جست‌وجوی استاد و پژوهشگر

• Astrophysics
• Cosmology
• Dark matter + dark energy
• +۷ مورد دیگر

Jens Hjorth is a Professor of Astrophysics at the University of Copenhagen's Niels Bohr Institute, where he leads research in the DARK center. With over 400 refereed publications, more than 35,000 citations, and an h-index of 96, he is a prominent figure in modern astrophysics. His work spans cosmology, dark matter research, and high-redshift galaxy studies, with approximately 33 papers published in Nature or Science journals. Professor Hjorth's primary research focuses on astrophysical transients, very high-redshift galaxies, cosmology, and the origin of universality in dark-matter halos. His work bridges theoretical modeling with observational data, particularly through his involvement with the Euclid space mission. His research often explores the intersection of astrophysics with art and science, demonstrating a commitment to interdisciplinary approaches. His recent publications reveal a strong emphasis on dark matter halo structure, galaxy evolution across cosmic time, and the development of sophisticated simulations for cosmological studies. His publication record shows consistent high-impact contributions, with recent work heavily focused on the Euclid mission's instrumentation and data analysis. These publications span theoretical cosmology, observational techniques, and the development of advanced simulation methods for understanding large-scale structure formation. The research demonstrates both depth in specialized areas like dark matter physics and breadth across related astrophysical disciplines. Villum Investigator: Time in Astrophysics Member of the boards of the Carlsberg Foundation Member of the boards of the Tuborg Foundation Approximately 33 scientific papers in Nature or Science journals Most cited lead-author paper: J. Hjorth et al. Nature 423, 847–850 (2003) with ~1300 citations As a Villum Investigator, Professor Hjorth leads significant research initiatives focused on time-domain astrophysics. He also serves as Co-lead of the UCPH Forward career development program, demonstrating his commitment to academic leadership and mentorship. His extensive publication record and high citation count reflect substantial research impact across multiple funding cycles and collaborative projects. Professor Hjorth is deeply involved with the DARK research center at the Niels Bohr Institute, which focuses on cosmology, dark matter, and dark energy research. His work with the Euclid mission places him at the forefront of international space-based cosmological surveys. The research teams he participates in combine observational astronomers, theoretical physicists, and computational scientists to tackle fundamental questions about the universe's structure and evolution.

• Schema discovery for Semantic Web data
• Data mining
• Recommendation systems
• +۵ مورد دیگر

Kenza Kellou-Menouer is a researcher affiliated with the ETIS Laboratory at ENSEA, France, and part of the MIDI research group . Her work focuses on schema discovery for Semantic Web data, data mining, and big data optimization. Research: Semantic schema discovery, clustering/classification algorithms, and association rules. Teaching: Semantic Web technologies, database design, algorithms, and programming languages (Java, C++, C#, C). Research Interests center on Semantic Web data integration, RDF schema inference, and hybrid machine learning approaches. She has contributed to scalable schema discovery systems and real-time profiling techniques for large datasets. Publications include work on schema inference tools (SchemaDecrypt++, HInT) and methodological frameworks presented at top-tier venues like VLDB (A*), ICDE (A*), SSDBM (A), and ISWC . Her research bridges theoretical advancements with practical implementations for RDF datasets. Community Contributions include organizing tutorials at the International Semantic Web Conference (ISWC) 2022 and developing educational materials for database and programming courses.

Daniel Paul O'Donnellمشاهده پروفایل

استاد

• Digital Humanities
• Medieval Literature
• History of the Book
• +۵ مورد دیگر

Daniel Paul O'Donnell is a tenured Professor and Department Chair of English at the University of Lethbridge, co-PI of the Humanities Innovation Lab , and Editor-in-Chief of Digital Studies / Le champ numérique . He teaches Digital Humanities, medieval literature, History of the Book, and English language courses, including first-year English 1900. Education: PhD in English, Yale University (1996) MA in English, Yale University (1991) BA with Distinction, St. Michael's College, University of Toronto (1989) Research Interests: Digital Humanities, Scholarly Communication, Cultural Heritage Representation, and Old English Philology. His work focuses on markup theories, digital edition design, and the intersection of Web 2.0 with academic practices. The Visionary Cross Project digitizes Anglo-Saxon crosses, while the Lethbridge Journal Incubator explores sustainable open-access publication models. Scientific Awards: Honourable Mention, Modern Language Association Prize for a Distinguished Scholarly Edition (2007) for Cædmon's Hymn: A Multimedia Study, Edition and Archive Grants and Funding: Recipient of multiple SSHRC grants, CFI funding, and Andrew W. Mellon Foundation support for digital edition projects and scholarly communication initiatives. Currently leading SSHRC Insight Grant (2025-2029) for Resistance to Data: Understanding data use in the traditional Humanities . Leadership Roles: Past president of University of Lethbridge Faculty Association, Confederation of Alberta Faculty Associations, and Society for Digital Humanities. Former Director of Text Encoding Initiative and Digital Medievalist Community of Practice.

Ipshita Rayمشاهده پروفایل

دانشیار

• Customer Decision-Making
• Customer Relationship Management
• Online and Offline Shopping Behaviors
• +۵ مورد دیگر

Dr. Ipshita Ray serves as Associate Professor of Marketing and Graduate Program Chair at Pace University's Lubin School of Business in New York City. With faculty tenure since 2005, she maintains an active presence in academic organizations including the American Marketing Association, Association of Consumer Research, Academy of Marketing Science, and Academy of Business Research. Her educational credentials include: PhD in Marketing Communications from the University of Connecticut, Storrs, CT MA in Marketing Communications from the University of Connecticut, Storrs, CT Dr. Ray's research investigates customer decision-making processes, relationship management dynamics, and digital-physical shopping behavior intersections. Her work integrates self-identity algorithms with social community analysis, published in journals like Journal of Business Research and Journal of Strategic Marketing. She pioneered analytics integration into Pace's curriculum since 2015, teaching Python, Tableau, and Google Analytics across graduate and undergraduate courses. Publication trends reveal an evolution from health marketing (2004) toward digital consumer behavior analytics (2010-2015), with consistent focus on customer retention metrics and brand valuation frameworks. Her methodology shifted toward Rule Developing Experimentation (RDE) applications while maintaining behavioral psychology foundations. Her accolades include: Kenan Excellence in Teaching Award (2018) - Pace University's highest teaching honor Advertising Education Foundation National Award (2008) Outstanding Professor of the Year at Fairfield University (2002) Dr. Ray advises Lubin Graduate Marketing Association and Advertising Club while directing industry partnerships with Publicis, GroupM, and IBM. Her annual analytics competitions have secured 24+ job placements with visa sponsorships for international students. She currently develops an analytics advisory council to enhance curriculum and professional training. Her teaching laboratory integrates Nielsen @Plan, SPSS, and MRI data tools with real-time industry projects, creating a pipeline for students into global marketing analytics careers through structured corporate collaborations.

Michel Dumontierمشاهده پروفایل

استاد

• FAIR data
• generative artificial intelligence
• machine learning
• +۹ مورد دیگر

Dr. Michel Dumontier is a Distinguished Professor of Data Science at Maastricht University, where he serves as the founder and Director of the Institute of Data Science. He is internationally recognized as a co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles, which have transformed scientific data management globally. His academic background includes: BSc in Biochemistry from the University of Manitoba (1999) PhD in Bioinformatics from the University of Toronto (2004) Assistant/Associate Professor at Carleton University (2005-2013) Associate Professor at Stanford University (2013-2016) Distinguished Professor at Maastricht University (2017-present) Dr. Dumontier's research focuses on unlocking data potential for scientific discovery, with expertise in knowledge graphs for drug discovery and personalized medicine. His work spans FAIR data principles, generative AI, machine learning, semantic technologies, ontology, and data integration. His recent publications reveal a strong trend toward applying generative AI to healthcare data, with increasing focus on synthetic health data generation, privacy-preserving techniques, and knowledge graph applications in drug repurposing. His work bridges computer science, biomedical informatics, and clinical applications across multiple medical domains. Dr. Dumontier has secured significant research funding as a principal investigator: NWO (Dutch Research Council) Horizon Europe MCSA NIH/NCATS ARPA-H He coordinates the AIDAVA and REALM projects, leads the NCATS Biomedical Data Translator, and directs the GENIUS AI lab. As editor-in-chief of the journal Data Science, he shapes discourse in the field. Dr. Dumontier maintains active industry connections through: Minderheidsaandeelhouder at Data2Discovery Inc Scientific advisor and minority shareholder at OntoForce NV Scientific advisor, board member, and minority shareholder at Comunicare Editor-in-chief of Data Science Journal at Sage Publishing

F. Donelson (Don) Smithمشاهده پروفایل

استاد پژوهشی

• Computer Networking
• Operating Systems
• Distributed Systems
• +۳ مورد دیگر

F. Donelson (Don) Smith is a Research Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill . He holds a Ph.D. in Computer Science (1978) from UNC-Chapel Hill, with prior degrees in Chemistry (1962) and Industrial Management (1964) from the University of Tennessee. Key research areas: Computer networking, multimedia systems, distributed systems Collaboration with: Kevin Jeffay , Jasleen Kaur , and the DiRT Lab Notable contributions include: Co-inventor of U.S. Patents 7,444,720 (2008) and 5,892,754 (1999) Key roles at IBM (1965-1997) in network architecture , protocol development , and multimedia networking Active in professional service: Program Chair, TriComm '91 Co-chair, ACM CSCW '94

Gergely Kocsisمشاهده پروفایل

دانشیار

• Information spreading
• Agent-based simulations
• Cellular automata
• +۱ مورد دیگر

Dr. Gergely Kocsis serves as an Associate Professor at the University of Debrecen's Faculty of Informatics, Department of Informatics Systems and Networks. His office is located in the Faculty of Informatics building at 4028 Debrecen, Kassai út 26, ground floor, IF13 (Lecturers' room), with contact email kocsis.gergely@inf.unideb.hu and central telephone +36 52 512 900 75013. Dr. Kocsis's research program focuses on: Information spreading phenomena Agent-based and individual-based simulations Cellular automata applications Network structure and dynamics His scholarly output reveals a sophisticated research trajectory evolving from foundational work on cellular automata modeling of social dynamics (2007-2014) to contemporary investigations of transportation networks, VANETs, and AI applications. The 2023-2025 publications demonstrate particular expertise in network extraction methodologies, containerized computing environments, and the application of generative AI to productivity challenges. His work consistently applies computational modeling approaches to understand complex spreading phenomena across diverse network structures. Dr. Kocsis maintains comprehensive scientific profiles across major academic platforms including Google Scholar, ResearchGate, ORCID, Scopus, and Web of Science, demonstrating active participation in the international research community. His departmental colleagues work in complementary areas such as complex networks, embedded systems, and neural networks, suggesting rich collaborative opportunities within the Faculty of Informatics.

Alexey Gotsmanمشاهده پروفایل

استاد پژوهشی

• Distributed Systems
• Software Verification
• Consensus Algorithms
• +۵ مورد دیگر

Alexey Gotsman is a tenured Research Professor at the IMDEA Software Institute in Madrid, Spain, where he leads research at the intersection of software verification and distributed computing. He also works part-time as a visiting academic at Amazon Web Services. His educational background includes a Ph.D. from the University of Cambridge, where he was previously a postdoctoral fellow. His research spans theoretical foundations and practical implementations of distributed systems, with particular emphasis on fault tolerance, consensus algorithms, and consistency models. His research interests focus on the theoretical and practical aspects of distributed systems, including Byzantine fault tolerance, state machine replication, distributed transactions, and consistency models. His work bridges the gap between formal verification techniques and real-world distributed systems implementations, with numerous publications in top-tier venues like PODC, DISC, and NSDI. His recent publications show a clear progression from theoretical foundations to practical implementations, with increasing focus on real-world applications, performance considerations, and fault tolerance in large-scale distributed systems. The research demonstrates strong connections between formal methods and practical system design, particularly in the areas of consensus protocols, replication strategies, and transaction processing. Best paper award at OPODIS'23 Best paper award at DISC'18 Best paper award at CONCUR'12 EAPLS Best Dissertation Award Runner-up prize in the BCS Distinguished Dissertation Competition ERC Starting Grant 'RACCOON: A Rigorous Approach to Consistency in Cloud Databases' (2017-2022) Ramón y Cajal Fellowship (2017-2022) Alexey actively mentors PhD students including Alejandro Naser Pastoriza, Fedor Ryabinin, and Antonio José Fernández Pinto, while his alumni have gone on to faculty positions at institutions like University of Paris 7 and University of Colorado Boulder, as well as industry roles at companies like ARM and Informal Systems. He has received significant funding including an ERC Starting Grant and served on program committees for numerous top conferences including POPL, DISC, and PODC. He currently co-organizes the International Symposium on Distributed Computing (DISC) and has been instrumental in organizing workshops focused on consistency in distributed systems. His research group at IMDEA Software Institute focuses on developing rigorous approaches to consistency in cloud databases and distributed systems, with active projects spanning theoretical analysis, protocol design, and practical implementation of fault-tolerant distributed systems.

Ramon Canalمشاهده پروفایل

استاد

• Secure microarchitectures
• System reliability
• Virtualization and operating systems
• +۵ مورد دیگر

Ramon Canal is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics and the Computer Architecture Department. He has served as Vice Dean of postgraduate studies and leads the VirtuOS (Virtualization and Operating Systems) research group. His academic background includes BSc, MSc, and PhD from UPC, with thesis supervision by Antonio González (UPC) and James E. Smith (University of Wisconsin-Madison). He completed sabbaticals at Harvard University (2006-2007) and University of Cyprus (2019-2020). Education: PhD, MSc, BSc in Computer Engineering (UPC) Research focus: Microarchitecture security, reliability across circuit/system levels, cloud optimization Recent publications address privacy in IoT, secure hardware accelerators, and safety-critical systems. His work contributes to the DRAC project (2019-2022), Red-RISCV network, and Horizon's Vitamin-V project. Awards include HiPEAC Paper Awards, IEEE Senior Member status, Fulbright recognition, and multiple education excellence accolades. Scientific Honors HiPEAC Paper Award (ISCA-44, 2017) IEEE Senior Member (2016) Best Paper Nominee (ICCD-32, 2014) UPC Outstanding PhD Award supervision (2011) He advises current MSc students and has mentored multiple PhD graduates. Professional activities span academic leadership, research collaborations with Barcelona Supercomputing Center (BSC), and technical contributions to reliability analysis frameworks like RECIPE and FRACTAL.

Olga Ilieva Georgievaمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۶ مورد دیگر

Olga Ilieva Georgieva is a Professor at the Faculty of Mathematics and Informatics (FMI) , Sofia University , specializing in Software Technologies . She has held academic positions at the Bulgarian Academy of Sciences and Technical University of Sofia , and is actively involved in research, teaching, and national/EU-funded projects. Education: 1986 – Faculty of Automatics, TU-Sofia 1995 – PhD, Institute of Control and System Research, Bulgarian Academy of Sciences 2000 – Associate Professor, Institute of Control and System Research, Bulgarian Academy of Sciences 2008 – Associate Professor, Faculty of Mathematics and Informatics, Sofia University Research Interests: Her work spans Artificial Intelligence , Machine Learning , Data Mining , and Soft Computing Methods . She applies these to domains such as emotion recognition from EEG , QoS in web services , educational data mining , and industrial energy modeling . Scientific Awards: Best Paper Award, IEEE 8th International Conference on Intelligent Systems (2016) Teaching & Projects: She teaches courses including Requirements Engineering , Models of Software Systems , Fuzzy Sets and Applications , and Professional Ethics at Sofia University, and previously taught at TU-Sofia. She leads or co-leads multiple national and EU projects such as GATE: Big Data for Smart Society , ITDGate , and Modelling of Voluntary Saccadic Eye Movements .

Ross Horneمشاهده پروفایل

مدرس ارشد

• Security protocols
• Privacy-preserving technologies
• Concurrency theory
• +۷ مورد دیگر

Ross Horne is a Senior Lecturer in the Department of Computer & Information Sciences at the University of Strathclyde, Glasgow, United Kingdom. He is a member of the StrathCyber and Mathematically Structured Programming research groups. Education: PhD (University of Southampton, 2012), BA (Oxford University, 2005) Prior Appointments: Research Fellow at University of Luxembourg (2018-2023), Senior Research Fellow at Nanyang Technological University (2015-2018), Associate Professor at Kazakh-British Technical University (2012-2015) Research Interests: Dr. Horne's work focuses on security and privacy protocols for digital systems, particularly addressing threats in payment technologies, ePassports, and decentralized identity management (e.g., Solid protocol). His theoretical contributions bridge concurrency theory, proof theory, and logic through applications to security verification and process calculi. Developed formal models for unlinkability in EMV payment protocols Created intuitionistic logical frameworks for process equivalence Explored graphical proof systems beyond formulaic representations Investigated legal-compliant AI for space systems (CubeSat anomaly detection) Scientific Contributions: He has published extensively in top venues including ACM CCS, IEEE CSF, LICS, and CONCUR. His 2017 CONCUR best paper introduced intuitionistic characterizations of bisimilarity. Principal Investigator for EU COST Action on Distributed Knowledge Graphs Co-developed privacy models adopted in Luxembourg parliamentary responses Advising: Currently accepting PhD students with strong mathematical and computer science skills for research in security/privacy of emerging systems. Former student Semen Yurkov completed a thesis on privacy-preserving smart card payments. Interdisciplinary Work: Collaborates with space lawyers through the Interdisciplinary Master Program in Space Resources. Projects include AI for CubeSat reliability and legal-compliant software certification frameworks.

Daniel E. Fordمشاهده پروفایل

استاد

• Coronary artery disease
• Epidemiology
• Depression
• +۷ مورد دیگر

Daniel E. Ford is a Professor of Medicine at Johns Hopkins University School of Medicine with joint appointments in Psychiatry and Behavioral Sciences, and at the Johns Hopkins Bloomberg School of Public Health in Health Policy and Management and Epidemiology. He serves as Director of the Johns Hopkins Institute for Clinical and Translational Research and Senior Associate Dean for Clinical and Translational Research at the Johns Hopkins School of Medicine. Dr. Ford received his MD from State University of New York at Buffalo in 1982 and has been on the Johns Hopkins faculty since then, except for a brief period as a National Institutes of Health fellow. He earned his Master's in Public Health from the Bloomberg School in 1986. He has published more than 120 research papers and book chapters and served as associate editor of the Journal of General Internal Medicine. Dr. Ford is widely regarded as a pioneer in research on the interrelationships between mental disorders and chronic medical conditions. His research interests focus on depression and coronary artery disease, improving care for patients with medical comorbidity, and exploring how information technology can be used to improve care for patients with depression and tobacco abuse. He was one of the first investigators to document depression as a risk factor for myocardial infarction and stroke. His work includes developing web-assisted interventions for tobacco cessation and studying seasonal patterns in mental health information seeking. His research demonstrates strong interdisciplinary connections between mental health, cardiology, epidemiology, and digital health technologies. The publications show a consistent focus on translating research findings into practical clinical applications, particularly through information technology solutions. His work spans clinical trials, epidemiological studies, implementation science, and digital health innovation. David M. Levine Professor of Medicine (2005) Dr. Ford has been instrumental in developing clinical research infrastructure at Johns Hopkins, working closely with personnel who developed e-IRB, an electronic process for submitting research proposals to the Institutional Review Board. He has been principal researcher on a large training grant to develop researchers in general internal medicine and was chosen by the Robert Wood Johnson Foundation to direct the evaluation of its $12 million Depression in Primary Care Initiative. He advocates treating human research subjects as partners in the research process. His laboratory research focuses on understanding relationships between depression and various chronic medical conditions, with recent emphasis on depression and coronary artery disease. The Ford Lab explores how information technology can be used to improve care for patients with depression and tobacco abuse, with interest in moving these interventions into the commercial world.

David Hovemeyerمشاهده پروفایل

عضو هیئت علمی

• Static Analysis
• Systems Software
• Computer Science Education
• +۳ مورد دیگر

David Hovemeyer is an Associate Teaching Professor at the Whiting School of Engineering, Johns Hopkins University . He holds a PhD (2005) and MS (2001) in Computer Science from the University of Maryland and a BA (1994) from Earlham College. Prior to joining JHU in 2019, he taught at Vassar College and York College of Pennsylvania. Education : PhD, MS, and BA in Computer Science Research : Focuses on static analysis , systems software , and computer science education Projects : FindBugs, CloudCoder, ProgSnap2, FunWithSound His recent work includes frameworks for declarative autograders , formats for programming process data , and tools for educational software development . He has been recognized with Excellence in Teaching Awards and contributes to open-source educational platforms like GitHub. Scientific Awards : 2024 Whiting School Teaching, Advising, and Mentoring Award Excellence in Teaching Award (multiple years) David maintains an active role in the academic community through peer instruction , programming contests, and recommendation letter advising . He also develops tools like FreePoll and Declarative Autograder Framework to enhance teaching efficiency.

Martin Raubalمشاهده پروفایل

استاد

• Spatial Decision-Making
• Mobile Geographic Information Systems (GIS)
• Location-Based Services (LBS)
• +۷ مورد دیگر

Prof. Dr. Martin Raubal is a Full Professor at the Institute for Cartography and Geoinformation, Department of Civil, Environmental and Geomatic Engineering, ETH Zurich. He leads research on spatial decision-making, mobile GIS, and location-based services, with applications in transportation, energy, and aviation. His work integrates cognitive engineering and eye-tracking to analyze human mobility and interaction with geospatial systems. Doctorate in Geoinformation (with distinction), Vienna University of Technology (2001) MS in Spatial Information Science and Engineering, University of Maine (1997) Dipl.-Ing. in Surveying Engineering and Geoinformation, Vienna University of Technology (1998) His research focuses on spatiotemporal human mobility, cognitive models for GIS, and sustainable urban systems. Key projects include the Digital Underground initiative at the Singapore-ETH Centre and the Empirical Use and Impact Analysis of Mobility-as-a-Service (EIM). Awards include the UV-Helava Prize and multiple best paper recognitions. Recent publications emphasize 3D spatial analysis, AI-driven geospatial tools, and causal inference in mobility modeling. Collaborations span institutions like Lufthansa Systems, SBB, and ETH-IVT. His lab investigates applications such as electric vehicle charging networks, bikeability indexes, and augmented reality in transportation planning.

• Bayesian Methods
• Stochastic Processes
• Time Series Analysis
• +۳ مورد دیگر

Tevfik Aktekin is a Professor in the Department of Decision Sciences at the Paul College of Business and Economics, University of New Hampshire. His research focuses on Bayesian inference and stochastic modeling in service systems and business analytics. Education : Ph.D. in Decision Sciences (George Washington University), M.B.A. in Management Decision Making (George Washington University), B.S. in Mechanical Engineering (Yildiz Technical University). His work applies Bayesian state-space models to multivariate count data, with applications in call center staffing, product modification cycles, and public health analysis. He has published in journals like Annals of Applied Statistics , Bayesian Analysis , and European Journal of Operational Research . The 15 most recent articles highlight trends in sequential Bayesian learning for dynamic systems (e.g., bike-sharing, web traffic), time series of non-Gaussian data, and stochastic optimization under uncertainty. These works bridge statistical theory with practical applications in business and health.