جست‌وجوی استاد و پژوهشگر

• Databases
• Information Systems
• Data Management
• +۹ مورد دیگر

Johann Eder is a full professor for Information and Communication Systems at the Department of Informatics Systems, University of Klagenfurt, Austria, and currently serves as Deputy Head of Department. He previously held positions at the Universities of Linz, Hamburg, Vienna, and Klagenfurt, and was Vice President of the Austrian Science Funds (FWF) from 2005-2013. He was also a visiting scholar at AT&T Shannon Labs, NJ. Educational Background: Diplom-Ingenieur, University of Linz Doctor of Technical Sciences, University of Linz Johann Eder's research focuses on databases, information systems, and data management for medical research, including temporal information modeling, process evolution, and workflow systems. His work spans temporal data warehousing, exception handling in workflows, and application interoperability, with a particular emphasis on privacy and quality in medical data lakes and federated biobanks. Recent publications highlight trends in temporal reasoning for business processes, medical data quality, and service composition optimization. His editorial roles include positions at ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering . He leads the Information and Communication Systems Research Group at AAU, contributing to projects like federated biobank integration and blockchain-based smart contracts.

Vladimir Vlassovمشاهده پروفایل

استاد

• Machine Learning
• Data-intensive computing
• Cloud computing
• +۷ مورد دیگر

Dr. Vladimir Vlassov is a full Professor in Computer Systems at the Division of Software and Computer Systems (SCS) , Department of Computer Science (CS) , School of Electrical Engineering and Computer Science (EECS) , KTH Royal Institute of Technology , Stockholm, Sweden. He leads the AVA project in ALEC2, an AI-powered system for mental health care. He is a member of the Distributed Computing research group (DC@KTH) . Education & Roles: Holds a PhD and is a member of ACM and IEEE. Previously visited MIT (1998) and UMass Amherst (2004). Teaches courses on Data Mining , Distributed Systems , and Concurrent Programming . Research Interests: Focus on scalable AI, Cloud computing, distributed systems, and NLP for mental health. Projects include ExtremeEarth (Copernicus data analytics) and EMJD-DC (distributed computing PhD program). Grants & Projects: Principal Investigator in ALEC2 (adaptive mental health care) and ExtremeEarth (EU H2020). Led EU projects like ENCORE (manycore systems) and PaPP (embedded systems). Labs & Teams: Directs the Distributed Computing group, contributing to Hopsworks (machine learning feature store) and Maggy (hyperparameter optimization).

• Database Systems
• Distributed Systems
• Cloud Computing
• +۴ مورد دیگر

Dr. Kenneth Salem is a Professor at the University of Waterloo, Canada , with a distinguished career spanning over three decades in database systems, distributed computing, and data management. His work has significantly influenced transaction processing, replication, and scalability in modern databases. Institution: University of Waterloo Collaborations: Frequent co-author with Hector Garcia-Molina, Ashraf Aboulnaga, Umar Farooq Minhas, Khuzaima Daudjee Research Interests: Dr. Salem’s research focuses on database systems, particularly in transaction processing , distributed databases , cloud computing , and energy-efficient data storage . He has pioneered techniques for schema design in NoSQL , adaptive caching , and RDMA-based data transfer . His work often addresses challenges in high availability , workload-aware optimization , and cardinality estimation . Recent Article Trends: His latest publications (2023-2025) explore ad hoc transactions , eventual durability , and summary-based cardinality estimation , emphasizing practical solutions for real-world database scalability and consistency. Earlier works (2018-2022) covered memory power optimization , RDMA abstractions , and workload-aware CPU scaling , reflecting a sustained focus on performance and efficiency. Advising and Collaborations: Dr. Salem has mentored numerous co-authors in database research, including Ashraf Aboulnaga, Umar Farooq Minhas, and Khuzaima Daudjee. His collaborative projects span Apache Spark caching , RemusDB high availability , and DimmStore memory optimization . Labs and Teams: He has been a key contributor to the DaMoN and Versatile Database Systems workshops, focusing on hardware-aware database design. His work with teams at Waterloo and collaborations with institutions like ETH Zurich and MIT has advanced self-managing databases and edge replication technologies.

Olaf Hartigمشاهده پروفایل

دانشیار

• Database Systems
• Semantic Web
• Data Management
• +۵ مورد دیگر

Olaf Hartig is a Senior Associate Professor at Linköping University's Department of Computer and Information Science (IDA), affiliated with the Database and Information Techniques (ADIT) division. He is also an Amazon Scholar collaborating with the Neptune graph database team. His research focuses on data management, semantic web technologies, graph databases, and distributed data systems. Hartig holds a PhD from Humboldt-Universität zu Berlin and is a Docent at Linköping University. He has received numerous awards, including the SWSA Distinguished Dissertation Award and eight best paper awards, and was selected as a Wallenberg Academy Fellow in 2024. Education: PhD in Computer Science (Humboldt-Universität zu Berlin), Docent (Linköping University). Research interests span query processing for Linked Data, federated systems, RDF and GraphQL semantics, and knowledge graph construction. He leads research groups in Database and Web Information Systems and Semantic Web Technologies at IDA. Key achievements include pioneering traversal-based query execution, developing Triple Pattern Fragments, and contributions to standards like RDF* and SPARQL*. His work has been recognized through grants, patents (e.g., on graph acceleration techniques), and leadership roles in conferences like ISWC and ESWC. Teaching: Course leader for database technology courses (TDDD12, TDDD37) and advanced topics like big data analytics and bioinformatics databases. Active in curriculum design and interdisciplinary education. Labs/Teams: Database and Web Information Systems Group, Semantic Web Research Group, Sports Analytics Group (IDA) Grants: Wallenberg Academy Fellowship, Swedish Research Council funding

Ewilly Liewمشاهده پروفایل

مدرس ارشد

• Digital Transformation
• Emerging Technology Adoption
• Public Healthcare Analytics
• +۴ مورد دیگر

Dr. Ewilly Liew is a Senior Lecturer at the Econometrics and Business Statistics Department of Monash University's Malaysia School of Business. She holds multiple administrative roles, including Director of Undergraduate Studies, Course Director for Bachelor of Business and Commerce (BBusCom), and Deputy Course Director for Bachelor of Digital Business (BDigBus). Her academic journey includes a Postgraduate Research Degree Full Scholarship (2013-2015) and a Data Science Microcredential from Monash Australia (2020). Dr. Liew has received notable awards like the Monash Vice Chancellor's Citation for Outstanding Contribution to Student Learning (2020). Her research focuses on emerging technology adoption, digital transformation, and behavioral analysis in public healthcare, higher education, and service sectors. Methodologies include data visualization, statistical learning, and structural equation modeling. She has led interdisciplinary projects on AI-driven healthcare analytics and collaborated with clinical specialists using Electronic Medical Records systems. Internationally, she served as a visiting research fellow at Harvard University (2015) and organized the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2022). Dr. Liew's teaching innovations include developing four new Business Analytics units. Her students excel in national and regional data science competitions. She actively participates in conferences and workshops, contributing to topics like geopolitical data security and healthcare service quality decision analytics. Her work aligns with UN Sustainable Development Goals, emphasizing thriving communities in developing contexts.

• Obstetric Anesthesiology
• Pain Management
• Perioperative Medicine
• +۳ مورد دیگر

Dr. Kristen L. Fardelmann is an Assistant Professor of Anesthesiology at Yale School of Medicine and Yale New Haven Hospital. She holds a medical degree (MD) from the University of Connecticut (2013) and a BS in Molecular and Cell Biology from the same institution. Dr. Fardelmann completed her Anesthesiology residency at New York Presbyterian-Weill Cornell Medical Center (2017) and a fellowship in Obstetric Anesthesiology at the University of North Carolina Chapel Hill (2018). Her research focuses on obstetric anesthesia, perioperative pain management, maternal-fetal medicine, and critical care in pregnancy. Key areas include optimizing cesarean delivery analgesia, managing opioid use disorders during pregnancy, and applying rotational thromboelastometry (ROTEM) to assess coagulopathy in obstetric populations. She has also contributed to studies on SARS-CoV-2 placental infection and rare vascular anomalies in pregnancy. Dr. Fardelmann’s publications emphasize clinical practice improvements, such as refining anesthesia protocols for cesarean sections and non-obstetric surgeries in pregnant patients. She collaborates with experts in cardiology, infectious disease, and maternal-fetal medicine to address complex peripartum challenges. Her work bridges clinical care and translational research, aiming to enhance patient safety and outcomes in high-risk obstetric scenarios. Professional certifications include Board Certification in Anesthesiology (American Board of Anesthesiology, 2018). Her research has been published in journals like Anesthesiology , Obstetric Anesthesia Digest , and Journal of Clinical Monitoring and Computing .

Pingbo Tangمشاهده پروفایل

دانشیار

• Civil Engineering
• Remote Sensing
• Human Systems Engineering
• +۵ مورد دیگر

Pingbo Tang is an Associate Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University, affiliated with the College of Engineering. He leads the Spatiotemporal Workflows and Resilient Management Laboratory (SWARM Lab). Tang holds a Ph.D. from Carnegie Mellon University (2009), a Master’s in Bridge Engineering from Tongji University (2005), and a Bachelor’s in Civil Engineering from Tongji University (2002). His research focuses on civil infrastructure operations, human systems engineering, and AI-driven solutions for predictive management. Key areas include remote sensing, data analytics, and Human-Cyber-Physical-Systems (H-CPS) in construction and infrastructure (e.g., airports, nuclear plants). He has published over 100 peer-reviewed articles and secured funding from NSF, DOE, NASA, and industry partners. Tang is a leader in professional organizations, including ASCE (Computing Division Chair), TRB (Bridge Management Committee), and ASTM International. He has received prestigious awards, including the NSF CAREER Award (2015), ASCE Halpin Award (2020), and multiple best-paper honors. His work integrates AI, digital twins, and safety innovation, with applications in aviation scheduling (e.g., Alaska Airlines collaborations) and nuclear power plant operations. Tang’s research emphasizes sustainable infrastructure, safety, and interdisciplinary solutions for complex systems.

• Cyberinfrastructure
• Collaborative Work
• Virtual Organizations
• +۶ مورد دیگر

Thomas Finholt serves as the Dean of the School of Information at the University of Michigan . His academic work focuses on the intersection of people, information, and technology , with particular emphasis on creating inclusive environments for collaborative research. Current leadership role: Dean of the School of Information Core research areas: Cyberinfrastructure, virtual organizations, distributed teams Key contributions: Studies on data sharing, collaboration technology, and science policy His article trends reflect a deep engagement with cyberinfrastructure design , collaborative systems , and data governance across scientific domains. The research spans from virtual team dynamics to economic models for resource allocation in digital environments. Finholt has no explicitly listed scientific awards in the provided text but maintains active involvement in advising and grants through projects like the NSF CAREER grant on networked ecological sciences. His lab and team work focuses on large-scale scientific collaboratories, including the Upper Atmospheric Research Collaboratory (UARC) and earthquake engineering cyberinfrastructure.

• Cloud Computing
• Distributed Computing
• Parallel Computing
• +۱۰ مورد دیگر

Professor Javid Taheri is a leading academic at Karlstad University (2019–present), previously serving as Associate Professor (2015–2019) and Senior Lecturer (2015). His research focuses on cloud computing, edge computing, distributed systems, and AI-driven networking. He holds a Ph.D. in Information Technologies from The University of Sydney (2007) and an M.Sc./B.Sc. in Electrical Engineering from Sharif University of Technology (2000/1998). Research interests include cloud-edge continuum systems , resource optimization , 5G/6G networking , and AI for IoT . Notable contributions include frameworks like PerfSim (microservice performance simulation) and MultiScaler (auto-scaling for cloud applications). Publications highlight innovations in edge computing optimization, security for distributed systems, and machine learning for resource management. He has co-authored over 150 papers across top venues like IEEE Transactions and ACM conferences. Academic leadership includes roles as conference chair (IC2E 2023) and editorial work for journals on cloud and edge computing.

• Database Systems
• Healthcare Information Systems
• Artificial Intelligence
• +۵ مورد دیگر

Carlo Combi is a Full Professor at the Department of Computer Science, University of Verona. He serves as Department Director and holds roles in various academic committees, including the Faculty Board of PhD in Computer Science and the Computer Science Teaching Committee. His research focuses on databases, healthcare information systems, temporal data mining, and business process management. He leads the STARS laboratory and has contributed to projects like PREPARE (prostate cancer evaluation) and EDIPO (neuroimaging genetics). His teaching spans courses on biomedical databases, software engineering, and Python programming. Combi's work integrates ethical considerations into process models and addresses challenges in healthcare workflows, temporal analytics, and AI applications in medicine. Education: Not explicitly listed in provided texts. Research Projects: Includes 30+ projects since 2008, emphasizing healthcare informatics, temporal systems, and data warehousing. Labs/Teams: STARS (Semistructured Temporal clinical Geographical Systems) and collaborations with CBMC (Computational Biomedicine Center). Grants: Multiple national/international grants, including funding for temporal data mining and healthcare process modeling. Awards: None explicitly mentioned, though his leadership roles and extensive publications highlight academic recognition. His research bridges clinical processes, temporal databases, and AI, with applications in acute kidney injury prediction, BPMN extensions for healthcare, and explainable AI in medical systems. Combi actively contributes to open-source solutions for clinical data analysis and integrates ethical frameworks into process management.

Kwasi Gyau Baffour Awuahمشاهده پروفایل

پژوهشگر ارشد

• Land use planning and urban development processes
• Land/property & natural resource administration and management
• Heritage Conservation & Management
• +۵ مورد دیگر

Dr Kwasi Gyau Baffour Awuah is an interdisciplinary academic and practitioner with over 22 years of international experience in real estate, urban development, and sustainability across developing and developed contexts. Currently based at THINKlab, University of Salford, he leads the real estate research and consultancy cluster while teaching urban development modules. His educational qualifications include: PhD in Economic Analysis of Spatial Planning & Management Systems PG Cert. in Academic Practice in Higher Education (PCGAP) MA in Development Studies BSc (Hons) in Land Economics Professional Diploma in Real estate surveying & valuation Certificate in Cradle-to-Cradle (C2C) Professional Certificate in Alternative dispute resolution Dr Awuah's research spans land administration, heritage conservation, urban governance, sustainable development, and property valuation, with particular focus on African urban contexts. His work bridges theoretical frameworks with practical policy implementation, addressing challenges in informal settlements, infrastructure financing, and sustainable resource management. Recent publications (2021-2024) demonstrate a pronounced shift toward digital heritage conservation (HBIM applications in Jordan), stakeholder dynamics in Nigerian water systems, and sustainable housing solutions. His interdisciplinary approach integrates urban planning, digital technologies, and governance frameworks to tackle complex sustainability challenges in rapidly urbanizing regions. No scientific awards were explicitly mentioned in the source material. Dr Awuah has supervised over 50 student dissertations across degree levels and serves as an external examiner for multiple universities. His research attracts substantial funding from: RICS (Property Valuation Practice in Sub-Saharan Africa) DFID (Urbanisation and Infrastructure Research Programme) EU (INTERREG IVB C2C BIZZ project) AHRC (Digital Heritage in India) Royal Academy of Engineering (Jordanian Heritage Conservation) As leader of the real estate research cluster at THINKlab, he directs a multidisciplinary team conducting internationally collaborative projects with academic institutions, government bodies, and industry partners across Africa, Europe, and Asia.

Elena Rizaمشاهده پروفایل

استاد

• Public Health
• Epidemiology
• Global Health
• +۷ مورد دیگر

Elena Riza is a Professor and Public Health Specialist at the Department of Hygiene, Epidemiology, and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens. She holds advanced degrees including a PhD in Epidemiology from the London School of Hygiene and Tropical Medicine. Her roles include coordinating and teaching in undergraduate and postgraduate programs such as 'Occupational, Environmental and Pharmaceutical Risk Assessment and Management.' She focuses on epidemiology, public health policy, and global health crises, particularly addressing vulnerable populations like refugees and migrants. Educational background: Master’s in Public Health (University of Dundee), PhD in Epidemiology (LSHTM), and additional certificates in Forced Migration (University of Oxford), Health in Humanitarian Crises (LSHTM), and Bioethics (Johns Hopkins University). She teaches epidemiology, global health, and research methodology across multiple programs. Research interests center on migrant/refugee healthcare access, health equity, disaster medicine, and occupational/environmental risk assessment. She leads projects such as the Mig-HealthCare initiative to reduce health disparities among migrants in Europe. Her work spans telemedicine sustainability, pandemic response strategies, and environmental health interventions. Publications emphasize refugee healthcare utilization, pandemic policy, and health equity. She actively contributes to humanitarian actions, serves on Médecins Sans Frontières, and reviews for scientific journals. Her work bridges academic research with real-world applications to improve population health outcomes globally.

Anna Goldenbergمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence in Healthcare
• Biomedical Informatics
• +۳ مورد دیگر

Anna Goldenberg is an Associate Professor in Computer Science at the University of Toronto and Senior Scientist in the Genetics & Genome Biology Program at The Hospital for Sick Children (SickKids). She holds the Varma Family Chair in Biomedical Informatics & AI and CIFAR AI Chair. Her roles include Co-chair of SickKids' AI in Medicine Initiative and Associate Research Director, Health at Vector Institute. Goldenberg's research focuses on developing machine learning methods for healthcare applications, including disease mechanisms, risk prediction systems, and responsible AI deployment. Affiliations: SickKids Research Institute, University of Toronto, Vector Institute Education: PhD from Carnegie Mellon University, Postdoc in Computational Biology Research Interests: Machine learning for healthcare, biomedical informatics, precision medicine, and overcoming AI challenges like rare event prediction and model explainability. Her lab emphasizes ethical AI integration into clinical workflows. Publications: Over 119 peer-reviewed articles spanning AI in medicine, genomics, and clinical prediction systems. Recent work includes early cancer detection via cell-free DNA and AI-driven pediatric urology management. Awards: Early Researcher Award, CIFAR AI Chair, Canadian Research Chair in Computational Medicine Grants: Multiple NIH, CIHR, and industry-funded projects totaling ~$20M, including grants for AI in cardiac arrest prediction, pediatric asthma modeling, and cancer detection via federated learning. Labs/Teams: Leads Goldenberg Lab at SickKids focusing on clinical AI systems and responsible innovation in healthcare technology.

• Bioinformatics
• Machine Learning
• Computational Biology
• +۷ مورد دیگر

Jan Baumbach is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he leads cutting-edge research at the intersection of computer science, bioinformatics, and biomedical data science. His work integrates machine learning, network biology, and systems medicine to address complex challenges in health and disease. His research interests include Bioinformatics , Machine Learning , Gene Regulatory Networks , Drug Repositioning , Biomedical AI , and Computational Biology . He applies advanced computational methods to analyze large-scale biological data, with applications in cancer, metabolic diseases, dermatology, and infectious diseases. The 15 most recent publications highlight a strong trend toward biomedical artificial intelligence , network-based analysis , and translational bioinformatics . His work spans from foundational machine learning in healthcare to clinical applications in osteoarthritis, bone regeneration, and skin biology. A consistent theme is the integration of multi-omics data and the development of privacy-preserving federated learning frameworks for distributed healthcare systems. Jan Baumbach has been principal investigator on several major research projects, including: EU Horizon2020: Privacy-preserving federated machine learning in distributed healthcare Danish National Research Foundation: ATLAS Center for Functional Genomics of Tissue Plasticity Villum Foundation: Big Data Bioinformatics (Young Investigator Programme) Carlsberg Foundation: Computational profiling of bacterial volatile metabolomes (ProVol) He has supervised 13 PhD students and has an extensive publication record of 262 works. His research has been featured in high-profile media outlets, emphasizing the societal impact of drug repositioning and AI in medicine. He leads a research group focused on computational systems biology , with strong collaborations across Europe in the fields of genomics, metabolomics, and clinical data science.

Oliver Karrasمشاهده پروفایل

مدرس

• Data Science
• Artificial Intelligence
• Knowledge Representation
• +۴ مورد دیگر

Oliver Karras is a researcher, data scientist, and lecturer at the Data Science and Digital Libraries research group at TIB – Leibniz Information Centre for Science and Technology. He holds a BSc, MSc, and PhD in Computer Science from Leibniz University Hannover. His research focuses on FAIR scientific knowledge, Open Research Knowledge Graph (ORKG), and national research infrastructure projects like NFDI-4Ing and FAIR-DS. He is a member of the German Informatics Society (GI) and spokesperson of the Requirements Engineering (RE) group, contributing to conferences and journals as a reviewer. Previously, he was a research associate and PhD student in the Software Engineering group at Leibniz University, leading the DFG project ViViReq on video integration in requirements engineering. His research interests include Data Science, AI, Knowledge Representation, Software Engineering, Requirements Engineering, Empirical Research, and Open Science. He has published over 60 papers in these areas, with notable contributions to knowledge graphs, FAIR data, and reproducibility frameworks. His work emphasizes organizing scientific knowledge for accessibility and collaboration across disciplines. He is actively involved in initiatives like the ORKG, promoting sustainable literature reviews and open science practices. His professional contributions extend to tool development, such as OntoAligner for ontology alignment and SciKGTeX for semantic annotation in LaTeX. Oliver Karras collaborates with institutions like Leibniz University, contributing to the NFDI consortium and energy research projects. His expertise bridges technical innovation and academic rigor, addressing challenges in knowledge management and reproducibility. His current roles include advancing TIB’s research infrastructure and fostering interdisciplinary collaboration through knowledge graph applications.