جستجوی استاد راهنمای دانشگاهی

Carlo Orsiمشاهده پروفایل

استادیار

• Non-Central Probability Distributions
• Gaussian Process Regression
• Change Point Analysis
• +۶ مورد دیگر

Carlo Orsi is an Assistant Professor in Statistics at IMT School for Advanced Studies Lucca since November 2023. He holds a Ph.D. in Statistics (2014) from the University of Milan-Bicocca, preceded by a Master's (2011) and Bachelor's (2005) in Statistics from the same institution. Education: Bachelor's in Statistics, University of Milan-Bicocca (2005) Master's in Biostatistics & Experimental Statistics, University of Milan-Bicocca (2011) Ph.D. in Statistics, University of Milan-Bicocca (2014) His research focuses on non-central probability distributions over the unit simplex, multi-output Gaussian process regression, change point analysis, and applied statistics in tourism, medicine, and engineering. He has held adjunct professor roles at multiple universities, including teaching Mathematical Analysis and Probability, and served as a research collaborator at institutions like the National Research Council. His recent publications explore theoretical advancements in non-central distributions, with implications for statistical computation and simulation. He has held diverse roles in academia and industry, including statistical work at pharmaceutical and market research firms, and organizational roles like membership in the Local Organizing Committee for an international statistical conference (2008).

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۹ مورد دیگر

Carlo Masone is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, affiliated with the College of Electronic, Telecommunications, and Physics Engineering. He is also an invited member of the College of Management and Production Engineering and the College of Mathematical Engineering, reflecting his interdisciplinary contributions. His research focuses on artificial intelligence, machine learning, computer vision, and robotics, with significant work in visual place recognition, federated learning, and geospatial AI. His research interests span Artificial Intelligence , Machine Learning , Computer Vision , Robotics , Visual Place Recognition , Federated Learning , Open-Set Segmentation , and Geospatial AI . He has developed methods for uncertainty quantification in ML models for autonomous vehicles and contributed to digital heritage through the MAPP project. The recent publications highlight a strong trend in visual place recognition (e.g., EigenPlaces, MeshVPR), geolocalization of astronaut photography (Earthloc, EarthMatch), and robust segmentation (Mask2Anomaly). There is a clear emphasis on leveraging pre-trained features, federated learning for privacy-preserving recognition, and topological methods in vision. His work bridges robotics, AI, and real-world applications in autonomous systems and cultural heritage. Scientific Awards: Outstanding Reviewer at CVPR (2022, 2023, 2024) IROS JTCF Novel Technology Paper Award (2016) Best Paper Award Finalist at IEEE ICIA (2016) ELLIS Fellow (2024–) He advises PhD students in Artificial Intelligence and Computer and Systems Engineering and leads commercial research projects such as Quantifying Uncertainties in ML Models for Driver-Assisted and Autonomous Vehicles and MAPP - Phygital and Participatory Alpine Museums . He has previously collaborated with the Max Planck Institute for Biological Cybernetics (2014–2017). He teaches courses including Machine Learning for Mathematical Engineering , Robot Learning , and GeoAI , and contributes to programming and data science curricula. He is also a co-inventor on a patent for automated neural network design.

Janna Smirnovaمشاهده پروفایل

استادیار

• Environmental economics
• Circular economy
• Institutional development
• +۷ مورد دیگر

Janna Smirnova is Assistant Professor in Economic Policy (SECS-P/02) at the University of Calabria , Department of Economics, Statistics and Finance. She earned her PhD in Firm, State and Market from the same university, preceded by a Master of Arts in Economics from University College Dublin and earlier degrees from the National Research University of Electronic Technology (MIET, Russia). Since 2011 she has taught macroeconomics, growth theory and international economics across Bachelor, Master and PhD curricula and since 2017 has served as Delegate for Internationalization and President of the International Relations Committee of her department. Research Interests Environmental and resource economics, circular economy and renewable energy policies Institutional development, rule of law and governance quality Gender economics and women’s leadership effects on firm productivity Education economics and long-run impacts of remedial programs Foreign direct investment, innovation diffusion and firm efficiency Her empirical work combines panel econometric techniques with large firm-level and cross-national datasets to evaluate policy effectiveness, environmental regulation and the interplay between institutions and economic outcomes. Research Projects & Funding Scientific Coordinator, University of Calabria Local Unit – GPS Education – Green & Pink for Sustainable Education (PNRR-TNE, 2024-2026) Member, CERERE agri-food supply-chain resilience project (PRIMA, 2024-2026) Member, Institutional Systems and Hospital Performance (PRIN-PNRR 2022, 2023-2025) Member, Ecosystems of Innovation – Tech4You PNRR Mission 4 (2023-2025) Coordinator, Erasmus+ KA171 & KA107 programs with Vietnam, Russia, Czech Republic and Slovakia (2014-2027) Editorial & Peer-Review Service Editorial board member, Modern Economy (SCIRP) and Economic and Socio-Humanitarian Research (MIET) Referee for more than 15 SSCI journals including Energy, Sustainability, International Journal of Finance & Economics, Kyklos, Labour Economics Teaching & Doctoral Supervision PhD supervisor (XXXVII cycle) and tutor (XXXII cycle) Lecturer, Advanced Macroeconomics – Theory of Economic Growth (PhD) Course leader for Macroeconomics (BSc), International Economics (MSc), Theory of Growth (MSc) Invited lecturer, University of Hanoi & University of Danang (2024), Mendel University Brno (2022), Pan-European University Bratislava (2014)

Gianluca Zazaمشاهده پروفایل

استادیار

• mHealth
• Remote Patient Monitoring
• Cardiovascular Risk Assessment
• +۴ مورد دیگر

Gianluca Zaza is an Assistant Professor (non-tenure track) in the Computer Science Department at the University of Bari Aldo Moro, where he conducts research in healthcare technology and artificial intelligence applications. His work focuses on developing contact-less monitoring systems for vital signs and cardiovascular risk assessment using advanced computational techniques. Dr. Zaza's research interests span mHealth, remote patient monitoring, cardiovascular risk assessment, fuzzy inference systems, photoplethysmography, computer vision, and healthcare technology. His work demonstrates a strong focus on applying computational intelligence to solve real-world healthcare problems, particularly in the context of non-invasive monitoring solutions. His recent publications reveal a clear trend toward developing contact-less monitoring systems for vital signs, with particular emphasis on blood oxygen saturation and cardiovascular risk assessment. These works leverage neuro-fuzzy systems, remote photoplethysmography, and video imaging techniques to create practical healthcare solutions that have gained significant relevance during the pandemic era. Member of GNCS-INDAM (Gruppo Nazionale per il Calcolo Scientifico) of Istituto Nazionale di Alta Matematica Research supported by INdAM GNCS within the project 'Computational Intelligence methods for Digital Health' Associated with CITEL - Centro Interdipartimentale di Telemedicina Dr. Zaza's research has practical applications in telemedicine and remote patient monitoring, with potential to reduce the need for physical contact during health assessments, which became particularly valuable during the COVID-19 pandemic. His work bridges the gap between computer science, biomedical engineering, and clinical practice through innovative technological solutions.

Corrado Sinigagliaمشاهده پروفایل

استاد

• Philosophy of Science
• Cognitive Neuroscience
• Social Cognition

Corrado Sinigaglia is Professor of Philosophy of Science at the State University of Milan. He leads the CIA Lab and is affiliated with virtual ABCLabs 6.0. His research bridges philosophy, neuroscience, and social cognition, with a focus on mirror neuron mechanisms, embodied cognition, and interpersonal coordination. His publications explore neurocognitive foundations of social interaction, including EEG/TMS studies on joint action, emotion mirroring, and intentionality. Recent work investigates computational models of collective goals and clinical applications in schizophrenia.

• Machine Learning
• Electronic Design Automation
• Reliability Engineering
• +۷ مورد دیگر

Nicolò Bellarmino is a Researcher at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, where he also serves as an External Lecturer and Teaching Assistant. His work is centered on machine learning applications in electronic design automation, particularly in microcontroller performance screening and reliability assessment of deep learning hardware. His research interests include machine learning for embedded systems, feature selection, neural network testing, and reliability engineering. He employs techniques such as evolutionary algorithms, transfer learning, and fault injection to develop efficient and robust methodologies for semiconductor testing and DNN accelerator validation. The recent publications highlight a strong focus on data-efficient and automated approaches for performance prediction and reliability assessment, leveraging foundation models, unsupervised learning, and hierarchical modeling. These works span journals and top-tier conferences in computer-aided design, electronics, and machine learning. He has no listed scientific awards in the provided text. Bellarmino actively contributes to teaching in the Computer Engineering and Aerospace Engineering programs, collaborating on courses such as Systems Programming, System and Device Programming, and Future of Work. He is a member of the CAD - Electronic CAD & Reliability Group (DAUIN), contributing to cutting-edge research in EDA and hardware reliability. No grants or advising roles are mentioned.

Alfredo Pulvirentiمشاهده پروفایل

استاد

• Bioinformatics
• Biomedicine
• RNA Interference
• +۹ مورد دیگر

Alfredo Pulvirenti is a Full Professor of Computer Science at the University of Catania, Italy. He holds a joint appointment with the Department of Clinical and Experimental Medicine and the Department of Mathematics and Computer Science. Born in 1974, he earned his Laurea (1999, summa cum laude), PhD (2003), and post-doc (2004) in Computer Science from the University of Catania. His academic career includes roles as Assistant Professor (2005-2014), Associate Professor (2014-2023), and Full Professor since 2023. His research bridges Bioinformatics and Biomedicine , focusing on RNA interference (microRNAs, long non-coding RNAs) via stochastic and network-based inference methods. Key contributions include subgraph matching , motif finding , and multiple network alignment using Monte Carlo techniques for analyzing biological networks . He also applies time series analysis to seismic and infrasonic signals through collaborations with Italy's National Institute of Geophysics and Volcanology (INGV). Recent publications highlight advancements in graph algorithms (e.g., MultiGraphMatch, ArcMatch) and systems biology tools like MITHrIL and SPECifIC. He co-directs the Jacob T. Schawartz International School for Scientific Research and leads national/regional projects on Bioinformatics and Big Data in Cancer . His group includes 3 researchers, 1 post-doc, and 3 PhD students in Complex Systems. Awards and Leadership : Best Paper Award at CBS 2009 Guest Editor for BMC Bioinformatics, Briefings in Bioinformatics, Elsevier Program Committee Member for major international conferences International Collaborations span institutions like NYU, Ohio State University Wexner Medical Center, Brown University, Tel Aviv University, Toronto University, and Università di Ancona.

Luis Alberto Barron Cedenoمشاهده پروفایل

دانشیار

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۷ مورد دیگر

Luis Alberto Barron Cedeno is an Associate Professor at the Department of Interpretation and Translation, University of Bologna since 2022, where he previously served as Senior Assistant Professor from 2019-2022. He holds a PhD in Computer Science from Universitat Politècnica de València (2012) and has worked at Qatar Computing Research Institute (2014-2019) and TALP Research Center (ERCIM fellowship, 2012-2014). PhD: Universitat Politècnica de València (2012) MSc: AI (Universitat Politècnica de València, 2009) MSc: Computing Science (UNAM, 2007) BEng: Computing (UNAM, 2004) His research focuses on NLP applications for analyzing text qualities like originality (plagiarism detection) and intent (hate speech, propaganda). Recent work includes persuasion techniques in spam emails , misogyny detection using argumentation theory, and Spanish language varieties analysis. He has published over 100 papers with 20+ in top-tier conferences. Key awards include SemEval 2020 Best Task for propaganda detection and ACL 2020 Best Demo . He serves as Specialty Chief Editor for Frontiers in Artificial Intelligence (NLP) since 2023. His students include PhD candidates Arianna Muti (misogyny detection), Katerina Korre (hate speech), and Paolo Gajo (inceldom analysis). 2020: SemEval Best Task 2020: ACL Best Demo 2012: PhD International Mention 2009: Best MSc Thesis 2007: MSc Cum Laude 2004: BEng Cum Laude He organizes the annual CheckThat! lab at CLEF since 2018 and chaired CLEF 2022. His teaching includes NLP courses, computational linguistics, and game localization for translation students.

Carlo Rasmus Schwarzمشاهده پروفایل

استادیار

• Applied Microeconometrics
• Political Economy
• Media Economics
• +۱ مورد دیگر

Carlo Rasmus Schwarz is an Assistant Professor in the Department of Economics at Bocconi University. He holds a PhD in Economics from the University of Warwick and teaches courses including AI Methods for Economic Research and Advanced Econometrics. PhD in Economics, University of Warwick Dr. Schwarz's research focuses on applied microeconomics with particular emphasis on policy-relevant questions. His work uniquely combines causal inference strategies with text analysis, machine learning, and data science techniques to address pressing societal issues. He is particularly interested in how digital platforms shape political behavior and social dynamics. His publication portfolio reveals a strong trend toward investigating the societal impacts of social media, with increasing focus on hate speech, political polarization, and electoral outcomes. The research demonstrates methodological innovation through the development of specialized Stata commands for text analysis, bridging computational linguistics and traditional economic inquiry. Dr. Schwarz actively contributes to advancing methodological approaches in economics through his software development work, creating tools that enable more sophisticated text-based economic research. He maintains an active research agenda exploring the complex relationship between digital communication platforms and real-world socioeconomic phenomena, with recent work examining how online discourse translates to offline behaviors including hate crimes and voting patterns.

Gianluigi Pillonettoمشاهده پروفایل

استادیار

• System Identification
• Stochastic Systems
• Deconvolution Problems
• +۳ مورد دیگر

Gianluigi Pillonetto is an Assistant Professor at the Department of Information Engineering , University of Padova , where he has been employed since 2005. His academic career focuses on system identification, stochastic systems, and nonparametric regularization techniques. Born: January 21, 1975 in Montebelluna, Italy Education: Doctoral degree (1998) and PhD (2002) in Computer Science/Engineering Research roles: Visiting scholar (2000), Visiting scientist (2002), Research Associate (2002-2005) His research spans system identification, stochastic processes, and deconvolution problems, with a particular emphasis on Bayesian methods and kernel-based regularization. He has contributed to areas like distributed Gaussian regression, sparse system identification, and nonlinear stochastic modeling in physiological systems. Recent publications (2016-2021) examine Gaussian regression techniques for distributed systems, entropy-based kernel design, and nonlinear stochastic deconvolution. These works incorporate machine learning principles into control theory, focusing on applications in wireless communications, robotics, and biomedical engineering.

Mattia Zorziمشاهده پروفایل

دانشیار

• Learning Dynamic Networks from data
• Robust and distributed filtering
• Dynamic Brain Networks
• +۸ مورد دیگر

Mattia Zorzi is an Associate Professor in the Department of Information Engineering at the University of Padova, Italy. He has held academic positions since 2014, transitioning from Assistant Professor to Associate Professor in 2020. His research focuses on system identification, machine learning, and robust control, with applications in dynamic brain networks, robotic systems, and quantum information processing. Education: Ph.D. and M.S. in Information Engineering from University of Padova International Experience: Visiting Scientist at University of Cambridge (2013-2014), Research Associate at University of Liege (2013-2014) Zorzi's research integrates robust and distributed filtering, inverse dynamics learning, and nonparametric identification of Kronecker networks. His work bridges theoretical advancements in spectral estimation with practical applications in neuroscience (e.g., effective connectivity analysis) and control systems (e.g., robust Kalman filtering under uncertainty). Recent publications (2024-2023) demonstrate expertise in ARMA graphical models, kernel-based estimation, and optimal transport for Gaussian processes. He has contributed to the IEEE and IFAC communities as Associate Editor and actively participates in editorial roles for leading journals. Scientific Awards: IEEE Senior Member (2021) Member of IFAC Technical Committee TC 1.1 (2018) Associate Editor roles in Automatica, IEEE Control Systems Letters, and major conferences Grants & Collaborations: Collaborated on projects involving quantum channel estimation, free-space quantum communication, and biomedical signal processing.

Yashar Deldjooمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Recommender Systems
• +۷ مورد دیگر

Yashar Deldjoo is an Assistant Professor specializing in artificial intelligence, machine learning, and their applications in healthcare, user modeling, and recommender systems. His research focuses on explainable AI, ethical AI practices, multimodal learning, and brain-computer interfaces. He has contributed to projects like WeBIUM (Wearable Devices and Brain-Computer Interfaces for User Modelling) and ARIEL (emotional support via BCI and LLMs). His work bridges technical advancements with societal impacts, addressing challenges in healthcare diagnostics (e.g., Alzheimer’s disease prediction), environmental sensing (real-time pollution-aware recommendations), and cybersecurity (data poisoning attacks on recommendation systems). He also explores fairness in large language models and the integration of EEG-based emotion recognition systems. Notable contributions include frameworks like BRAINEX (CNN model evaluation for brain age prediction), Ducho (multimodal feature extraction for recommendation systems), and KGUF (knowledge-aware graph-based recommenders). He chairs conferences like RecSys and contributes to industry-relevant standards for trustworthy AI systems. His research emphasizes interdisciplinary collaboration, combining neural networks, ethical considerations, and human-computer interaction. Current projects involve neurorehabilitation tools, quantum security for smart cities, and AI-driven usability testing.

Edoardo Zanelliمشاهده پروفایل

پژوهشگر ارشد

• Econometrics
• Bootstrap Inference
• Nonparametric Methods
• +۳ مورد دیگر

Edoardo Zanelli is a Research Fellow and 5th-year PhD student in Economics at the University of Bologna's Department of Economics. He also serves as a Teaching Tutor and has held roles as a Teaching Assistant for courses like Mathematical Economics and Advanced Time Series Econometrics. His research focuses on econometric methodologies, particularly bootstrap inference, nonparametric techniques, and boundary parameter analysis. In Fall 2025, he will assume a postdoctoral position at Aarhus University's Aarhus Center for Econometrics (ACE). Education includes a BSc and MSc in Economics (both summa cum laude) from the Catholic University of Milan and University of Bologna respectively, followed by PhD studies at the University of Bologna under Prof. Giuseppe Cavaliere. Research interests include bootstrap methods for nonlinear models, bias correction in estimators, boundary parameter inference, instrumental variable (IV) specification testing, and Phillips Curve instability estimation.

• Bayesian inference
• Machine learning
• Nonparametric methods
• +۵ مورد دیگر

Francesca Panero is an Assistant Professor (RTT) in Statistics at the Department of Methods and Models for Economy, Territory, and Finance (MEMOTEF) at Sapienza University of Rome. She also serves as a Visiting Fellow at the Department of Statistics of the London School of Economics and Political Science, where she was previously an Assistant Professor until May 2024. Additionally, she maintains an affiliation with the Grantham Research Institute on Climate Change and the Environment at LSE. Dr. Panero earned her PhD in Statistics from the University of Oxford in 2022, following undergraduate and master's studies at the Department of Mathematics of the University of Turin and Collegio Carlo Alberto. Her academic journey reflects a strong foundation in mathematical and statistical theory applied to complex real-world problems. Her research centers on Bayesian statistical methodologies with applications across multiple domains. She specializes in complex networks analysis using Bayesian nonparametric approaches, disclosure risk assessment for privacy preservation, spatio-temporal Gaussian process modeling for food insecurity prediction, and fair machine learning techniques. Her work demonstrates a consistent thread of developing rigorous statistical methods with practical societal applications, particularly in network science, privacy protection, and algorithmic fairness. Dr. Panero's publications reveal a strong trajectory in high-impact statistical research, with recent work focusing on sparse network modeling, fairness constraints in machine learning, and privacy-preserving statistical techniques. Her methodological contributions bridge theoretical statistics with applications in social sciences, public policy, and computational challenges. 2025 Visiting Lecturer at Faculty of Informatics, University of the Italian Switzerland (USI) Elected as j-ISBA Chair Elect for 2025-2026 Recipient of IMS junior research travel grant for ICSDS 2024 Awarded LSE Research and Impact Support Fund (RISF) grant for food insecurity research As an educator, Dr. Panero teaches Probability and Stochastic Processes at Sapienza University and has previously instructed Deep Learning and Artificial Intelligence courses at LSE. She actively mentors students and encourages PhD candidates interested in her research areas to contact her. She is also a core member of GENIAL, an LSE focus group examining how students utilize generative AI tools for learning. Beyond her technical work, she has been engaged in equality, diversity, and inclusion initiatives since 2020 and maintains an active academic blog discussing data visualization, research projects, and academic life.

Gaia BERTARELLIمشاهده پروفایل

استادیار

• Social Statistics
• Small Area Estimation (SAE)
• Robust Statistics
• +۷ مورد دیگر

Gaia BERTARELLI is an Assistant Professor (Tenure-Track) in Social Statistics at the Department of Economics, Ca' Foscari University of Venice. She holds a PhD in Statistics from the University of Milan-Bicocca (2015), with earlier degrees in Mathematics (Bachelor) and Biostatistics (Master). Her research focuses on small area estimation (SAE), robust statistics, latent variable models, and multidimensional poverty measurement, with applications in health systems, gender inequality, and sustainable well-being. She collaborates with institutions like ISTAT (Italian National Institute of Statistics), FAO, and Save the Children ONLUS, and has been involved in EU-funded projects since 2018. Education: Bachelor's in Mathematics, University of Milan-Bicocca Master's in Biostatistics and Experimental Statistics, University of Milan-Bicocca PhD in Statistics, University of Milan-Bicocca (2015) Research Interests: Her work integrates statistical methodology with real-world challenges, emphasizing poverty measurement, health systems analysis, and gender inequality. She develops SAE models to assess multidimensional poverty and policy effectiveness, particularly in official statistics. Her recent projects include measuring educational poverty, analyzing healthcare disparities in aging populations, and evaluating digital health interventions. Editorial Roles: Associate Editor, Statistical Methods & Applications (2024–) Editor of 'Book and Software' section, The Survey Statistician (2024–) Professional Activities: Member of the S2G group (SIS) on Methodologies for Sample Surveys (2024–2025) Past coordinator of y-SIS (Young Italian Statisticians) and YSE (Young Statisticians Europe) Labs/Teams: She contributes to the Research Institute for Social Innovation at Ca' Foscari, focusing on interdisciplinary social science research.