جستجوی استاد راهنمای دانشگاهی

Marco Ieva is an Assistant Professor in Marketing at the Department of Economics and Management, University of Parma (Italy). His academic career spans postdoctoral research, visiting scholar appointments, and extensive teaching across multiple universities including CUOA Business School (Italy), University of Valencia (Spain), and Technological University Dublin (Ireland). Research Focus : Retailing, omni-channel marketing, media effectiveness, customer experience touchpoints, and marketing innovation. Methodologies : Specializes in statistical causal inference, partial least squares (PLS), and latent class analysis for segmentation. Scientific Recognition : Best paper award (2018) - MICRO & MACRO MARKETING journal Best Conference Paper (2017) - Excellence in Services International Conference Best Conference Paper (2017) - Italian Marketing Association Conference National Award finalist for Doctoral Dissertation (2017) Winner of Spanish Ministry research funding (ECO2017-83051-R project) Teaching : Delivers courses on CRM and Customer Analytics, Digital Marketing, and Services Marketing at bachelor, master, and MBA levels. Holds certifications in Google Analytics, Google Ads, and Hubspot Social Media Marketing.

• Retailing
• Omni-channel marketing
• Media effectiveness
• +۶ مورد دیگر

Davide Pellegrini is an Associate Professor at the Department of Economic and Business Sciences, University of Parma, where he teaches courses in Marketing, Trade, and Consumer Behavior. He has been instructing courses such as Trade and Consumer Marketing , Digital Marketing in Pharmacy , and Economics and Company Management across multiple academic years (2013/2014–2025/2026). His research focuses on sustainable marketing practices, consumer decision-making, and digital interventions in retail contexts. Academic Rank: Associate Professor Department: Economic and Business Sciences University: University of Parma Research trends include: Analysis of sustainable consumer behavior Integration of behavioral theories (TPB, NAM) Digital marketing strategies in pharmaceutical and retail sectors Bibliometric reviews of marketing and nutrition intersections Contact: davide.pellegrini@unipr.it

• Marketing
• Consumer Behavior
• Digital Marketing
• +۳ مورد دیگر

Vincenzo Gioia is a Research Fellow at the University of Trieste's Department of Economics, Business, Mathematics and Statistics (DEAMS). She specializes in statistical methodologies for environmental and multivariate data analysis, with a focus on extreme value theory and Markov-switching models. Her work addresses climate change impacts (heat wave detection), energy demand modeling, and urban pollution analysis. Current Projects: Joint DEAMS research project analyzing public/telecom data for environmental applications Third-party transport data analytics funded by Trieste Trasporti (€33k) Research Interests: Bayesian statistics, time series modeling, spatial-temporal analysis, and algorithmic approaches to high-dimensional data. Active in environmental and energy sector applications.

• Statistics
• Environmental Statistics
• Time Series Analysis
• +۳ مورد دیگر

Grid Thoma is an Assistant Professor at the University of Camerino (Università degli Studi di Camerino). His research focuses on intellectual property valuation, patent strategies, and real options analysis in finance. He specializes in quantifying the market value of patents, trademarks, and R&D investments using advanced econometric models like binomial option pricing frameworks. Key areas of research include cross-national comparisons of patent strategies, trademark-patent pairing effects, and the impact of innovation policies on market valuations. His work integrates firm-level patent data with financial metrics such as Tobin's Q to develop composite indices for IP valuation. Publications emphasize strategic IP management, including studies on knowledge spillover localization, combined IP portfolio synergies, and the geographic dimensions of patent premium valuation. His analysis spans industries like medical/cosmetic products and nanobiotechnology, with a focus on both developed and emerging markets like China. No scientific awards or academic grants are explicitly mentioned in the provided texts. Advising activities and student supervision details are currently unavailable.

• Intellectual Property Valuation
• Patent Strategy Analysis
• Real Options in Finance
• +۵ مورد دیگر

Lorenzo Rossi is an Assistant Professor specializing in the intersection of process mining, robotics, and business process management (BPM). His research focuses on advancing methodologies for analyzing robotic systems, IoT environments, and collaborative processes through formal models like BPMN. Key areas include process discovery, digital twins, and system resilience in smart environments. Expertise: Process Mining, Multi-Robot Systems, BPMN Semantics, Cyber-Physical Systems Key Tools: BEAR (BPMN animator), MIDA (multi-instance animator), UBBA (Unity-based BPMN animator) His work emphasizes reproducibility and practical frameworks for rapid prototyping. Recent trends in his articles highlight the integration of process mining with robotics for data-driven decision-making, as well as formal verification of BPMN collaborations to ensure system correctness. Awards: None explicitly mentioned in the provided texts. Advising & Grants: No student/advisor relationships or grant details documented here. Labs/Teams: Collaboration with Unity-based simulation tools (UBBA, MIDA) and serious game platforms (PlayWithUnicam).

• Process Mining
• Robotics
• Business Process Management (BPM)
• +۵ مورد دیگر

Gabriella Marcarelli is an Associate Professor at the University of Sannio, Italy, working in the Department of Law, Economics, Management and Quantitative Methods (DEMM). Her research focuses on mathematical methods of economics and actuarial and financial sciences, specifically in the area of multi-criteria decision-making methodologies. Dr. Marcarelli's research interests span multiple areas within decision science, with particular emphasis on the Analytic Hierarchy Process (AHP), ELECTRE methods, and their applications in various domains including finance, education, public administration, and healthcare. She has made significant contributions to understanding how multi-criteria methods can explain behavioral anomalies that violate traditional expected utility theory. Her work demonstrates how methods like ELECTRE III can account for phenomena such as the certainty effect and reflection effect in decision making. Her publication record reveals a strong trend toward applying multi-criteria decision methods to practical problems. Early in her career, she focused on statistical approaches to analyzing AHP matrices, then expanded to applying these methods to investment choice problems, public tenders, school ranking systems, and healthcare performance management. Recent work shows increasing sophistication in classification methods like q-AHPSort II for evaluating STEM programs. Her research demonstrates the versatility of multi-criteria decision methods across diverse application domains while maintaining theoretical rigor. Dr. Marcarelli has established productive collaborations with researchers including Massimo Squillante, Gerarda Fattoruso, Paola Mancini, Matteo Rossi, and Antonio Lucadamo. Her work often involves empirical testing of theoretical models using data from financial markets, educational institutions, and public organizations. While specific grant information isn't detailed in the available materials, her research program shows sustained productivity across multiple application areas of decision science.

• Multi-criteria Decision Making
• Mathematical Methods of Economics
• Actuarial and Financial Sciences
• +۵ مورد دیگر

Maria Elena Bruni is an Associate Professor in Operations Research at the University of Calabria , actively contributing to research and teaching since 2006. Her academic journey includes a Ph.D. in Operations Research (2005) and an M.S. in Public Economy from Sapienza University of Rome (2002). She has held various teaching roles, including Optimization , Production Process Management , and Business Process Design , primarily within Mechanical and Energetic Engineering programs. Research Focus: Stochastic and robust optimization, healthcare logistics, project scheduling, and energy systems. Key Labs: Financial Engineering and Risk Management Lab (FERM), Decision Engineering for Healthcare Lab. Bruni's research centers on combinatorial optimization under uncertainty, with applications in healthcare (operating room scheduling, EMS design), logistics (vehicle routing, post-disaster relief), and energy systems (smart microgrids, prosumer management). Her work often combines mathematical programming with risk-averse strategies for real-world complexity. Scientific honors include multiple best poster awards at ICORES (2019, 2018, 2015) and scholarships from prestigious institutions. She serves on editorial boards of journals like Sustainability and Mathematical Problems in Engineering , and has participated in significant research projects such as PRIN 2018's MACHINE and PON HEALTHSOAF. Her supervision spans 3 doctoral theses in Operations Research and 2 in Mathematics/Computer Science. Notable scientific collaborations include co-authoring over 70 journal articles and book chapters, with a focus on stochastic programming and data envelopment analysis applications.

• Operations Research
• Stochastic Programming
• Robust Optimization
• +۵ مورد دیگر

Mario Agostino Rocca serves as a Full Professor in the Department of Physics (DIFI) at the University of Genoa, Italy. He teaches multiple graduate-level courses including Structure of Matter, Solid State Physics, and Surface Science within the Master's Degree Programs in Advanced Materials Science and Technology and Materials Science and Technology. His research centers on experimental surface science and nanotechnology, with emphasis on atomic-scale phenomena at material interfaces. Key interests include surface reactions on metal substrates, graphene functionalization, nanostructure formation through molecular self-assembly, and advanced characterization techniques like XPS. His work bridges fundamental physics with materials engineering applications. Analysis of recent publications (2022-2025) reveals consistent focus on surface-assisted chemical reactions, particularly using Pd-cyclometalled complexes on single-crystal surfaces (Ag(110), Ni(111)). His research combines ultra-high vacuum surface science with near-ambient pressure studies, highlighting methodological innovation in characterizing 2D materials and catalytic processes. Scientific Awards: No awards or honors are documented in the provided information. While specific student advising details are absent, his teaching responsibilities in advanced materials programs and research publications indicate active supervision of graduate students. The collaborative nature of his publications across multiple institutions suggests participation in internationally funded research projects, though explicit grant information is not provided. His experimental work implies affiliation with surface science laboratories within DIFI equipped for ultra-high vacuum surface preparation, XPS analysis, and nanomaterials characterization, though specific lab names or team structures are not mentioned in the source material.

• Surface Science
• Nanotechnology
• Condensed Matter Physics
• +۲ مورد دیگر

Vera Muccilli is an Associate Professor of Organic Chemistry at the University of Catania , Italy. She coordinates the Master Degree in Chemical Sciences and contributes to the Chemistry of Bioactive Natural Products Group. Her academic journey includes a summa cum laude degree in Industrial Chemistry (2002) and a PhD in Chemical Sciences (2006), focusing on mass spectrometry applications in cereal proteins. She conducted research at the National Center for Biotechnology in Madrid and received recognition from the Italian Chemical Society in 2006. Research interests span chemical/enzymatic modification of bioactive natural compounds, structure-activity relationship studies, polyphenol extraction from medicinal plants and agricultural waste, antioxidant activity evaluation, and metabolomic analysis via NMR. Her work integrates Biomimetic and enzyme-mediated synthesis Spectroscopic characterization (MS, NMR) Metabolic enzyme inhibition for drug discovery Valorization of plant biomass into sustainable applications. Recent publications highlight her contributions to pancreatic lipase inhibition, antidiabetic agent development, and polyphenol-based materials. Collaborations include BASF SE , Universidade Federal do Paranà , and EU-OPENSCREEN ERIC. Funding includes national PRIN PNRR 2022 and 2017 grants, alongside a University of Catania Pia.ce.ri. grant for diabetes-targeted research. Award: 2006: Young Researcher in Mass Spectrometry, Italian Chemical Society Educational leadership includes roles as accredited tutor at the Scuola Superiore di Catania and delegate for CINAP (Active & Participatory Inclusion Center). She serves on the International Summer School on Natural Products committee and is a reviewer for 14 journals including Food Chemistry and Molecules .

• Bioorganic Chemistry
• Enzymology
• Antioxidants
• +۳ مورد دیگر

Alberto Torrisi is a Full Professor of Analytical Chemistry at the Department of Chemical Sciences of the University of Catania . His career spans over four decades, including roles as Assistant Professor of Physical Chemistry (1984-1992), Associate Professor of Analytical Chemistry (1992-2006), and Full Professor since 2006. He has held visiting positions at Philips Research Laboratories and contributed to institutional committees for academic evaluations. Education: PhD in Chemistry from University of Catania (1980, magna cum laude ) His research focuses on surface and interface phenomena in materials like polymers, metals, and composites, with applications in microelectronics, cultural heritage conservation, and biomedical fields. He pioneered advancements in Secondary Ion Mass Spectrometry (SIMS) , X-ray Photoelectron Spectroscopy (XPS) , and Angle-Resolved XPS for depth profiling and artifact mitigation. His work also includes synthesizing ion-selective macrocyclics and developing big data statistical methods for ToF-SIMS. Recent publications highlight innovations in cluster ion beam depth profiling and multivariate data analysis for improved mass resolution. His scientific output comprises 63 international journal publications and 69 conference presentations, with interdisciplinary applications in cultural heritage and biomedicine. Scientific Awards NATO Scholarship (1988-1989) As an educator, he teaches Analytical Chemistry I and laboratory courses, with active involvement in PhD admissions committees. His institutional roles include membership in evaluation commissions for academic grants and professorships.

• Materials Science
• Analytical Chemistry
• Surface Science
• +۳ مورد دیگر

Andrea Prati is a Full Professor in the Department of Engineering and Architecture at the University of Parma, Italy. He has previously served as an Assistant Professor at the University of Modena and Reggio Emilia and as an Associate Professor at the University IUAV of Venice. His research spans computer vision, pattern recognition, video surveillance, machine learning, and sensor networks, with applications in smart cities, traffic systems, healthcare, and industrial automation. His research interests include: Computer Vision and Pattern Recognition for creative industries (e.g., apparel analysis with Adidas) Distributed and embedded sensor networks for mobile vision Motion analysis and object tracking in multi-camera environments Semantic video transcoding and annotation Abnormal behavior detection for security and terrorism prevention Performance optimization in multimedia architectures The recent publications highlight a strong focus on trajectory modeling, anomaly detection, and multi-camera surveillance systems. Themes such as spectral graph analysis, statistical modeling of motion, and robust outdoor surveillance illustrate a consistent trajectory in advancing intelligent video analytics. His work bridges theoretical innovation with real-world applications in public safety, transportation, and ambient intelligence. Scientific honors include: IAPR Fellowship (2014) for contributions to video surveillance algorithms He has served as Program Chair and General Chair for major international conferences such as ICDSC, ICIAP, and VNBA. He is actively involved in research leadership, including editorial roles for IEEE TCSVT, Elsevier's CVIU, and MDPI Applied Sciences. He leads and collaborates on numerous research projects funded regionally (Emilia-Romagna), nationally (PRIN), European (DELOS, THIS), and internationally (NATO Science for Peace). He also co-developed a patented solution with Marchesini Group SpA. His research group, IMPLab, drives innovation in intelligent systems. He teaches courses in computer architecture, algorithms, AI, and machine learning across undergraduate and graduate programs in engineering and data science.

• Computer Vision
• Pattern Recognition
• Video Surveillance
• +۱۲ مورد دیگر

Olga Baysal is an Associate Professor at the School of Computer Science, Carleton University, and serves as Director of the Carleton University Institute for Data Science (CUIDS). She has held roles including Graduate Director (2020-2022) and Acting Director of CUIDS (2021), with prior faculty positions at Université de Montréal and Ryerson University. PhD and Master's in Computer Science from University of Waterloo NSERC Postdoctoral Fellowship at University of Toronto Her research focuses on applying AI, ML, and NLP techniques to software engineering challenges through empirical studies of development artifacts. She leads the Software Analytics (SWAN) research group, mentoring 3 PhD and 4 MCS students while collaborating with industry partners like Ericsson, Shopify, and Google. Research keywords: Software Engineering, Data Science, AI/ML, Mining Software Repositories, Human-Computer Interaction, Empirical Methods. NSERC Postdoctoral Fellowship Dr. Baysal has supervised over 20 graduate and 30 undergraduate students. Her teaching includes courses on Data Science (DATA 5000) and Mining Software Repositories (COMP 5117), emphasizing interdisciplinary teamwork and practical applications using R, Tableau, and IBM tools.

• Software Engineering
• Empirical Software Engineering
• AI for Software Engineering
• +۶ مورد دیگر

Stefano Lambiase is a researcher in Computer Science currently affiliated with Aalborg University in Denmark, where he holds an institutional email address (stla@cs.aau.dk). He earned his PhD in Computer Science from the University of Salerno at the Software Engineering Laboratory (SESA Lab), with a doctoral project titled "Longitudinal Data-Driven Software Project Management" focusing on the social and human aspects of Software Development and Management. His educational background includes: PhD in Computer Science from University of Salerno (2019-present) Master's Degree in Computer Science from University of Salerno (2019-2021), with thesis on "Cultural and Geographical Dispersion Impact on Communication and Collaboration of Software Development Teams" Bachelor's Degree in Computer Science from University of Salerno (2015-2019), with thesis on "Test Smell Detection and Suggestions (TESEUS)" Stefano's research interests center around the human and social dimensions of software engineering , with particular focus on cultural and geographical dispersion in software development teams, community smells (socio-technical anti-patterns), and their impact on productivity and software quality. His work bridges theoretical frameworks with practical applications, developing tools like CADOCS (a conversational agent for community smell detection) and DARTS (a test smell detection and refactoring plugin). He has also explored emerging areas including quantum software communities, metaverse development, and the integration of large language models in software engineering practices. His publication record demonstrates a consistent focus on socio-technical aspects of software development, with recent work examining cultural dispersion effects, community smells in various contexts (including machine learning systems and quantum computing), and educational applications in the metaverse. His research employs diverse methodologies including empirical studies, surveys, interviews, and tool development. Stefano has received recognition for his work, including a Best Paper Award at the 25th Euromicro Conference on Software Engineering and Advanced Application (SEAA 2022) for his paper "'There and Back Again?' On the Influence of Software Community Dispersion Over Productivity". He has been actively involved in the software engineering research community, serving on program committees for major conferences including ICSE-SEET 2024, SANER 2024, ICSEA 2023, MSR 2023, and SCAM-NIER 2023. Additionally, he served as Social Media and Web Chair for the Third Workshop on Gender Equality, Diversity, and Inclusion in Software Engineering (GE@ICSE 2022). Stefano has developed several research tools and projects: DARTS (Detection And Refactoring of Test Smells): An IntelliJ plugin for detecting and refactoring test smells CADOCS : A conversational agent for community smell detection and refactoring in Slack Erwin Bot : A chat bot for management support built with Azure Cloud Services BiblioNet : A Spring Boot Web App for library support QuantuMoonLight : A low-code platform to experiment with quantum machine learning SENEM : A software engineering-enabled educational metaverse SERGE : A serious game for risk management education in software project management

• Social and Human Aspects of Software Engineering
• Cultural and Geographical Dispersion
• Community Smells
• +۶ مورد دیگر

Assistant Teaching Professor at Carnegie Mellon University with expertise in AI-assisted programming, developer tools, and human-computer interaction. Previously held academic positions at the University of Tennessee (Assistant Professor 2018-2022) and research roles at Microsoft (Senior Researcher 2022-2023, Visiting Researcher 2019). Industry experience includes CTO at BYBE (acquired in 2023) and VP of Engineering at Swiftly. PhD from University of Memphis (Advisor: Scott Fleming) Over 40 publications in software engineering, AI tools, and educational technology Recipient of multiple best paper awards at EICS, SIGMOD, and VL/HCC Research focus on AI-enhanced programming interfaces and educational tool development Recent work explores transitioning academic research into industry applications through the OurCode framework, while educational efforts examine LLM-based programming assistants' impact on learning outcomes.

• AI-assisted programming
• Developer tools
• Software engineering
• +۳ مورد دیگر

Daniel Alencar da Costa is a Lecturer (Assistant Professor equivalent) at the Information Science Department of the University of Otago, Dunedin, New Zealand. Previously, he worked as a Postdoctoral Fellow in the Software Reengineering Research Group at Queen's University, Kingston, Canada, under Prof. Ying Zou. His academic background includes a BSc (2007) from University Centre of Pará (Belém, Brazil), MSc (2013) and PhD (2017) from Federal University of Rio Grande do Norte (UFRN), supervised by Prof. Uirá Kulesza and Prof. Ahmed E. Hassan during his SAIL Lab visit. Current Position: Lecturer at School of Computing, University of Otago Past Role: Postdoctoral Fellow at Queen's University Education: PhD & MSc from UFRN; BSc from CESUPA His research focuses on Empirical Software Engineering , employing machine learning, statistical analysis, and qualitative methods (surveys, interviews) to understand software development phenomena. Key interests include optimizing software practices through empirical validation, CI/CD monitoring, defect prediction, and team dynamics analysis. Recent work investigates continuous integration patterns in ML projects and crash prediction in mobile applications. Scientific contributions include collaborative research with institutions like Queen's University and SAIL Lab. He co-supervises students such as Chathrie Wimalasooriya and explores tools for identifying development bottlenecks. Contact available via danielcalencar@otago.ac.nz.

• Empirical Software Engineering
• Machine Learning
• Statistics
• +۳ مورد دیگر