جستجوی استاد راهنمای دانشگاهی

• Business Administration
• Operations Research
• Supply Chain Management
• +۶ مورد دیگر

Prof. Dr. Julia Rieck is a Full Professor of Business Administration at the University of Hildesheim , leading the Department of Business Administration and Operations Research within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science. As Dean of the Faculty , she oversees academic programs, quality management, and research initiatives. Her roles include academic advising for the Business Information Systems (B.Sc./M.Sc.) programs and active participation in examination boards and quality committees. Education: PhD in Political Science (Dr. rer. pol.) with summa cum laude (2008), Habilitation at Clausthal University of Technology (2014), and studies in Business Mathematics (Diploma, University of Hamburg, 2003) and Mathematics (Georg-August-University Göttingen, 2000). Research: Focuses on Operations Research , Supply Chain Management , Project Planning , and Logistics . Her work integrates mathematical modeling , machine learning , and real-world applications , particularly in disaster response , dynamic transportation , and sustainable e-commerce . Projects: Leads third-party funded initiatives like "IT für die sorgende Gesellschaft" (AI in healthcare/social sectors) and contributes to the HULLS real-lab (AI in aging societies). Collaborates with regional companies (e.g., Youco, ADITUS) and institutions (HAWK, University of Hannover). Teaching: Emphasizes practical application through case studies, industry partnerships, and the IT-Speed Dating event for student-company connections. Her courses cover project resource planning , logistics , and digital transformation . Labs & Teams: Active in the Institute of Business Administration & Business Information Systems , contributing to the KET Kompetenzwerkstatt (entrepreneurship support) and interdisciplinary teams in AI and sustainability research.

• Process Mining
• Business Process Management
• Stochastic Processes
• +۴ مورد دیگر

Dr. Sander Leemans is a Professor at RWTH Aachen University leading the Business Process Management Foundations and Engineering research group. His work focuses on advancing process mining theory and practice with emphasis on stochastic modeling and conformance verification. Leemans' research centers on process mining, business process management, and stochastic process modeling. He investigates conformance checking techniques for probabilistic models, process discovery algorithms, and the integration of exogenous data into process analysis. His work bridges theoretical foundations with practical applications in healthcare, robotic process automation, and inter-organizational systems. Recent publications reveal a concentrated research trajectory in stochastic conformance checking, where Leemans develops methods for matching observed traces to stochastic process models using alignment techniques, entropy metrics, and partial-order reasoning. He also pioneers object-centric process mining frameworks and explores silent transitions in labeled Petri nets, significantly enhancing the precision and applicability of process mining in real-world scenarios. The Business Process Management Foundations and Engineering group under Leemans' leadership drives innovation in process mining through rigorous theoretical development and open-source tooling, maintaining RWTH Aachen's position at the forefront of business process intelligence research.

• Embedded Systems
• Software Verification and Validation
• Model Checking
• +۵ مورد دیگر

Stefan Kowalewski serves as Professor of Embedded Software at RWTH Aachen University, leading the Chair of Embedded Software (Informatik 11) within the Department of Computer Science. His research spans critical domains including medical cyber-physical systems, automotive software, and industrial automation, with over 150 publications demonstrating sustained scholarly impact. Professor Kowalewski's work focuses on three interconnected research pillars: Embedded Systems Verification: Pioneering model checking techniques for PLC code, particularly addressing state space challenges in GRAFCET-based specifications Medical Cyber-Physical Systems: Developing safety-critical software for mechanical ventilation, extracorporeal membrane oxygenation, and ARDS diagnosis systems with strong clinical collaborations Automotive Software: Creating verification frameworks and safety architectures for automated vehicles through projects like UNICARagil Recent publications reveal an increasing integration of AI techniques with traditional verification methods, particularly for medical applications involving neonatal care and critical respiratory support. His 2024-2025 work shows particular emphasis on timing isolation in vehicle communication systems, middleware performance evaluation, and robust AI models for medical diagnosis. Professor Kowalewski maintains active collaborations with RWTH Aachen University Hospital's medical departments and automotive industry partners. His laboratory operates specialized facilities including the Cyber-Physical Mobility Lab for vehicle research and in-vivo testing setups for medical device validation. He has supervised numerous doctoral candidates, with recent students focusing on topics like ARDS classification algorithms, GRAFCET verification techniques, and safety architectures for software-defined vehicles. His educational contributions include developing remote teaching platforms for cyber-physical systems education.

Oktay Türetkenمشاهده پروفایل

استاد

• Business Process Management
• Digital Business Models
• Smart Mobility Solutions
• +۳ مورد دیگر

Oktay Türetken is a Full Professor at Eindhoven University of Technology (TU/e) in the Industrial Engineering and Innovation Sciences school, specializing in Information Systems . He chairs the Industrial Engineering Bachelor Program and contributes to the European Research Center for Information Systems (ERCIS) in Münster, Germany. PhD in Information Systems Research Fellow at European Research Institute in Service Science (2008-2012) Adjunct Lecturer at METU’s Software Management program (pre-2008) His research focuses on digital innovation and collaborative business models , particularly in urban mobility. He develops methods for operational design , business process management , and data analytics maturity models . Key projects include MobilitEU and EU-funded initiatives in smart mobility. Recent publications address KPI frameworks for business models, platform design for shared mobility, and maturity models for organizational capabilities. He leads multi-disciplinary teams and has co-authored over 129 research outputs, including 2025 articles in Production Planning & Control and Business & Information Systems Engineering . 2021 : 1st Prize at DESRIST for paper prototype 2022 : 1st Prize for MaaS Platform Features research He supervises PhD candidates Ginger Korsten , Yasmin Rettab , and Stella Lo Giudice , and teaches courses like Digitalization and Enterprise Systems and Green and Digital Transformation . His work bridges academic research with industry consultancy via Cogniton Business Engineering Consultancy.

• Database Information Management
• Big Data Management Systems
• Data Structures
• +۲ مورد دیگر

Ioannis Tsaknakis is an Associate Professor at the Department of Electrical & Computer Engineering, School of Engineering, University of Peloponnese. He holds a PhD in computational geometry and multidimensional data structures from the University of Patras (2004) and has been actively involved in software systems research since 2004. His work spans Database Information Management , Big Data Systems , and Knowledge Mining , with a focus on data structures and computational geometry. Research Interests : Information Management in Databases Big Data Management Systems Computational Geometry Knowledge Mining in Databases/Web Publications highlight his contributions to IoT-driven educational frameworks, machine learning applications, and cryptographic systems for data security. He has taught courses on software design and data management since joining the University of Peloponnese in 2019. Contact : jtsaknakis@uop.gr . Office hours are in Building K (Monday & Tuesday, 8:00-9:00).

Kelly McDonoughمشاهده پروفایل

استاد

• Colonial Literary and Cultural Studies
• Critical Indigenous Studies
• Ethnohistory (Nahuatl Studies)
• +۲ مورد دیگر

Kelly McDonough is a Tomás Rivera Regents Professor and Graduate Adviser at the University of Texas at Austin, affiliated with the College of Liberal Arts. She holds a Ph.D. from the University of Minnesota and specializes in interdisciplinary research bridging Colonial Literary and Cultural Studies, Critical Indigenous Studies, Ethnohistory (Nahuatl Studies), Science and Technology Studies, and Digital Humanities. Ph.D., University of Minnesota Her research focuses on Nahua intellectual production in Mexico over the past 500 years, challenging racialized discourses that exclude Nahuas from intellectual history. Her books The Learned Ones: Nahua Intellectuals in Postconquest Mexico and Indigenous Science and Technology: Nahuas and the World Around Them (2024) explore Nahua theoretical and practical inquiries into their environments across pre-invasion, colonial, and contemporary periods. McDonough leads collaborative digital humanities projects, including the digitization of the Fondo Real de Cholula judicial archive and the Co-PI role in the Unlocking the Colonial Archive initiative, which harnesses AI for Indigenous and Spanish American historical collections. She teaches courses covering global Indigenous media, critical Indigenous studies, and Nahuatl language. Key Research Themes: Indigenous knowledge systems, colonial archives, environmental inquiry, digital humanities methodologies, ethnohistory.

• Software Technology
• Artificial Intelligence
• Educational Software
• +۵ مورد دیگر

Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.

Michelle Perryمشاهده پروفایل

استاد

• Mathematics Education
• Educational Psychology
• Online Learning
• +۳ مورد دیگر

Michelle Perry is a Professor in Educational Psychology at the University of Illinois, Urbana-Champaign, with appointments at the Beckman Institute for Advanced Science and Technology. Her research focuses on children's acquisition of mathematical concepts in elementary classrooms, teacher professional development through online platforms, and equity in STEM education. She has received NSF funding for projects examining gesture-based learning and statistical concept development. Education: Ph.D., The University of Chicago Research Interests: Mathematics education and cognitive development Online learning environments and teacher professional development Equity in STEM for underrepresented students Gesture-speech integration in education Statistical reasoning and virtual manipulatives Scientific Awards: Richard C. Anderson Professor of Cognitive Science of Teaching & Learning Recent Publications: 2025: Gesturing to understand abstract mathematical concepts 2025: Online video instruction and student engagement 2024: Teacher mindset theories and classroom observation skills 2023: Digital help-seeking and social presence Advising & Grants: Mentored NSF-funded projects on teacher development Collaborated with University of Chicago and NYU researchers

• Machine Learning
• Time Series Analysis
• Text Mining
• +۷ مورد دیگر

Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, University College Dublin , where she serves as Director of Graduate Research and Co-Lead of the SFI Centre for Research Training in Machine Learning (ML-Labs). She holds concurrent appointments as an SFI Funded Investigator at the Insight Centre for Data Analytics and VistaMilk SFI Research Centre . Her academic journey includes postdoctoral research at Insight Centre, Cork Constraint Computation Centre (4C), and Aarhus University's Bioinformatics Research Centre (BiRC). Education: BSc in Computer Science, University of Bucharest, Romania MSc and PhD in Informatics, Max-Planck Institute for Informatics, Germany Dr. Ifrim specializes in scalable predictive modeling for diverse applications including: Sequence learning (DNA analysis, time series) Real-time prediction for streaming data (news/social media, energy) Interpretable machine learning models Knowledge graph exploitation (WordNet/Yago, Naga) Wearable sensor data analysis (sports science, health monitoring) Energy price forecasting for sustainable systems Her recent publications focus on time series explainability (TSHAP, tsCaptum), multivariate analysis (scalable channel selection), and healthcare applications (fall detection, walking speed estimation). Key contributions include open-source tools like SEQL (sequence learner) and Twitter-Topics (event detection). Scientific Awards: Winner of SNOW@WWW14 Data Challenge As Director of Graduate Research, she oversees advanced academic training while leading funded projects at the intersection of machine learning , real-time analytics , and domain-specific applications in agriculture, healthcare, and digital journalism. Her research group maintains active GitHub repositories with open-source implementations.

Nicolas Lachicheمشاهده پروفایل

استاد

• Data Science
• Relational Data Mining
• Sequential/Temporal Data Mining
• +۴ مورد دیگر

Nicolas Lachiche is a Professor in Computer Science at the University of Strasbourg, where he serves as Deputy Head of the SDC (Data Science and Knowledge) team within the Engineering, Computer and Imaging Sciences Laboratory (ICube - UMR 7357). His research focuses on machine learning and data/knowledge management across various application domains. Professor Lachiche's primary research interests include data science, relational data mining, sequential and temporal data mining, anomaly detection, and NoSQL databases. His work spans healthcare applications (ICU with Vincent Castelain), high-performance computing (with Florina Ciorba), materials science (with Yves-André Chapuis), and smart factories (with Technology & Strategy). His research trajectory shows evolution from early foundational work in scope classification (94-97) and the PRIMUS family of systems (97-04) to current cutting-edge projects addressing modern data challenges across multiple sectors. Professor Lachiche maintains an extensive service record in the scientific community, having organized numerous workshops and conferences including the MODA series (2020-2024), PFIA 2023 (as Local chair), and various international workshops on data mining and machine learning. He has served on program committees for prestigious conferences such as AAAI (2018, 2020-2024), ECAI, ICDM, and SDM. Additionally, he has reviewed for top journals including Artificial Intelligence Journal, Machine Learning Journal, and IEEE Transactions. His teaching portfolio includes data science, data mining, and machine learning; big data technologies, business intelligence and data warehouses; advanced databases (OLAP, NoSQL, GIS); and foundational courses on databases, data persistence, web programming, and user interfaces.

Ramana V Davuluriمشاهده پروفایل

استاد

• Machine Learning
• Cancer Data Science
• Gene Regulation
• +۴ مورد دیگر

Ramana V Davuluri serves as Professor in the Department of Biomedical Informatics at Stony Brook University's Renaissance School of Medicine. With over 20 years of experience in bioinformatics and computational genomics, he leads research at the intersection of machine learning and cancer genomics, focusing on translating high-dimensional -omic data into clinically actionable insights through statistically rigorous methodologies. Dr. Davuluri's research spans Machine Learning applications in Cancer Data Science , isoform-level gene regulation , and precision-medicine development. His lab pioneers bioinformatics solutions for genomic data interpretation, with emphasis on developing machine learning algorithms that convert NextGen sequencing outputs into experimentally testable discovery models. A core focus involves creating rapid biomarker identification systems from human tissue and blood samples through integrated computational-experimental approaches in systems biology. Analysis of his 2023-2025 publications reveals a dominant trend toward genomic foundation models (e.g., DNABERT variants), multi-omic cancer subtyping , and time-dependent therapeutic strategies for pediatric brain tumors and ovarian cancer. His work consistently bridges computational innovation with biological validation across diverse cancer types including glioma, lung adenocarcinoma, and high-grade serous carcinoma. As Principal Investigator for multiple multi-investigator and multi-site projects, Dr. Davuluri directs research integrating high-throughput experimental procedures with advanced data-mining techniques. His laboratory maintains strong collaborations across oncology, neuroscience, and immunology domains while developing genomics-based decision support systems for clinical translation. The Davuluri Lab employs a systems biology framework to develop novel informatics tools for precision oncology, with particular emphasis on translating genomic discoveries into clinical applications through biomarker discovery and therapeutic strategy optimization.

Silvia Bonomiمشاهده پروفایل

دانشیار

• Cybersecurity
• Distributed Systems
• Blockchain
• +۸ مورد دیگر

Dr. Silvia Bonomi serves as an Associate Professor in the Department of Computer, Control and Management Engineering at Sapienza University of Rome, where she has held academic positions since 2006. Her career progression includes Research Fellow (2010-2011), Tenure Track Assistant Professor (2016-2019), and current Associate Professor appointment since 2019. She maintains her office in Room B114 and is actively engaged in research and teaching within the university's engineering faculty. Her educational background includes: PhD in Computer Engineering, Sapienza University of Rome and Institut de Formation Supérieure en Informatique et Communication (IFSIC/IRISA), Rennes, France (completed under advisors Prof. Roberto Baldoni and Prof. Michel Raynal) Dr. Bonomi's research critically examines dynamic distributed systems where entities autonomously join and leave networks, with applications spanning VANETs, airborne networks, social networks, and distributed cloud services. She pioneers work in Byzantine fault tolerance for mobile environments, blockchain security with emphasis on smart contract vulnerability analysis, and resilient cybersecurity frameworks integrating human factors. Her investigations into publish-subscribe systems focus on quality-of-service enhancements, while her peer-to-peer systems research addresses fundamental connectivity challenges in large-scale decentralized environments. This interdisciplinary approach bridges theoretical distributed computing with practical cybersecurity applications. Analysis of her 15 most recent publications (2021-2024) reveals dominant trends in blockchain security (particularly smart contract vulnerability taxonomies and analysis tool efficacy) and fault-tolerant distributed systems (reliable communication under Byzantine faults in dynamic networks). Her work increasingly integrates human factors into cybersecurity models and develops visual analytics for business-centric risk assessment. Publications span top venues including IEEE CSR, OPODIS, SAFECOMP, and journals like Computers & Security, demonstrating consistent contributions to both theoretical foundations and practical cybersecurity implementations.

• Cognitive Science
• Quantum Theory in Information Modeling
• Learning Analytics
• +۶ مورد دیگر

Kirsty Kitto is an Associate Professor at the University of Technology Sydney in the Learning Design and Technology Unit. With a background in theoretical physics and computer science, her research focuses on developing quantum-inspired models of contextuality to understand complex human behavior in educational systems. She explores the intersection of Artificial Intelligence (AI) , Learning Analytics , and Educational Theory , seeking to bridge the divide between big data and pedagogical frameworks. Current Appointments : Associate Professor (2020-present), Senior Lecturer (2017-2020) Past Academic Roles : Senior Research Fellow (QUT), Senior Lecturer (QUT), Associate Lecturer (Flinders University) Her funded research includes projects on: Quantum models in cognitive systems (ARC Fellowship DP1094974) AI literacy in digital workplaces (IEEE Transactions study) Contextual learning analytics (DVC Education and Students Division) Skills passports for lifelong learning (UMAP 2024 paper) Kitto's recent work examines human-AI interaction in writing assessment, data storytelling for teacher-centered analytics, and causal modeling to strengthen educational theory-data connections. She actively supervises Masters and PhD students and contributes to policy debates through government submissions on generative AI in education. Her methodology combines mathematical formalism with sociotechnical analysis to address educational complexity.

• Artificial Intelligence
• Educational Technology
• Business Process Management
• +۵ مورد دیگر

Darko Etinger is an Associate Professor and currently serves as the Dean of the Faculty of Informatics at Juraj Dobrila University of Pula in Croatia. His academic career spans over two decades with significant contributions to the fields of information systems, educational technology, and artificial intelligence. He teaches undergraduate courses including Artificial Intelligence, Business Information Systems, Business Process Management, ICT Fundamentals, Information Systems, Introduction to Artificial Intelligence, and Multimedia Systems. At the graduate level, he teaches Development of IT Solutions, IT Management, Modelling and Simulation, and Project Management. He also supervises doctoral research in Management of Information Technologies in Education. Dr. Etinger's research interests span several key areas in computer science and education technology. He has made significant contributions to understanding how information and communication technologies can support children with special educational needs, as evidenced by his 2024 and 2025 books on the topic. His work also focuses on business process management, educational data mining, and the application of artificial intelligence in educational contexts. His 2024 book 'Introduction to R and RStudio' demonstrates his commitment to data science education. Analysis of his recent publications shows a strong focus on practical applications of technology in education and business. His work spans educational robotics, learning management systems analysis, business process modeling, and the application of large language models in healthcare. He has a particular interest in how technology can be made accessible and beneficial for diverse learner populations, including those with special needs. His research often takes a human-centered approach, examining not just the technology itself but how it's adopted and used by end users. His 2025 bibliometric analysis of metaverse security demonstrates his ability to tackle emerging technological challenges. Associate Professor at Faculty of Informatics, Juraj Dobrila University of Pula Current Dean of Faculty of Informatics Author of multiple publications on educational technology and information systems Supervisor for numerous graduate theses on educational technology topics Active participant in EDIH Adria project as evidenced by 2025 publications Researcher in educational robotics implementation in Croatian schools Dr. Etinger has advised numerous students completing their theses, with a focus on educational technology applications. His research has been published in various international conferences and journals including IEEE Engineering Management Review, Procedia Computer Science, and System Dynamics Review. His current research appears to be heavily focused on the EDIH Adria project, which is a European Digital Innovation Hub initiative focusing on technology transfer and business innovation. He maintains an active research program with publications spanning from 2003 to the present, demonstrating sustained scholarly contribution to his fields of expertise.

• Artificial Intelligence
• Mobility and Transport
• Traffic (road)
• +۱۳ مورد دیگر

Eric C. van Berkum is a Full Professor at the Digital Society Institute and Transport Engineering and Management. His research spans Artificial Intelligence, Mobility and Transport, and Intelligent Transport Systems, with a focus on optimizing traffic networks, public transport efficiency, and railway maintenance scheduling. He contributes to UN Sustainable Development Goals (SDGs) related to environmental resilience and social safety in transport systems. Expertise in Equilibrium Traffic Models and Stochastic Modelling Active in Data Mining, Machine Learning, and Network Analysis Key themes: Dynamic Traffic Management, Infrastructure Optimization, and Passenger Behavior His recent work addresses railway maintenance scheduling, shared demand-responsive transit, and passenger rerouting in capacitated systems. He has received a Best Paper Award (2017) and served on editorial boards, including Tijdschrift vervoerswetenschap (2014–2017). He organized the E-COST Summer School on Autonomous Road Transport Systems (2014) and contributed to IEEE conferences as a program committee member.