineering
• Software Security
• Code Generation
• +4 more

Joanna Cecilia da Silva Santos is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame , where she leads the Security and Software Engineering research lab (S 2 E) . She earned her Ph.D. and M.Sc. in Computing and Information Sciences from Rochester Institute of Technology (RIT) and a B.Sc. in Computer Engineering from Federal University of Sergipe (UFS) . Research Interests: Her work focuses on the intersection of Software Engineering and Software Security , with specific emphasis on Code Generation , Program Analysis , Software Architecture , and Quantum Software Engineering . Recent projects include evaluating large language models for code generation, detecting regular expression denial-of-service vulnerabilities, and creating taint-based analysis tools for Java security. 2025: Code generation benchmarks, LLM performance in programming assignments 2024: Frameworks for secure code generation, ReDoS analysis, static analysis of deserialization 2023: GitHub Copilot complexity prediction, vulnerability characterization 2022: Transformer-based code smell detection, security evaluation datasets Scientific Awards: 2017 Best Paper Award at ICSA 2020 JOBS Workshop Research Pitch Competition Winner 2023 Distinguished Reviewer at ESEC/FSE 2014 CAPES Scholarship for Masters at RIT 2013 3rd Place Paper at XIII ERBASE Her research group engages in empirical studies of code vulnerabilities, automated security tools, and educational applications of language models, with funding reflected in multiple peer-reviewed publications.

Giuseppe DesoldaView profile

Associate Professor

• Human-Computer Interaction
• Usable Security
• End-User Development
• +4 more

Giuseppe Desolda is an Associate Professor at the Computer Science Department of the University of Bari Aldo Moro , where he has been since July 2, 2022. He leads research at the Interaction, Visualization, Usability & UX (IVU) Lab , focusing on Novel Interaction Techniques , Internet of Things development, and Usable Security . His work includes coordinating the PRIN PNRR DAMOCLES project (2022-2025) on human-centric cybersecurity and leading Work Package 1 of PNRR SERICS. PhD in Computer Science from University of Bari Co-author of over 110 publications Associate Editor for IEEE Access Journal Research interests span Human-Computer Interaction (HCI), End-User Development (EUD) for IoT, and Usable Security systems. His recent work explores AI-driven usability evaluation, voice-based 3D modeling, and GDPR-compliant software frameworks. Article trends show focus on phishing mitigation , smart environment customization , and privacy-by-design methodologies. Publications appear in TOCHI , FGCS , IJHCS , and BIT . Scientific achievements include: Selected for Heidelberg Laureate Forum (2019) LARE spin-off grant (EUR 50,000, 2013) He supervises PhD students Andrea Esposito and Francesco Greco, and has advised multiple funded research projects (PRIN DAMOCLES, DevProDev, PNRR SERICS). Teaching roles include courses on Human-Centered AI, IoT Security, and Web Programming across undergraduate and graduate programs.

Vittorio CurriView profile

Professor

• Optical Communications
• Optical Networks
• Multi-band Optical Networks
• +12 more

Vittorio Curri is a Full Professor in Optical Communications and Networking at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , Italy. He is a founding member of the OptCom Group and PhotonLab and leads the PLANET research team. His work spans optical network modeling, AI-assisted control, open-source software (GNPy), and environmental sensing via optical fiber. He has led numerous EU and industry-funded projects and is a key figure in open optical networking. Research Interests: Multi-band optical transmission in single-mode fibers Physical layer aware networking Machine learning and AI for optical network optimization Environmental sensing using optical network telemetry Open and disaggregated optical networks Digital twin development (GNPy project) WDM and coherent transmission modeling The recent publications reflect a strong trend toward integrating AI and machine learning with digital twin technologies for real-time network control, anomaly detection, and performance optimization. There is a clear focus on wideband, multi-band, and converged metro-access networks , with modeling efforts extending to filtering effects, polarization, and nonlinear impairments. The research is highly applied, with strong industry collaboration and open-source contributions. Scientific Awards: Concorso "Galileo Feraris" (2002) JLT Best Paper Award (2014, 2015) FFABR 2017 Research Grant Advising and Grants: Prof. Curri has supervised 25 PhD students and numerous postdocs. He has served as Principal Investigator on major projects including WON (EU H2020) , ALLEGRO , NESTOR , RESTART , SENSEI , and SCIPIO . He leads the GNPy open-source project under TIP and has extensive collaborations with Synopsys, Open Fiber, INFINERA, and CESNET. His research is funded by EU programs (Horizon Europe, H2020), PNRR, and multiple industrial contracts. Labs and Teams: He leads the PLANET (Physical Layer Aware NETworking) team, a subgroup of the OptCom Group at PoliTo. The team focuses on simulation, modeling, and AI-driven control of next-generation optical networks. They collaborate closely with the LINKS Foundation and international partners including Soochow University and CESNET .