Francesco Costantino is an Associate Professor at Sapienza University of Rome, affiliated with the Department of Computer, Management, and Control Engineering. He holds a PhD in Industrial Production Engineering (2005) and has been qualified as a Full Professor since 2018. Education: PhD in Industrial Production Engineering (2005), Master's in Quality Engineering and Management (2002), BS in Mechanical Engineering (2001), all from Sapienza University. His research focuses on digital innovation in production systems , lean and Six Sigma methodologies , supply chain management , and expert systems . Recent work explores applications in space manufacturing, cybersecurity, and virtual reality training. 2025 publications highlight large language models for accident analysis, smart manufacturing maturity , and human-machine reliability . 2024 contributions include models for hybrid agricultural vehicles , adaptive automation , and cyber-socio-technical systems .
Alberto De Santis is an Associate Professor in the Department of Computer, Automatic and Management Engineering A. Ruberti at the University of Rome La Sapienza, Faculty of Information Engineering, Computer Science and Statistics. He has maintained this position since 1998 in the sector ING-INF04 - Automatica, following his progression from researcher positions at both the National Research Council and the university's Department of Computer and System Engineering. His educational background includes a degree in Electronic Engineering from University of Rome La Sapienza (1984, with honors) and a Specialization in Control Systems and Automatic Computing Engineering (1985-86). His academic journey included a visiting scholar position at UCLA's School of Engineering and Applied Mathematics (1990-91) and research fellowships at the Institute of Systems Analysis and Informatics. Professor De Santis teaches Fundamentals of Automatic Control for Management Engineering undergraduate programs and Modeling and Identification for Master's degree students. His research spans theoretical and applied domains with particular emphasis on filtering and control theory, signal processing, and system identification. He's also a member of Continuous Optimization research group and since 2011 has been associated with the university spin-off ACTOR SRL focused on Analytics, Control Technologies and Operations Research. His recent publications (2022-2024) demonstrate remarkable interdisciplinary reach, connecting traditional control engineering with aerospace systems, nutrition science, healthcare optimization, and sports medicine. This reflects a research trajectory that has evolved from core control theory to practical applications across diverse fields including aircraft formation, sustainable diet planning, emergency department operations, and dietary supplement usage patterns. He maintains active academic engagement through regular teaching (with documented 2024/25 course schedules), ongoing research collaborations, and participation in university spin-off initiatives. His office is located in room A204 at the university's Department of Computer, Automatic and Management Engineering.
Simone Lenti is an Assistant Professor (Ricercatore RTDa) at the Department of Computer, Control, and Management Engineering of Sapienza University of Rome. He is an active member of the A.WA.RE research group , which specializes in visual analytics. Lenti obtained his Ph.D. in 2021 with a dissertation on visual analytics techniques for cybersecurity. His research bridges cybersecurity , visual analytics , and human-computer interaction , focusing on: Developing computational methods for vulnerability analysis (e.g., NLP for CVE relevance, smart contract taxonomies) Designing visual tools for threat detection (e.g., attack graphs, firmware fuzzing) Enhancing interpretability in data-driven systems (e.g., partial dependence analysis, process mining) Lenti's publications (2019–2025) demonstrate a consistent focus on applying visual analytics to cybersecurity challenges , with recent expansions into bioinformatics and education. Key trends include automated vulnerability management, human-centered explainability, and scalable threat modeling. Awards: IEEE VizSec 2018 Best Paper for contributions to cybersecurity visualization. He contributes to academic infrastructure through tools like easyDeclare (declarative process modeling) and BUCEPHALUS (business-centric cybersecurity analysis), emphasizing practical applications of his research.
Ksenia Morozova is a researcher at the Free University of Bozen-Bolzano's Faculty of Agricultural, Environmental and Food Sciences. Her work focuses on food chemistry and preservation, particularly antioxidant mechanisms in plant and dairy systems. Research Areas: Food chemistry, antioxidant analysis, lipid oxidation, and waste valorization Techniques: HPLC, NMR, calorimetry, and mass spectrometry Current Projects: Antioxidant extraction from agricultural by-products, oil stabilization, and food authentication Recent research demonstrates her expertise in advanced analytical methods for food quality assessment, with publications in 2025 covering HPLC analysis of Salvia extracts, NMR-based spice authentication, and isothermal calorimetry for oxidation kinetics. She has also explored supercritical CO2 extraction applications and Maillard reaction products as preservatives. Her 2024-2025 publications reveal a strong focus on food authenticity verification (saffron, hay milk), oxidation inhibition mechanisms, and innovative oil structuring techniques for food applications. Current collaborations include VOG Products and University of Zurich researchers.
Marco Reale serves as a Research Fellow within the Department of Physics and Chemistry at the University of Palermo, specializing in advanced nanophotonic systems and carbon-based nanomaterials. His academic activities span teaching core physics courses and conducting cutting-edge research in optical phenomena at the nanoscale. His research program centers on: Quantum dot superparticles and wavelength-tunable lasing mechanisms Carbon nanomaterial engineering for photoluminescence enhancement Random lasing phenomena in disordered systems Ultrafast photophysics of distorted nanographenes Hybrid optical structures using nanocarbons Analysis of his 13 recent publications (2022-2025) reveals a dominant focus on carbon nanomaterials (quantum dots, nanographenes) for lasing applications, with significant contributions to understanding surface interactions, plasmonic effects, and femtosecond-scale photophysical processes. His work bridges fundamental nanophotonics with practical applications in optical labeling, random number generation, and energy conversion. Teaching responsibilities include Physics II (6 CFU) for Robotics Engineering students and Physics Applied to Nutrition (2 CFU) for Dietitian training. Office hours are held Mondays 3:00-5:00 PM at the Department of Physics and Chemistry (Via Archirafi 36), or by appointment via the student portal.
Carlo Minganti serves as an Associate Professor in the Department of Human and Health Motor Sciences at the University of Rome 'Foro Italico', with significant institutional responsibilities including: Membership in the University Quality Committee Service on the Board for the Degree Course in Preventive and Adaptive Motor Activities (LM67) Participation in the University Scientific Research Commission He teaches in both the Bachelor's Degree in Exercise and Sport Sciences (Class L22) and Master's Degree in Sport Science and Technology (Class LM68). Professor Minganti's research program centers on: Training Control and monitoring methodologies Sports Performance Evaluation systems Statistical data management for sports applications His work integrates Sports Science, Exercise Physiology, and Biomechanics to address aging-related motor decline, exercise-induced hormonal responses, competition stress biomarkers, and post-injury movement rehabilitation. Analysis of his 2020-2022 publications reveals a strong interdisciplinary trajectory: Rhythmic movement studies in aging populations with complexity-based task design Dihydrotestosterone dynamics during maximal aerobic exercise Cortisol/amylase stress responses differentiating training versus competition Biomechanical alterations in ACL-reconstructed athletes at return-to-sport These works consistently employ advanced statistical analysis and feature international collaborations. Scientific awards: None documented in available sources. As an active educator and researcher, Professor Minganti supervises students through formal degree programs while contributing to institutional research strategy via the Scientific Research Commission. His data-intensive approach provides students with hands-on experience in empirical sports science methodology and statistical analysis. Prospective collaborators should note his expertise in bridging physiological monitoring with performance outcomes. Though no dedicated laboratory name is specified, his research group operates within the Department of Human and Health Motor Sciences, focusing on empirical projects requiring motion analysis, biomarker collection, and computational data processing in sports contexts.
Sara A. Solla is a Professor of Physics and Neuroscience at Northwestern University, conducting interdisciplinary research that bridges statistical physics and computational neuroscience. Her work applies theoretical frameworks from physics to model complex neural systems and cognitive processes. Her core research areas include: Theoretical neural network modeling using spin-glass systems for associative memory Statistical mechanics of supervised and incremental learning algorithms Emergence of generalization capabilities in adaptive systems Computational approaches to sensory processing and motor control Professor Solla's significant contributions have been recognized through prestigious honors: Election as Fellow of the American Physical Society Membership in the American Academy of Arts and Sciences She maintains active professional engagement through memberships in the Society for Neuroscience, New York Academy of Sciences, and Society for the Neural Control of Movement, reflecting her commitment to advancing interdisciplinary neuroscience research.
Matteo Dellacasagrande serves as a Researcher at the Department of Mechanical, Energy, Management and Transport Engineering (DIME) within the Polytechnic School of the University of Genoa. His academic appointments include membership on the Joint Teacher-Student Commission and teaching responsibilities for advanced courses in aircraft propulsion systems. His research focuses on fluid dynamics in turbomachinery , particularly low-pressure turbine optimization, separated flow modeling, and aircraft engine design. Key methodologies include computational fluid dynamics, experimental validation using large databases, and statistical modeling techniques like Bayesian Lasso for flow prediction. His work bridges theoretical fluid mechanics with practical aerospace engineering applications. Recent publications demonstrate consistent focus on turbine blade aerodynamics (2024-2025), with significant contributions to loss mechanism analysis in low-pressure turbines and novel approaches to modeling separation bubbles. His research integrates experimental data with advanced statistical methods to improve prediction accuracy in complex flow scenarios. Teaching activities: AIRCRAFT ENGINES (Master's Degree in Mechanical Engineering - Energy and Aeronautics) AIRCRAFT PROPULSION (Master's Degree in Mechanical Engineering - Energy and Aeronautics) DESIGN OF MACHINES AND ENERGY SYSTEMS Professional engagement: Member of the Joint Teacher-Student Commission at the Polytechnic School, with office hours by appointment via institutional email.
Jacopo Endrizzi serves as a Research Fellow within the Department of Industrial Engineering at the University of Trento, located at Via Sommarive, 9 - 38123 Povo. His research spans core domains of Industrial Engineering with emphasis on: Mathematical optimization in production systems Logistics network design Statistical process control Resource allocation modeling Lean manufacturing methodologies Stochastic inventory systems No scientific awards or student advisement records are documented in available sources. Current research focuses on operational efficiency frameworks within manufacturing contexts, though specific grant details remain unreported.
Songqun Gao serves as a Research Fellow in the Department of Industrial Engineering at the University of Trento, Italy, with institutional address at Via Sommarive, 9 - 38123 Povo, Trento. His research spans critical domains of Industrial Engineering, characterized by: Operations Research methodologies Supply Chain Optimization frameworks Advanced Manufacturing Systems design Statistical Quality Control techniques Logistics and Distribution Network analysis Production Systems efficiency modeling This work emphasizes quantitative approaches to industrial process improvement, integrating mathematical modeling and systems analysis for real-world operational challenges.
