جستجوی استاد راهنمای دانشگاهی

Miloš Mravikمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +۳ مورد دیگر

Miloš Mravik is an academic affiliated with Singidunum University's Faculty of Informatics and Computing, specializing in research involving artificial intelligence, cybersecurity, and data science. He holds a doctoral degree in 'Advanced Protection Systems' from Singidunum University (2020–2023), preceded by a Master’s in 'Contemporary Information Technologies' (2018–2019) and a Bachelor’s in 'Informatics and Computing' (2014–2018). His work emphasizes applying machine learning techniques to real-world challenges like healthcare diagnostics, cybersecurity frameworks, and pandemic-era education systems. Research Interests: AI-driven cybersecurity solutions for IoT and blockchain Machine learning applications in health informatics Optimization of predictive algorithms using metaheuristics E-learning strategies during crises Recent articles focus on explainable AI for metaverse security, sentiment analysis using BERT models, and blockchain node detection via XGBoost. His work bridges theoretical computer science with practical applications in emergency education and pandemic response. No scientific awards listed. Advised no formally registered students. Active in conference organizing and software prototyping, as seen in projects like a scheduling web application and network management systems.

• Mineralogy
• Crystallography
• High-Pressure Geoscience
• +۳ مورد دیگر

Dr. Jun Wu is an Assistant Professor in the School of Molecular Sciences and School of Earth and Space Exploration at Arizona State University (ASU). His research focuses on mineralogy, crystallography, and high-pressure geoscience using transmission electron microscopy (TEM). He developed the HPTEM (high-pressure TEM) technique, enabling in-situ analysis of Earth's interior under extreme conditions. Dr. Wu collaborates on the Keck Foundation-funded project exploring Earth’s water origins and investigates nano-material synthesis and deep earthquakes. He holds a Ph.D. in Mineralogy from Johns Hopkins University and postdoctoral training under Prof. Peter Buseck at ASU. Education : Ph.D., Mineralogy, Johns Hopkins University. Research Interests : Dr. Wu’s work bridges geoscience and materials science through advanced TEM applications. His HPTEM technique uses carbon nanostructures to simulate Earth’s high-pressure environments, advancing understanding of planetary formation and deep Earth processes. He also explores nanomaterials synthesis and unresolved geological phenomena like deep earthquakes. Grants : Active funding from the Keck Foundation for origins-of-water research. Collaborative projects integrate experimental and computational approaches in Earth sciences. Labs/Teams : Engaged in cross-disciplinary teams at ASU’s School of Molecular Sciences and Earth and Space Exploration, leveraging cutting-edge microscopy facilities for high-pressure experiments.

Muhammed-Ugur Karagülleمشاهده پروفایل

پژوهشگر

• Medical Informatics
• AI in Healthcare
• Mobile Health (mHealth)
• +۳ مورد دیگر

Muhammed-Ugur Karagülle is a Researcher at the Institute of Computer Science, Department of Databases and Information Systems at Freie Universität Berlin. His work focuses on developing AI-driven healthcare solutions and information systems for medical and veterinary applications. He is affiliated with the university's research group specializing in databases and information systems, contributing to advanced projects such as AINA, SurgeRate, and mHealthAtlas. Research interests include medical informatics, mobile health (mHealth) platforms, veterinary diagnostics systems, and AI integration in healthcare workflows. His projects address challenges in disease diagnosis (e.g., schistosomiasis), surgical performance evaluation, and regulatory frameworks for digital health applications. Key contributions include the design of HaLowNet (a WiFi-based emergency healthcare system), the PRECOSE grayscale conversion method for medical scoring boards, and collaborative platforms like mHealthAtlas for evaluating mHealth applications. His work emphasizes interdisciplinary collaboration and human-centered design principles. Currently, he is involved in projects such as XRay2Model, mCIS.vet (mobile clinical information systems for veterinary medicine), and process optimization for digital health applications. Office hours are held weekly, requiring prior email registration.

• Big Data
• Cloud Computing
• Data Management
• +۷ مورد دیگر

Dr. George Yu is an Associate Professor of Computer Science and Information Systems at Youngstown State University (YSU), Ohio. He holds a Ph.D. in Computer Science from Southern Illinois University (2013), an M.S. in Pure Mathematics from Shandong University (2008), and a B.S. in Information and Computation Science from Northeastern University (2005). As the Campus Champion of NSF XSEDE at YSU, he facilitates access to national supercomputing resources and organizes workshops on High-Performance Computing (HPC). His research focuses on Database Systems , Approximate Query Processing (AQP) , Big Data Analytics , Cloud Computing , and Bioinformatics . Notable contributions include the AQPrius framework for error-aware AQP and collaborative work on genomic data analysis in plants like Aspergillus niger and tomato. Dr. Yu has received multiple recognitions, including the 2020 Distinguished Professor in Scholarship at YSU and the 2019 Best Paper Award at the International Conference on Software Engineering and Data Engineering. He serves as an associate editor for journals like Transactions on Large-Scale Data and Knowledge-Centered Systems and actively contributes to conference program committees. His educational initiatives include developing YSU's Data Analytics (DATX) Certificate Program and teaching courses on databases, cloud computing, and blockchain. He leads the YSU Data Lab, which operates high-performance research clouds like Sarah Cloud and YSU STEM Cloud, and mentors students in NSF-funded research projects.

• Algorithms
• Graph Neural Networks
• Problem decomposition techniques
• +۴ مورد دیگر

Matthias Paul Lanzinger is an Assistant Professor at the Technische Universität Wien's Faculty of Informatics, Department of Database and Artificial Intelligence. His research focuses on algorithms, graph neural networks, hypergraph decomposition techniques, parameterized complexity, and computational logic. He leads projects like 'DeConquer' (Vienna Science Fund) and 'HyperTrac', exploring efficient query processing and hypergraph-based algorithms. Research interests include theoretical computer science, database systems, and applying logical frameworks to solve complex computational problems. Recent work emphasizes hypertree decompositions, fuzzy Datalog, and graph motif analysis via the Weisfeiler-Leman test. He co-edited the 2024 Datalog-2.0 workshop proceedings and has supervised students on topics like column-store performance and graph query languages. His publications span venues like ACM Transactions on Database Systems, ICLR, and IJCAI, highlighting contributions to algorithmic efficiency, database theory, and logical reasoning systems. Active in academic service, he teaches courses on database systems, scientific research, and advanced topics in informatics.

• Machine Learning
• Spatial Data Mining
• AI in Mental Health
• +۴ مورد دیگر

Dr. Saida Elmi is an Assistant Professor Adjunct at Yale University School of Medicine and an Assistant Professor at the University of New Haven. She holds a Ph.D. in Computer Science from the National School of Mechanics and Aerotechnics (2017), followed by postdoctoral research at Korea University of Technology and Education (2017–2018) and National University of Singapore (2018–2021). Her research focuses on AI applications in healthcare, transportation systems, and spatial data mining. She developed the Automated Test of Embodied Cognition (ATEC), an AI-driven system using motion capture and machine learning for mental disease detection. Key contributions include predicting taxi fares, travel times, and energy consumption in transportation networks using deep learning architectures like RNNs and CNNs, and designing group-oriented recommendation systems for points-of-interest (POIs) using graph convolution networks and attention mechanisms. Education : Ph.D., Computer Science, National School of Mechanics and Aerotechnics (2017) Postdoctoral Research, Korea University of Technology and Education (2017–2018) Postdoctoral Research, National University of Singapore (2018–2021) Her research interests span machine learning, spatial data mining, and AI ethics. She has pioneered frameworks for spatio-temporal data analysis, including a transfer learning approach for travel time prediction in data-scarce regions. Her work on energy consumption modeling and POI prediction has been published in top-tier conferences like WWW, MOBIQUITOUS, and ECIR. Dr. Elmi’s interdisciplinary projects integrate AI with healthcare and urban systems, emphasizing automated cognitive assessment and smart city technologies. Her current efforts focus on refining action recognition algorithms for clinical applications and optimizing recommendation systems for group mobility decisions.

• Neural Modeling
• Computational Neuroscience
• Neuroscience
• +۳ مورد دیگر

Michael Hines is a Senior Research Scientist in the Department of Neuroscience at the Yale School of Medicine. His work focuses on developing and optimizing computational tools for neural modeling, notably the NEURON simulation environment. This software enables researchers to model cellular and network mechanisms involved in neurological disorders and therapeutic interventions. Hines holds a PhD from the University of Chicago (1975) and has contributed extensively to computational neuroscience through software development and interdisciplinary collaboration. Education: PhD, University of Chicago, 1975 MS, Physics, University of Chicago, 1972 BS, Physics, Michigan State University, 1970 His research interests revolve around advancing computational methods for simulating neural systems, including the development of dynamic clamp techniques and real-time interfacing with living cells. He has collaborated with institutions globally to enhance the scalability and accuracy of NEURON for supercomputing environments. Hines' work bridges neuroscience, mathematics, and computer science, addressing challenges in modeling complex neural networks and their applications to disease mechanisms. Publications highlight his contributions to neural simulation software, error analysis in computational models, and interdisciplinary tools like ModelDB and SenseLab. His research underscores the integration of experimental and computational approaches to advance understanding of neurological disorders and therapeutic strategies. Labs/Teams: Hines leads the development of the NEURON Simulation Environment and contributes to collaborative projects in computational neuroscience at Yale.

Minos Garofalakisمشاهده پروفایل

استاد

• Big Data Analytics
• Private Data Analytics
• Machine Learning
• +۳ مورد دیگر

Minos Garofalakis is a Professor at the School of Electrical and Computer Engineering , Technical University of Crete, and serves as Director of the Information Management Systems Institute at the Athena Research & Innovation Center in Athens. He has held senior research roles at Bell Labs, Intel Research, Yahoo! Research, and academic positions at UC Berkeley as an Adjunct Associate Professor. Currently, he is a Senior Research Consultant at Huawei Edinburgh Research Center and co-founder of Agora Labs , focusing on medical data privacy. Research Interests His work centers on Big Data Analytics , encompassing private data analytics , machine learning , federated analytics , and blockchain systems . He has pioneered advancements in data stream management , query optimization , and approximation algorithms , with applications in distributed systems and privacy-preserving technologies. Scientific Awards ACM Fellow (2018) IEEE Fellow (2017) Excellence in Research Award, Technical University of Crete (2015) FP7 Marie-Curie International Reintegration Fellowship (2010-2014) Bell Labs President’s Gold Award (2004) Central Bell Labs Teamwork Award (2003) Patents and Citations Garofalakis holds 29 issued US patents (36 filed) with applications in data management and analytics. His research has garnered over 16,000 citations on Google Scholar and an h-index of 69.

Christiane Bergerمشاهده پروفایل

دانشیار

• Occupant-Centric Building Design
• Building Performance Simulation
• Indoor Environmental Quality
• +۳ مورد دیگر

Christiane Berger is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology within the Technical Faculty of IT and Design. Her research focuses on occupant-centric building design, building performance simulation, and indoor environmental quality, particularly through initiatives like IEA-EBC Annex 79. She leads or participates in multiple projects, including collaborations with C.F. Møller Architects and the International Energy Agency on human-centric buildings and climate resilience. Her work integrates sustainability, digital transformation, and resilience against disruptive events. Key projects include Joint Collaboration on 'Integrated Design of High-Performance Buildings' (2025–) IEA EBC - Annex 95 (2024–2029) ActRes: Agency for Resilience (2023–2025) Research emphasizes occupant behavior modeling, energy efficiency, and multi-domain environmental standards. Awards include the 2023 Building and Environment Best Paper Award and 2021 IBPSA Outstanding Young Contributor Award. Her teaching involves cross-semester collaborations on sustainability and universal design. Labs/teams include the Centre for Sustainable and Digital Transformation and Human Building Interaction initiatives. Over 70+ publications (2019–2025) address thermal comfort, energy performance, agent-based modeling, and occupant-centric standards.

Fernando Pedoneمشاهده پروفایل

استاد

• Dependable Distributed Systems
• Distributed Algorithms
• Distributed Data Management Systems
• +۶ مورد دیگر

Fernando Pedone is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), leading the Computer Systems Institute (SYS). He holds a Ph.D. in Computer Science from EPFL (1999). His research focuses on dependable distributed systems, distributed algorithms, and fault-tolerant data management. Pedone has authored over 70 papers and co-edited 'Replication: Theory and Practice.' Roles: Full Professor, SYS Director Affiliations: USI, Swiss National Science Foundation (SNSF), Interchain Foundation Teaching: Distributed Algorithms, Distributed Systems, Operating Systems Research interests span atomic multicast protocols, state machine replication, blockchain synchronization, and consensus algorithms. His work bridges theoretical foundations with practical implementations, emphasizing scalability and fault tolerance. Pedone's projects are sponsored by entities like SNSF, CTI, and Microsoft Research. Notable contributions include 'Heron' (shared-memory state replication), 'PrimCast' (atomic multicast), and studies on blockchain state synchronization. His lab oversees over 20 PhD students, with alumni holding roles in academia and industry. Grants and collaborations include partnerships with the Hasler Foundation, European Commission, and Western Digital Research. Pedone actively participates in conferences like Middleware, DSN, and EuroSys.

Zheying Zhangمشاهده پروفایل

مدرس

• Requirements Analysis
• Domain Modelling
• Quality Assurance
• +۱۰ مورد دیگر

Zheying Zhang is a Lecturer at Tampere University within the Faculty of Information Technology and Communication Sciences , Department of Computing Sciences . She holds a Ph.D. in Computer Science and Information Systems from the University of Jyväskylä (2004) and was awarded a Docent (Adjunct Professor) title in Software Development from the University of Tampere (2013). Education: Ph.D. (2004), Docent (2013) Her research focuses on Requirements Engineering , with specific interests in Requirements Analysis Domain Modelling AI-Assisted Requirements Management Software Quality Assurance Process Improvement Data-Driven Software Development Medical Device Software Current Master's thesis topics include AI for Software Engineering, DevOps pipelines, and cross-disciplinary software ethics. Recent publications highlight trends in AI applications for requirements management, software evolution analysis , and accessibility testing . She actively supervises PhD candidates like Xiaozhou Li and Wenhui Lu, with works spanning open-source projects and medical software quality. Scientific Contributions: 54 research outputs (2003-2025), including 3 2025 conference papers

Tom Johnstenمشاهده پروفایل

استاد

• Data Mining Algorithms
• Computational Biology
• Machine Learning Applications

Dr. Tom Johnsten is a Professor in the Computer Science Department at the University of South Alabama, part of the School of Computing. He holds a Ph.D. in Computer Science from the University of Louisiana at Lafayette (1998), an M.S. in Computer Science from Arizona State University (1992), and a B.S. in Mathematics from Oklahoma State University (1987). His research focuses on developing data mining algorithms, computational biology, and applying machine learning technologies to interdisciplinary challenges. His work bridges computational methods with biological systems, cybersecurity, and environmental data analysis. Notable contributions include advancements in DNA repair mechanisms, anomaly detection in data streams, and prescriptive maintenance frameworks. He has taught courses such as Digital Logic and Computer Architecture, Operating Systems, Programming Language Theory, and Data Mining. His office is located in Shelby Hall, Room 1119, with regular office hours on Tuesdays and Thursdays. Dr. Johnsten’s publications reflect a strong emphasis on cybersecurity, bioinformatics, and data-driven solutions. He has explored topics like mitochondrial DNA repair, robotic system security, and synthetic signal peptide design. While no scientific awards are explicitly listed, his extensive publication record highlights sustained academic contribution. Teaching and advising roles include mentoring students through courses like Research Methodologies and Database Design. His work integrates theoretical computer science with practical applications in diverse fields.

Axel Polleresمشاهده پروفایل

استاد

• Semantic Web
• Knowledge Engineering
• Data Management
• +۱۲ مورد دیگر

Axel Polleres is a full professor in the area of 'Data and Knowledge Engineering' at the Vienna University of Economics and Business (WU Wien) and a faculty member at the Complexity Science Hub (CSH) in Vienna, a position he has held since January 2017. His work bridges academic research and real-world applications in semantic technologies, knowledge graphs, and data governance. His research interests lie at the intersection of semantic web technologies, knowledge engineering, and data management. Focused on querying and reasoning over ontologies, logic programming, and rule-based systems, he explores how structured data can be effectively managed, validated, and integrated—especially through standards like SPARQL and SHACL. His work extends to applications in open data, legal data, biomedical informatics, and socio-environmental challenges such as climate and public health. The most recent publications highlight a growing trend toward practical and societal applications of knowledge graphs, including climate risk assessment, crisis response, healthcare accessibility, and open data governance. These works combine technical rigor in semantic modeling with impactful real-world use cases, particularly in European and Austrian contexts. Axel Polleres has been actively involved in international standardization, notably as co-chair of the W3C SPARQL Working Group, and serves on the editorial boards of the Semantic Web Journal and Journal of Web Semantics . He has contributed to numerous European and national research projects and has published over 100 articles in top-tier journals and conferences. He advises and collaborates with researchers across disciplines and institutions, contributing to interdisciplinary teams working on complex societal challenges. His work is supported by significant research grants, though specific funding sources are not detailed in the provided text. He leads and participates in research groups focused on semantic technologies, knowledge graphs, and data-driven policy.

Clemens Reichelمشاهده پروفایل

دانشیار

• Near Eastern Archaeology
• Rise of urbanism in the ancient Near East
• Emergence of bureaucratic complexity
• +۲ مورد دیگر

Clemens Reichel is an Associate Professor of Mesopotamian Archaeology at the University of Toronto's Department of Near and Middle Eastern Civilizations. His research spans the ancient cultures of Sumer, Assyria, and Babylonia, with a focus on urban development, bureaucratic systems, and conflict management in the Near East. Ph.D., University of Chicago (2001) Reichel's work integrates archaeological fieldwork and textual analysis to explore early urbanism, administrative complexity, and warfare. He co-directed excavations at Hamoukar (Syria) and leads the digital publication of the University of Chicago's Diyala Expedition artifacts. His current projects aim to investigate urban emergence at Tell al-Uqair (Iraq). His publications examine topics such as the Gutians in Mesopotamian scholarship, palace functions at Tell Asmar, and bureaucratic systems in early societies. Recent trends in his work emphasize cross-cultural interactions, digital archiving, and the societal implications of warfare and resource competition.

• Semantic Web
• Energy Load Forecasting
• Database Systems
• +۳ مورد دیگر

Dr. Monika Kaczmarek is a faculty member at the Department of Economic Informatics , part of the Faculty of Informatics and Electronic Economy at the Poznań University of Economics and Business . Her work focuses on semantic technologies, expert finding systems, and energy load forecasting. She has collaborated on research projects like Insemtives and ASG , and contributed to conferences such as ADBIS, eKnow, and ICEIS. Key research areas: Semantic Web, Database Systems, Information Retrieval Notable award: Best Paper Award at eKnow2011 Her publications span topics in semantic expert systems and real-time energy forecasting, with a focus on ontologies, scalable retrieval, and mobile applications. Collaborations include institutions like SAP AG and Technical University of Munich.