Matteo Sonza Reorda is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Automatic Control and Computer Science (DAUIN). He holds roles such as Partnership Agreement Coordinator with SMAT and has served as Vice-Rector for Research (2021–2024). His research focuses on fault tolerance, hardware reliability, and AI acceleration, with contributions to GPU/CNN reliability, self-test libraries, and defect-oriented testing. Education: M.S. in Electronics Engineering, Politecnico di Torino (1986) Ph.D. in Computer Engineering, Politecnico di Torino (1990) Research Interests: His work spans automatic test equipment, circuit reliability, GPU fault tolerance, neural network hardening, and embedded systems safety . He leads the Electronic CAD & Reliability Group and collaborates with institutions like the ISI Foundation and the National Research Council (CNR). Publications & Impact: With over 180 publications, his recent work emphasizes AI accelerator reliability, fault injection techniques, and safety-critical systems. Key trends include GPU resilience for CNNs, self-test library optimization, and radiation fault modeling in neural networks. Awards & Recognition: IEEE Fellow (2016–) Multiple best-paper awards at IEEE conferences (DDECS, DATE, etc.) Grants & Collaborations: Coordinator of EU projects (RESCUE, TUTORIAL) Partnerships with EDF, Marelli Europe, and SMAT Lead on National HPC/Quantum Computing Spoke 1 (2022–2025) Labs/Teams: Leads the CAD Group and collaborates with the French-Italian LIA LAFISI lab on hardware-software integration.
Corrado De Sio is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN) , Politecnico di Torino , affiliated with the College of Computer, Film, and Mechatronics Engineering . His academic roles include course instruction and collaboration for Reconfigurable Computing , High Performance Computing (HPC) , and Operating Systems for High-Performance Supercomputers across multiple academic years (2020-2025). Research Interests focus on: Reliability of reconfigurable systems and FPGAs under radiation effects Hardware-software co-design for fault tolerance Embedded systems in aerospace and safety-critical applications Machine learning acceleration on reconfigurable hardware Radiation effects on real-time operating systems and CNN implementations Recent publications address: 2025: Selective hardening of RISCV soft-processors for space applications 2025: Real-time 'signal for help' gesture recognition systems 2024: Reliability analysis of RISC-V processors and CNN placement algorithms 2023: Fault tolerance in FPGA-based CNNs and radiation effects on RTOS Patents include: PyXEL - Python Toolkit for Reconfigurable Hardware Surveillance Software for Real-Time Violence Detection Academic Supervision : Co-supervisor for PhD candidate Arash Amini Bardpareh in Computer and Systems Engineering .
Daniele Ielmini is a Professor at the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy, where he leads research in non-volatile memory technologies and neuromorphic computing. He received his Laurea (with merit) and Ph.D. in Nuclear Engineering from Politecnico di Milano in 1995 and 2000, respectively, and has held visiting positions at Intel Corporation (2006), Stanford University (2006), and the University of Illinois at Urbana-Champaign (2010). His research focuses on the modeling and characterization of non-volatile memories, including nanocrystal memory, charge trap memory, phase change memory (PCM), resistive switching memory (RRAM), and spin-transfer torque magnetic memory (STT-MRAM). He has co-edited the book 'Resistive switching – from fundamental redox-processes to device applications' and published over 300 papers with more than 10,000 citations and an H-index of 69 (Scopus, September 2023). Prof. Ielmini's recent publications demonstrate a strong trend toward in-memory computing and neuromorphic applications, with particular emphasis on closed-loop analog computing architectures, reservoir computing with 2D materials, and hardware security implementations using emerging memory technologies. His work bridges fundamental device physics with practical computing applications, especially for energy-efficient AI acceleration. Intel Outstanding Researcher Award (2013) ERC Consolidator Grant (2014) IEEE-EDS Paul Rappaport Award (2015) Fellow of the IEEE Prof. Ielmini leads multiple ERC-funded projects including SHANNON (Secure Hardware with Advanced Nonvolatile memories), NEURO2D (neuromorphic systems based on reservoir computing in MoS2), and ANIMATE (closed-loop in-memory computing). His research group includes post-doctoral researchers, PhD students, and M.Sc. students working on various aspects of emerging memory technologies and their applications. He serves as Associate Editor for IEEE Trans. Nanotechnology and Semiconductor Science and Technology (IOP), and has served in several Technical Subcommittees of international conferences including IEEE-IEDM, IEEE-IRPS, and IEEE-ISCAS. His laboratory at Politecnico di Milano is equipped with advanced semiconductor device testing equipment including probe-stations, semiconductor parameter analyzers, high-speed waveform generators, and other specialized instruments for nano-electronic research. The lab collaborates with major semiconductor companies including Micron Technology Inc. and STMicroelectronics, as well as participating in national and international research projects.
Gianfranco Chicco is a Full Professor at the Politecnico di Torino , Italy, within the Department of Energy (DENERG). He serves as Scientific Director of the Electrical Power Systems research group and the Turin unit of the ENSIEL Consortium. A Fellow of IEEE (since 2018), he has held editorial leadership roles as Editor-in-Chief of Sustainable Energy, Grids and Networks and Subject Editor of Energy , while chairing major conferences like IEEE ISGT Europe 2017 and UPEC 2020. Education : Laurea (cum laude) in Electrical Engineering (1987), Ph.D. in Electrical Engineering (1992), Doctor Honoris Causa (2017, Polytechnic University of Bucharest; 2018, Technical University 'Gheorghe Asachi' of Iasi). Research Interests : Focus on power transmission and distribution systems , distributed energy resources , and multi-energy smart grids , with applications in artificial intelligence , load management , and power quality . His work addresses technical, economic, and environmental aspects of distributed generation and smart grid sustainability . Publications Trends : Recent articles emphasize photovoltaic power optimization , dynamic grid modeling , and multi-energy system coordination , reflecting expertise in renewable integration , clustering algorithms , and adaptive control . Key subfields include voltage stability , load forecasting , and blockchain for energy trading . Awards : IEEE Fellow (2018-) Best Paper Awards at SEST (2018, 2020) Doctor Honoris Causa (2017, 2018) 'Giancarlo Vallauri' Degree Prize (1988) Advising and Grants : Supervises PhD students in power converters , renewable integration , and high-voltage measurement methodologies . Leads European projects like H2020 MIGRATE and OSMOSE, focusing on grid resilience , clustering-based network planning , and multi-energy sustainability .
Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.
Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.
Matteo Brunelli is Associate Professor of “Mathematical Methods of Economics and Actuarial and Financial Sciences” at the University of Trento , Department of Industrial Engineering, and Adjunct Professor (docent) at Lappeenranta University of Technology , Finland. He is nationally habilitated as Full Professor in Italy and has held long-term visiting positions at Berkeley, Turku, Auckland, JAIST and Binghamton. Education: Ph.D. (Doctor of Science) in Information Technologies, Åbo Akademi University, Finland, 2011 – graded Eximia cum laude approbatur M.Sc. in Economics, University of Trento, 2007 – grade 110/110 cum laude B.Sc. in Economics, University of Trento, 2005 Research focus: Brunelli’s work sits at the intersection of multi-criteria decision analysis , operations research and computational optimisation . He develops axiomatic foundations and algorithms for pairwise comparison matrices , consistency indices , the best-worst method and fuzzy preference relations , and applies them to energy planning, sustainable inventory, maintenance scheduling, 3-D printer selection, and blockchain governance. His 2023-2025 articles reveal intensified interest in uncertainty modelling (Dempster-Shafer theory), bi-objective optimisation of inventory and maintenance, and group decision protocols that integrate probabilistic or active-learning components, demonstrating both methodological depth and practical relevance. Scientific awards & grants: Academy of Finland Postdoctoral Researcher grant (€254 670, 2014-2017) Claudio Dematté Research Grant (€19 000, 2008) Teacher of the Year Award, Aalto University (2013 – both Spring & Autumn semesters) Bernard Roy Award 2021 for outstanding contribution to Multiple Criteria Decision Aiding (under-40 category) Supervision & funding: While specific doctoral students are not listed, Brunelli currently supervises graduate theses at Trento and has continuously held competitive national grants. His Academy of Finland project “Consistency of valued preference relations for decision analytics methods” financed three years of full-time research and international collaboration. Editorial & community roles: He serves on the editorial boards of International Journal of General Systems and Mathematical and Computational Applications , and acts as area editor for Journal of Multi-Criteria Decision Analysis , positioning him among the key gatekeepers of the MCDA community.
Alexia Delfino serves as Assistant Professor in the Department of Economics at Bocconi University, with affiliations spanning CEPR DEV & OE, J-PAL, IZA, IGIER, LEAP, CESIfo, and BAFFI. She maintains a dual research presence as Visiting Research Fellow at STICERD. Her academic foundation includes a PhD in Economics from the London School of Economics (2020). Delfino operates at the intersection of Development, Organizational, and Behavioral Economics, employing experimental and survey methodologies to investigate how social norms, institutions, and identity shape labor market disparities and organizational productivity. Her fieldwork spans both developed and developing economies, with particular emphasis on gender dynamics in entrepreneurship and workplace culture. Recent projects examine trauma's impact on economic decision-making and value alignment in corporate environments. Her publication trajectory reveals a consistent focus on gender economics and institutional analysis, with increasing methodological sophistication in field experiments and cross-national comparisons. The 2024-2025 publications demonstrate expansion into historical data analysis and team dynamics while maintaining core themes of gender barriers and entrepreneurial ecosystems. Recognition includes: UniCredit Foundation Best Paper Award on Gender Economics (2021) Research funding reflects policy relevance through partnerships with major development institutions: J-PAL Global Economic Affairs and Policy & Performance Evaluation Innovations for Poverty Action (IPA) Exploratory and Research Grants LEAP and Weiss Fund support for gender-focused field experiments IGA-Rockefeller Research and Impact Fund for trauma economics research She leads international collaborations examining reskilling interventions in Italy, lactation infrastructure in Kenya, and teenage job experimentation in Switzerland, demonstrating strong cross-institutional research networks with Harvard, LSE, and World Bank affiliates.
Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.
Marco Pirola is a Full Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin, Italy. He is a member of the Interdepartmental Center 'CleanWaterCenter@PoliTo' and actively contributes to research in high-frequency electronics and microwave engineering. His work focuses on power amplifiers, device characterization, and advanced microwave circuit design. Research Interests: Microwave power devices, GaN technology, 5G/mm-Wave applications, space communications, and smart pipeline monitoring systems. Awards: IEEE Fellow (since 2019), IEEE Senior Member. Recent Publications address topics like Ka-band MMIC amplifiers for SAR systems, broadband Doherty amplifiers using GaN, and harmonic analysis of current-mode power stages. His projects include STARGATE (European GaAs power architectures) and Millimetre-Wave GaN Radar for UAV detection. Teaching: He leads courses on 'Radio Frequency Integrated Circuits' and 'Advanced Devices for High Frequency Applications' at the Polytechnic University of Turin. Supervised PhD students include Wenjun Zhang and Abbas Nasri, who worked on III-V HEMT circuits and GaN power amplifiers.
Giuseppe Bruno Averta is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is affiliated with the College of Computer, Film and Mechatronics Engineering and contributes to national and international research in artificial intelligence and robotics. Averta has held a Visiting Researcher position at the Massachusetts Institute of Technology (MIT) from January to June 2019. His research interests include Computer Vision, Deep Learning, Robotics, Neural Architecture Search, Egocentric Vision, Embodied Intelligence (Edge/Tiny ML), and Human-Robot Collaboration . His work is aligned with ERC sectors in Artificial Intelligence, Machine Learning, and Robotics, and contributes to UN SDGs such as Good Health and Well-being, Industry Innovation and Infrastructure, and Responsible Consumption and Production. The recent publication trends highlight his focus on vision-language models (e.g., CLIP), egocentric action recognition, efficient neural architectures (e.g., BiSeNet, MaskFormer), and robust deep learning. His research bridges theoretical advances with practical robotics applications, including grasping and manipulation. Scientific Awards and Recognitions: Georges Giralt PhD Award (euRobotics AISBL, 2021) Wiley Best Reviewer (Wiley, Italy, 2021) Best Paper Award, ICUMT 2015 (2017) Fellow, ELLIS Network of Excellence (2022–) Fellow, DAAD AInet (2022–) DAAD AInet Fellowship Advising and Grants : Averta supervises multiple PhD students in the Artificial Intelligence and Computer and Systems Engineering doctoral programs at Politecnico di Torino. He is involved in teaching at both the master’s and doctoral levels, including courses on Robot Learning and Machine Learning and Deep Learning. He is also a co-inventor on a national and international patent for a method and algorithm for the automatic design of neural networks through machine learning, indicating active research funding and innovation. Labs and Research Groups : He is a member of the SmartData@PoliTO center and contributes to research in the VANDAL PoliTO lab (as indicated by his student Davide Buoso). His work is deeply integrated with teams working on egocentric vision, embodied AI, and neural architecture search.
Andrea Santilli is a Research Scientist at Nous Research and holds a PhD in Computer Science from GLADIA at Sapienza University of Rome. His research focuses on large language models (LLMs), robustness, reliability, and multimodal learning. He previously worked at Apple MLR, Hugging Face’s BigScience, and Pi School. He earned his MSc and BSc in Computer Science from Tor Vergata University and Sapienza. Education: PhD in Computer Science, Sapienza University of Rome (2024) MSc in Computer Science, University of Roma Tor Vergata (2020) BSc in Computer Science, University of Roma Tor Vergata (2018) Research Interests: Santilli’s work spans LLM robustness , mechanistic interpretability , multimodal neural databases , and instruction-tuning . He introduced Parallel Jacobi Decoding and contributed to projects like BLOOM, Camoscio, and Fauno. His research bridges syntax-aware NLP, privacy-preserving LLMs, and cross-modal alignment. Publications: His work includes advancements in 3D-text latent space alignment (CVPR 2025), evolutionary merging (ICML 2025), and efficient decoding (ACL 2023). Over 15+ peer-reviewed papers span venues like ACL, CVPR, and ICLR. Awards: Received the Emanuele Pianta Award for his MSc thesis on continual language learning with syntax-based episodic memory. Grants & Projects: Winner of ‘Machine Learning Algorithms for Translation’ grant (2022), developing Parallel Decoding Co-PI for ‘Multimodal AI for 3D Analysis’ (2021) with Ecole Polytechnique Labs & Teams: Active in GLADIA (Sapienza), Apple MLR, and Hugging Face’s BigScience initiative. Core contributor to open-source projects like PromptSource and BLOOM.
Damiano Piovesan is Associate Professor in Bioinformatics (SSD BIO/10) at the Department of Biomedical Sciences , University of Padua , Italy. Since March 2022 he has held this rank, having previously served as Assistant Professor (2022) and PostDoc researcher (2019) in the same department. Education 2013 – PhD in Biotechnology, Pharmacology and Toxicology, University of Bologna 2009 – MSc in Bioinformatics, University of Bologna 2007 – BSc in Biotechnology, University of Bologna Research Focus Piovesan’s research integrates machine-learning approaches with structural bioinformatics to advance understanding of intrinsically disordered proteins (IDPs) and protein function prediction . He develops widely used resources such as MobiDB for disorder annotation, DisProt for functional curation of disordered regions, and RING for residue interaction networks. Additional interests include tandem repeat proteins , cancer-related IDP targets , and community benchmarking initiatives (CAFA, CAID, CAGI). Publication Trends His 2024–2025 output is dominated by updates to flagship databases ( InterPro , DisProt , MobiDB ), next-generation disorder predictors leveraging deep learning ( PredIDR , MobiDB-lite 4.0 ), and large-scale genomics challenges ( CAGI6 ). Across the decade, recurring themes include methodological advances in disorder prediction, creation of interoperable bioinformatics platforms, and rigorous benchmarking to ensure community-wide reliability. Scientific Awards No specific awards are listed in the provided materials. Advising & Grants No individual students or grant details are explicitly supplied; however, his leadership in multi-institutional consortia (e.g., InterPro, DisProt, CAFA) implies substantial supervisory and funding coordination roles. Labs & Teams Piovesan is affiliated with the BioComputingUP Lab ( https://biocomputingup.it/ ) at the University of Padua, a hub for computational biology and bioinformatics tool development.
Roberto Garello is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino . He specializes in Communication Systems , Satellite Networks , and Channel Coding , with a focus on 5G/6G Technologies and Non-Terrestrial Networks . His work aligns with the School of Master’s Programmes and Lifelong Learning . Research Interests: Satellite communications systems, Direct-to-Satellite IoT constellations, Mega-constellation services in space, and physical layer advancements for 5G/6G. Teaching: Offers courses like Information Theory for Data Science , Communication and Network Systems , and Space Exploration and Resources , while supervising Applied Signal Processing Laboratory . Projects: Leads initiatives such as DitDSSS (satellite localization), RESTART (future telecommunications), and TESL@ (ICT energy efficiency). Scientific Awards: Received Best Paper Awards at CTRQ 2010 and COCORA 2013. Students: Supervises PhD candidates including Alessandro Compagnoni, Agbotiname Lucky Imoize, and Riccardo Tuninato, focusing on topics like Wireless Communication, Machine Learning, and Non-Terrestrial Networks. Publications: His recent work explores OTFS vs. OFDM, spectrum sensing algorithms, MIMO with cylindrical arrays, and 5G NTN synchronization, reflecting trends in satellite IoT and machine learning integration.
Andrea Passerini is a Full Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy, where he also serves as Coordinator of the PhD programme in Information Engineering and Computer Science (Ministerial Decree 45/2013). His academic footprint spans multiple departments including Mathematics, Sociology, Cellular Biology, and Industrial Engineering, reflecting deep interdisciplinary engagement across computational sciences and life sciences. His research centers on Machine Learning and Data Mining with specialized expertise in Neuro-Symbolic AI , Probabilistic Reasoning , and Statistical Relational Learning . He pioneers methods for graph-based learning, medical AI applications, and explainable systems, with significant contributions to bioinformatics (particularly RNA-protein interactions) and healthcare diagnostics. His work bridges theoretical rigor with practical implementations in critical domains. Analysis of his 2025 publications reveals dominant trends in neuro-symbolic integration for graph data, human-AI collaboration in medical decision-making, and robust recommender systems. His research increasingly focuses on interpretable AI for high-stakes applications like surgical planning and physician support, while advancing foundational techniques in graph neural networks and concept-based modeling. As PhD programme Coordinator, Professor Passerini mentors doctoral candidates across AI and computer science disciplines. His collaborative network extends to medical researchers at CIBIO (Cellular, Computational and Integrative Biology department) and industrial partners, though specific lab structures aren't documented in available materials. Current projects emphasize medical AI validation, temporal network modeling, and LLM integration with structured reasoning frameworks.
