جست‌وجوی استاد و پژوهشگر

Christian Micheloniمشاهده پروفایل

دانشیار

• Pattern Recognition
• Active Vision
• Neural Networks
• +۳ مورد دیگر

Christian Micheloni is an Associate Professor at the University of Udine's Department of Mathematics and Computer Science. He holds a Laurea (cum Laude) and Ph.D. in Computer Science from the University of Udine (2002 and 2006 respectively). His research focuses on Active Vision, Pattern Recognition, and Resource Aware Networks. He has been involved in European projects like MUSAS (2008-2010) and HAMLet (2006-2008), and collaborates with international research centers and industry. Key research areas include person re-identification using neural networks, trajectory analysis, and camera network optimization. He has received the Best Paper Award at the International Conference on Distributed Smart Cameras (2014) and serves as an editor for the IEEE Journal of Selected Topics in Signal Processing. His work emphasizes real-time surveillance systems and adaptive sensor networks to manage computational and power constraints. Micheloni teaches courses like Artificial Vision and advises post-doctoral researchers. He maintains an active lab (AVires Lab) and offers post-doctoral positions. His publications span journals like IEEE Transactions on Pattern Analysis and Machine Intelligence, and conferences such as CVPR and ICCV.

Gigliola Vagliniمشاهده پروفایل

استاد

• Distributed Systems Verification
• Model Checking
• Machine Learning Applications
• +۲ مورد دیگر

Gigliola Vaglini is Full Professor of Computer Engineering at the University of Pisa's Department of Information Engineering. She teaches Software Systems Engineering and Databases, with research focusing on formal specification and verification of concurrent/distributed systems. Her work integrates model checking methodologies with machine learning techniques for industrial anomaly detection and mobile security applications. She has participated in multiple research projects funded by the Italian Ministry of University and Research, National Research Council, and European Community. Research Focus: Vaglini's work bridges theoretical computer science and practical applications, developing verification frameworks for complex systems while creating AI solutions for real-world problems. Her current investigations span swarm intelligence coordination, structural monitoring via digital twins, and multimodal deep learning architectures. Recent publications demonstrate cross-disciplinary approaches combining formal methods with machine learning, particularly in environmental monitoring, structural engineering, and neural architecture design. This reflects a consistent pattern of translating theoretical computer science concepts into applied technological solutions.

Vito Andrea Racanelliمشاهده پروفایل

پژوهشگر

• Control Systems
• Autonomous Systems
• Robotics
• +۳ مورد دیگر

Vito Andrea Racanelli is a Researcher at the Department of Electrical and Information Engineering, Politecnico di Bari, Italy. He holds a PhD in Control Engineering (2025) and a cum laude Master's degree in Control Engineering (2021). His research focuses on control strategies for autonomous systems, including industrial vehicles, UAV swarms, and adaptive video streaming. He is affiliated with the Control Engineering and Computer Science Laboratory (C3Lab), collaborating on robotics and control theory projects. Education: Bachelor/Master: Politecnico di Bari (2016–2021), Thesis: 'Autonomous Driving Systems: The AGV's Case' PhD: Politecnico di Bari (2021–2025), Focus: Model Predictive Control, Networked Systems, and Autonomous Mobile Robots Research interests span Model Predictive Control (MPC), decentralized coordination of UAV swarms, fault-tolerant industrial automation, and medical technology applications (e.g., insulin delivery systems). His work bridges control theory with real-time systems, emphasizing safety and adaptability in dynamic environments. His publications highlight advancements in MPC-based video streaming optimization, event-triggered consensus algorithms for live streaming, and GAN-based depth reconstruction for mmWave sensors. He has presented at top conferences like IEEE CCNC, IFAC SAFEPROCESS, and ICUAS. Advising/grants: No formal advisees listed. Collaborates on C3Lab projects funded by EU and national initiatives in robotics and control systems. Labs/Teams: Active member of C3Lab, contributing to interdisciplinary research in robotics, networked control, and AI-driven systems.

• Artificial Intelligence
• Semantic Web
• Machine Learning
• +۲ مورد دیگر

Eugenio Di Sciascio is a Full Professor and Scientific Coordinator at Politecnico di Bari. His research spans artificial intelligence, semantic web technologies, machine learning, and explainable AI, with applications in recommender systems, healthcare, and cybersecurity. As evidenced by 413+ publications, his work frequently bridges theoretical computer science with practical implementations. Recent research trends focus on trustworthy AI systems, particularly in healthcare diagnostics and recommendation security. His 2024-2025 publications demonstrate strong emphasis on explainable AI methodologies in medical applications (e.g., BRAINEX for brain age prediction, MORIX for mortality inference) and adversarial robustness in recommender systems. Additional work explores neurotechnology interfaces and semantic web foundations.

Raffaele Carliمشاهده پروفایل

دانشیار

• Control Systems Engineering
• Energy Systems Management
• Industrial Automation
• +۴ مورد دیگر

Prof. Raffaele Carli is an Associate Professor in Systems and Control Engineering at Politecnico di Bari, Italy. He holds a PhD in Electrical and Information Engineering (2016) and has been qualified as a Full Professor since 2023. His roles include technical lead of the Decision and Control Laboratory (DCLAB) and Vice-Coordinator of the National PhD program in Autonomous Systems (DAuSy). He has extensive editorial roles, including Associate Editor for IEEE Transactions on Automation Science and Engineering and IEEE Transactions on Systems, Man, and Cybernetics. Education: Laurea (Master’s) in Electronic Engineering (2002), PhD in Electrical and Information Engineering (2016), both from Politecnico di Bari. Professional experience includes roles as a System Engineer in the defense sector (2004–2012) and military service as a Reserve Officer (2003–2004). Research focuses on decision and control techniques for energy systems, industrial automation, and complex systems. Key areas include smart grids, energy communities, robotics, and optimization. Recent work emphasizes distributed control for renewable energy integration, human-robot collaboration, and sustainable manufacturing. Publications span 120+ international articles in journals like IEEE Transactions and conferences such as CDC and CASE. His research trends include game-theoretic control, MPC applications, and energy system optimization. Awards include the 2024 IEEE Italy SMCS Chapter Award and recognition for editorial contributions. Advising 8 current PhD students and supervising 7 past candidates. Active in organizing international conferences (e.g., General Chair of SENSYS 2025). Grants include projects on energy communities and smart city technologies funded by the Apulia Region. Labs include the Decision and Control Laboratory (DCLAB), focusing on automation, energy systems, and industrial applications. Collaborations with global institutions like TU Delft, UPC Barcelona, and Chinese Academy of Sciences.

Graziana Cavoneمشاهده پروفایل

استادیار

• Decision Support Systems
• Modeling and Control of Complex Systems
• Transportation Systems Optimization
• +۴ مورد دیگر

Graziana Cavone is an Assistant Professor in Systems and Control Engineering at the University Roma Tre. She holds a Ph.D. in Electronic and Information Engineering from the University of Cagliari and is qualified as an Associate Professor in Automatica. Her research focuses on decision support systems, transportation networks, energy systems, and industrial automation, with expertise in Model Predictive Control (MPC), Petri Nets modeling, and resilient infrastructure design. Education: Ph.D. (Excellent with Honors), Electronic and Computer Engineering, University of Cagliari (2018) Master’s (Summa Cum Laude), Control Engineering, Polytechnic of Bari (2013) Research Interests: Optimization of intermodal transport terminals and railway networks Energy-efficient building management and microgrids Cyber-physical systems in Industry 4.0 Resilient critical infrastructure control Human-robot collaboration and safe ergonomics Grants & Leadership: Principal Investigator for a National Natural Science Foundation of China grant (2020–2021) Recipient of multiple RTD-B and research fellowships in control systems and automation Organizer of international conferences like IEEE CASE 2024 and MED 2021 Labs & Collaborations: Member of the Decision and Control Laboratory at University Roma Tre Collaborations with institutions like Delft University of Technology and Southwest Jiaotong University Industry partnerships with Enel, Fiat Chrysler Automobiles, and Elettric80

Arcangela Ragoمشاهده پروفایل

استادیار

• Telecommunications
• Machine Learning
• 6G Systems
• +۱ مورد دیگر

Arcangela Rago is a Tenure Track Assistant Professor at the Department of Electrical and Information Engineering, Polytechnic University of Bari. She specializes in telecommunications engineering with a focus on 6G systems, non-terrestrial networks, and AI integration. Education: Obtained M.Sc. in Telecommunications Engineering (with honors) and Ph.D. in Electrical and Information Engineering from Polytechnic University of Bari. Research Interests: Her work explores the integration of terrestrial and non-terrestrial networks, 6G communication systems, and machine learning applications in telecommunications. Current projects focus on AI-driven network optimization, drone-assisted emergency systems, and sustainable network architectures. Publication Trends: Recent articles demonstrate strong focus on 6G network integration, AI applications in telecommunications, and hybrid terrestrial-satellite systems. Research shows increasing emphasis on practical implementations for smart agriculture, disaster management, and multimedia services. Awards: Best Workshop Paper at ICT-DM'23 (2023) Best Workshop Paper at ISCC: NGMSE2024 (2024)

• Artificial Intelligence
• Optimization Techniques
• Reinforcement Learning
• +۲ مورد دیگر

Michele Ciavotta is an Associate Professor at the University of Milano-Bicocca's Department of Computer Science, Systems, and Communication, specializing in AI-driven optimization for complex systems. His research integrates reinforcement learning, graph neural networks, and metaheuristics applied to distributed computing and physical systems like smart mobility and production lines. Research spans cloud/edge computing optimization, industrial production systems, smart city applications, and graph-based learning methods. Recent publications demonstrate focus on decentralized AI systems, geospatial data processing, and hypergraph neural networks for chemical and urban applications. Extensive involvement in European R&D projects addresses challenges in cloud computing infrastructure, Industry 4.0 implementations, and distributed AI solutions.

Antonio Pellicaniمشاهده پروفایل

پژوهشگر ارشد

• Data Mining
• Bioinformatics
• Social Network Analysis
• +۴ مورد دیگر

Antonio Pellicani is a Research Fellow at the Department of Computer Science, University of Bari Aldo Moro (Italy). He holds a PhD in Computer Science and Mathematics from the same institution, completed in 2024 under the supervision of Prof. Michelangelo Ceci. Research Interests: Bioinformatics Time Series Analysis Social Network Analysis Anomaly Detection Process Mining Data Mining His recent work focuses on hybrid computational approaches for analyzing complex data types, including microRNA expression data for disease biomarker discovery and cryptocurrency time series for anomaly prediction. Publications span high-impact journals like Knowledge-Based Systems and Information Fusion , with applications in cybersecurity and biomedical informatics. Laboratory Affiliation: KDDE lab (Knowledge Discovery and Data Engineering) at the University of Bari. International Collaboration: Visiting student at Jožef Stefan Institute’s Knowledge Technologies Department (2023).

Annunziata D'Aversaمشاهده پروفایل

پژوهشگر ارشد

• Time Series Forecasting
• Nowcasting
• Big Data Analytics
• +۱ مورد دیگر

Annunziata D'Aversa is a Research Fellow and PhD student in the Department of Computer Science at the University of Bari Aldo Moro, specializing in energy sector forecasting models. Her work focuses on developing incremental update methodologies for time-sensitive data streams in electricity networks and renewable energy systems. She earned her Master's degree in Data Science from the University of Bari Aldo Moro in July 2021 with full marks and honors, completing a thesis on spatial autocorrelation modeling for energy consumer forecasting in electricity networks. Her research interests include Time Series Forecasting, Nowcasting, Big Data Analytics, and Neural Networks, with emphasis on spatial-temporal pattern recognition for energy applications. She develops adaptive models that process real-time data streams for grid management and wind power optimization. Her 2022-2024 publications demonstrate consistent innovation in spatio-temporal modeling, applying model trees and linear architectures to multi-step forecasting challenges across smart grids and wind power plants. Key contributions include spatially-aware nowcasting techniques and autocorrelation leverage for consumption prediction.

Stefano Polimenaمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Computer Vision
• Deep Learning
• +۴ مورد دیگر

Stefano Polimena is a Research Fellow at the Department of Computer Science, University of Bari Aldo Moro. He earned his Bachelor's degree in Data Science with full marks and honors in July 2021. Research Interests: Computer Vision for agro-food quality control Deep Learning and Neural Networks Big Data Analytics and Data Mining Energy Forecasting in Smart Grids Publications Trends: Stefano's work focuses on applying machine learning to food quality assessment and energy consumption forecasting. His research integrates computer vision with regression models for agriculture, and leverages spatio-temporal data mining for smart grid analytics.

Francesco Ravazzoloمشاهده پروفایل

استاد

• Econometrics
• Energy Economics
• Financial Econometrics
• +۳ مورد دیگر

Francesco Ravazzolo is a Full Professor of Econometrics at the Faculty of Economics and Management, Free University of Bozen-Bolzano, and Head of the Department of Data Science and Analytics at BI Norwegian Business School. He holds a Ph.D. from Tinbergen Institute (2007). His research focuses on commodity markets, energy economics, financial econometrics, and macroeconometrics, with over 40 publications in leading journals such as the Journal of Applied Econometrics and Annals of Applied Statistics. He serves on the editorial boards of the International Journal of Forecasting, Journal of Applied Econometrics, and others. His work addresses policy-relevant issues like energy price forecasting, macroeconomic volatility, and cryptocurrency modeling. He co-founded AIAQUA and COMMODIA, spin-offs from the Free University of Bozen-Bolzano. Key research interests include Bayesian econometric methods, nowcasting techniques, and the application of advanced statistical models to energy and financial markets. His recent work examines gas price caps, smart energy systems, and pandemic impacts on businesses. He has collaborated with institutions like the Reserve Bank of Australia on core inflation measures and co-developed the DeCo toolbox for density forecast combination.

Nicola Salvatiمشاهده پروفایل

دانشیار

• Survey Sampling
• Model-Assisted Inference
• Robust Regression
• +۴ مورد دیگر

Nicola Salvati is an Associate Professor in Statistics at the University of Pisa's Department of Economics and Management. He holds a PhD in Applied Statistics from the University of Florence (2004). His research focuses on survey sampling, model-assisted inference, robust regression, quantile and M-quantile regression, spatial statistics, and applications to poverty mapping and Big Data. He contributes to interdisciplinary studies bridging statistics with socio-economic analysis and environmental science. Research interests include developing methodologies for small area estimation, handling linked data, and addressing challenges in causal inference. His work is supported by grants from the European Union and Italy's Ministry of Research. He is a Fellow of the Italian Statistical Society and affiliated with the International Business and Human Rights focus area. Key publications emphasize temporal M-quantile models, causal small area estimation, and applications of statistical methods in air quality and healthcare analysis. His articles frequently address policy-relevant topics like poverty measurement, unemployment, and enterprise sustainability. Advances in his work include methodologies for bias correction, spatial semiparametric modeling, and robust regression techniques. He collaborates on projects involving hedonic pricing, nursing home performance evaluation, and environmental exposure assessment.

Hadi Khaliliaمشاهده پروفایل

پژوهشگر

• Language Diversity
• Natural Language Processing
• Lexical-Semantic Resources
• +۲ مورد دیگر

Hadi Khalilia is a researcher affiliated with Palestine Technical University-Kadoorie (PTUK) since 2015, where he participates in various academic communities and councils. He is currently pursuing a PhD in Information Engineering and Computer Science at the University of Trento , supervised by Prof. Fausto Giunchiglia, after earning his MSc. in Computer Science from AlQuds University (2015) and BSc. in Computer Science with Honors from Arab American University-Palestine (AAUP) (2008). Research Interests: Language diversity, lexical-semantic resources, natural language processing, crowdsourcing, and language computing. Awards: Certificate of Distinction for Outstanding University Research (2019). Article Trends: His work spans computational linguistics (e.g., Arabic WordNet, lexical diversity), educational analytics (student performance prediction), and classical mechanics (coupled pendulum/oscillator systems). Recent publications focus on multilingual lexicon enrichment, semantic gaps in kinship terminology, and web archiving for Palestinian digital heritage.

• Nonlinear Control
• Automotive Systems
• Robotics
• +۴ مورد دیگر

Antonella Ferrara is a Full Professor of Automatic Control at the University of Pavia's Department of Electrical, Computer and Biomedical Engineering (ECBE). She holds leadership roles, including Head of the Intelligent Robotics Laboratory and President of the Department's Research Standing Committee. Her academic journey includes a Laurea Degree (MSc equivalent) in Electronic Engineering from the University of Genova (1987) and a PhD in Computer Science and Electronics (1992). She transitioned from Assistant to Full Professor at the University of Pavia, contributing significantly to nonlinear control, automotive systems, robotics, and power systems. Her research focuses on sliding mode control, vehicular traffic modeling, and applications in autonomous systems. She has authored/co-authored over 450 publications, including 160 journal papers and monographs on topics like vehicle dynamics and freeway traffic control. Awards include IEEE Fellow (2020), IFAC Fellow (2021-2023), and AAIA Fellow (2024). She teaches courses such as Process Control, Robot Control, and Nonlinear Control in English, and contributes to international collaborations, including projects on sustainable mobility and medical robotics. Her institutional roles span research leadership, international mobility coordination, and editorial contributions to journals like Automatica and IEEE Transactions. Prof. Ferrara supervises numerous PhD, postdoc, and graduate students, leading over 200 MSc theses since 2020. She chairs major conferences, including the 24th IFAC World Congress (2029) and the 2024 IEEE Workshop on Variable Structure Systems. Her work bridges theoretical advancements with practical applications in industry, including collaborations with automotive companies like Ferrari F1 and FIAT.