جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Data Mining
• Recommendation Systems
• +۵ مورد دیگر

Univ.-Prof. Dr. Günther Specht is a faculty member in the Department of Computer Science at Universität Innsbruck. His research focuses on machine learning, data mining, and their applications in recommendation systems, music information retrieval, and authorship attribution. He has contributed to projects such as HPT4Rec (a hyperparameter optimization framework for recommenders) and Cloudgene (a cloud computing tool for biomedical pipelines). His work spans database systems, text analysis, and social media analytics. Notable tools include HaploGrep 2 (for mitochondrial DNA analysis) and StyleExplorer (for textual style visualization). Key research areas include: (1) Developing algorithms for music popularity prediction and playlist analysis; (2) Enhancing authorship attribution techniques using grammar profiling and syntax tree analysis; (3) Designing efficient database index structures like Height Optimized Tries; and (4) Investigating ethical aspects of recommendation systems and plagiarism detection. Publications from 2020-2024 highlight advancements in cross-domain text classification, social media behavior analysis, and automated music genre recognition. His work bridges traditional statistical methods with modern machine learning, emphasizing practical applications in both academic and industry contexts.

Manos Papagelisمشاهده پروفایل

دانشیار

• Data Mining
• Graph Mining
• Machine Learning
• +۳ مورد دیگر

Dr. Manos Papagelis is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. He serves as the Graduate Program Director for the MSc and MScAI programs. His research focuses on data science and machine learning, particularly in data mining, graph mining, big data analytics, mobility analytics, and knowledge discovery. Education: PhD in Computer Science (University of Toronto), MSc and BSc in Computer Science (University of Crete, Greece). Prior to York, he held postdoctoral and research roles at UC Berkeley, Yahoo! Labs Barcelona, and FORTH, Greece. Research emphasizes trajectory analysis, emotion recognition, and scalable systems. Recent work includes TrajLearn (2025) and Disease Outbreak Detection (2025), highlighting contributions to mobility and health informatics. He has filed three U.S. patents and designed systems like Confious (conference management) and Green2.0 (socio-technical building analysis). Honors include the Lassonde Educator of the Year (2021) and IEEE MDM Best Paper Awards (2020, 2018). His advising spans interdisciplinary teams in AI and data science, with active involvement in grants related to mobility analytics and healthcare technologies. Labs/Teams: Director of the Data Mining Lab, collaborating on projects like trajectory prediction and emotion-aware systems.

Jeong-Hyon Hwangمشاهده پروفایل

دانشیار

• Databases
• Distributed Systems
• Graph Database Systems
• +۵ مورد دیگر

Jeong-Hyon Hwang is an Associate Professor at the University at Albany, State University of New York , affiliated with the College of Nanotechnology, Science, and Engineering and the Department of Computer Science . As Director of the Data Management Systems (DMS) Lab, he focuses on scalable graph databases, trajectory data compression, and real-time stream processing. His work on the G* graph database system, funded by the NSF CAREER award IIS-1149372 , enables efficient storage and analysis of distributed dynamic graphs. PhD in Computer Science, Brown University (2008) MS in Computer Science, Brown University (2003) MS in Computer Science and Engineering, Korea University (2000) BS in Computer Science and Engineering and Mathematics Education, Korea University (1998, 1994) Dr. Hwang’s research spans Databases and Distributed Systems , with specific emphasis on graph database systems , trajectory data management , and fault-tolerant stream processing . His publications highlight advancements in Internet-scale data management , real-time analytics , and load balancing for dynamic environments. The 15 most recent publications reflect trends in graph algorithms , stream processing reliability , and trajectory compression . Key subfields include distributed graph storage , centrality estimation , non-relational stream models , and high-availability solutions for wide-area networks. Scientific Awards : NSF CAREER award (2012) Best Poster Award, IEEE ICDE (2014) Best Poster Runners-Up, ACM SIGSPATIAL GIS (2010) IBM Open Collaborative Faculty Award (2010) National Scholarship, South Korea (2001-2005) New Software Award, South Korea (2001) Dr. Hwang leads the DMS Lab , developing open-source systems like G* for graph storage and querying. He has authored patents, co-authored Korean translations of technical books, and contributed to foundational research in high-availability algorithms and stream processing engines .

• Software Engineering
• IT Security
• Cloud Systems Engineering
• +۳ مورد دیگر

Diomidis Spinellis is a Professor at the Department of Management Science and Technology, Athens University of Economics and Business. He is a leading researcher in software engineering, IT security, and cloud systems engineering, with over 300 publications and 10,000 citations. He has authored award-winning books including Code Reading , Code Quality: The Open Source Perspective , and Effective Debugging: 66 Specific Ways to Debug Software and Systems (2016). As a Senior Member of ACM and IEEE, he served as Editor-in-Chief of IEEE Software (2015–2018) and contributed to open-source tools like CScout, UMLGraph, and dgsh. Award-winning author in software engineering Developer of critical open-source tools Editorial leadership in IEEE Software Contributor to macOS and BSD Unix His research spans code quality, software evolution, security, and developer productivity. Articles highlight Unix modernization, AI-assisted coding, dependency analysis, and incident management. He has served on the IEEE Computer Society Board of Governors and holds degrees from Imperial College London (MEng, PhD). Scientific contributions include open-source datasets (e.g., VulinOSS, Alexandria3k) and innovative tools for software analysis. His work bridges academic research and industrial practice, with case studies on Eclipse, Android APIs, and ING’s incident management.

• Database Systems
• Graph Databases
• Route Planning
• +۴ مورد دیگر

Dr. Theodoros Chondrogiannis is a Post-doctoral Researcher at the University of Konstanz's Database and Information Systems group. He holds a PhD from the Free University of Bozen-Bolzano (2017) and previously worked as a postdoc there until joining Konstanz. His research focuses on route planning, graph database query processing, and spatial network analysis. He leads a DFG-funded project on multi-criteria path queries and teaches 'Graph Data Management and Analysis' annually. Education: BSc (Computer Science, University of Peloponnese, 2009), MSc (Advanced Information Systems, National Kapodistrian University of Athens, 2013), PhD (Free University of Bozen-Bolzano, 2017). Research interests include algorithm design for transportation networks, graph database systems, and geosocial network analysis. His work bridges theoretical foundations with practical applications in urban mobility and query optimization. He will assume an Associate Professor role at NTNU's Department of Computer Science (IDI) starting January 2025. Notable service roles include publicity chair for SSTD 2023 and co-chair for ACM SIGSPATIAL Student Research Competitions (2019-2020).

• Information Management
• Information Retrieval
• Text Categorization
• +۳ مورد دیگر

Kalamboukis Theodore serves as a Professor at Athens University of Economics and Business (AUEB), where he maintains active research and administrative roles. His institutional affiliation centers on AUEB's academic ecosystem, with significant leadership experience including two terms as Vice-Rector (2001-2007). His academic credentials include: BSc in Mathematics from Athens University Ph.D in Computer Science from the University of Glasgow Research activities prominently feature Information Management with specialized focus on cross-lingual text retrieval systems , medical information retrieval , and clustering-enhanced classification techniques . His methodological approach integrates computational linguistics with practical information system design, particularly addressing multilingual challenges in specialized domains like healthcare. Publication trends from 2004-2008 reveal consistent innovation in text processing architectures, with increasing emphasis on medical applications and cross-lingual solutions. His work demonstrates strong interdisciplinary connections between computer science, healthcare informatics, and linguistic engineering, particularly through clustering methodologies applied to classification problems. No scientific awards were documented in the provided materials. Academic supervision includes doctoral and Master's dissertations in Economics and Informatics. Research funding spans multiple high-impact projects: MedAS (2006): Cross-language medical retrieval and image systems TIME (2005): EU-ASIA ICT tele-imaging initiative Joint Research Programme (2002-2005): Collaboration with University of Iasi e-Lexicon (2002): Economic terminology digital dictionary DILOS (1999): Bilingual economic dictionary development He maintains active consultancy with EU research programs and Greece's General Secretariat for Research and Technology. As Administrator of AUEB's Information and Database Systems Laboratory, he directs research in database architectures and information management systems, providing infrastructure for text processing and cross-lingual applications development.

Essam Mansourمشاهده پروفایل

دانشیار

• Federated Data Science
• Data Systems
• Distributed Systems
• +۶ مورد دیگر

Essam Mansour is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University, Montreal, and the head of the Cognitive Data Science (CoDS) Lab. His research focuses on Federated Data Science, knowledge graphs, graph neural networks, large language models, and distributed systems. He has received an NSERC Discovery Grant (2020) and leads projects like the Data Civilizer system for big data management and Lusail for scalable RDF querying. He advises students across PhD, Master’s, and undergraduate levels, with notable alumni working at companies like Huawei, Amazon, and as PhD candidates at McGill. Mansour has contributed to systems such as E-Store, Accordion, and StarDB, and holds a pending patent for data processing. He actively reviews for top journals like ACM TODS and IEEE TKDE, and serves on program committees for SIGMOD, VLDB, and ICDE. His work emphasizes scalable systems for data integration, query optimization, and cybersecurity applications using graph-based techniques. The CoDS lab develops platforms like KGNet and KGLac, advancing federated learning and knowledge graph technologies.

Stephen Blottمشاهده پروفایل

دانشیار

• Unix/Linux systems
• Computer networks
• Container technologies
• +۲ مورد دیگر

Stephen Blott is an Associate Professor at the School of Computing, Dublin City University. He holds a BSc in Computing Science from Glasgow University and a PhD from the same institution. Previously, he worked as a Senior Research Associate at ETH Zurich and as a Principal Investigator at Bell Labs in New Jersey. His research focuses on Unix/Linux systems, computer networks, container technologies, DevOps, and educational tools for computer science. Key areas include operating system optimization, network security protocols, container orchestration, and pedagogical innovations in computer science education. Publications show consistent focus on network security, data management, and computational efficiency. Recent work emphasizes internet infrastructure, privacy-preserving technologies, and biomedical informatics, with strong methodological foundations in simulation and algorithm design.

Alessio Zamboniمشاهده پروفایل

پژوهشگر

• Knowledge Graphs
• Natural Language Processing
• Data Integration
• +۳ مورد دیگر

Alessio Zamboni is an academic researcher and senior software engineer at the University of Trento, where he earned a MSc in Computer Science. He holds roles in the Department of Information Engineering and Computer Science, contributing to the KnowDive research group focusing on Knowledge Management, DevOps, and NLP. His career began at 17 as a full-stack developer, evolving into research roles at Fondazione Bruno Kessler (geographical information systems) and exchange studies in China (Zhejiang and Jilin Universities). Research interests span knowledge graphs, data integration, and software engineering. Notable projects include interoperable electronic health records and university system integration architectures. He has advised EU-funded initiatives in technical education and contributed to multilingual data disambiguation systems. Labs: Active member of the KnowDive Group at University of Trento, collaborating on interdisciplinary projects blending AI, data systems, and educational technology.

• Database Systems
• Virtual Reality Applications
• Digital Humanities
• +۴ مورد دیگر

Yannis Ioannidis is a Professor at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens. His research spans interdisciplinary areas including database systems, virtual reality applications, and cultural heritage technology. He leads projects integrating technology with education, art, and social sciences, such as VR environments for urban planning (ARSINOE VR) and AI-driven scientific discovery frameworks. His work emphasizes collaborative tools for digital storytelling and participatory cultural experiences. Ioannidis has contributed to advancements in database query optimization, text exploration through SQL extensions (DETEXA), and indexing techniques for data lakes. His recent focus includes exploring the intersection of tabletop role-playing games with historical education and ethical AI-human coevolution. He actively participates in initiatives like the EBRAINS infrastructure for brain research and the MagicARTS social VR project. Notable research trends in his publications include leveraging VR for immersive learning, designing hybrid museum kits, and applying AI to support UN Sustainable Development Goals. His work bridges technical innovation with societal impact, addressing challenges in education, art preservation, and ethical technology use.

• Biological and Artificial Vision
• Human Sensory Augmentation
• Secure Data Analytics
• +۳ مورد دیگر

Dr. Noel Murphy is an Associate Professor and Head of the School of Electronic Engineering at Dublin City University (DCU). He has held various leadership roles, including Associate Dean for Education in the Faculty of Engineering and Computing (2005-2007), Head of School (2007-2012, 2015-2018, and returning in 2021). He has been teaching at DCU since 1986 and has contributed extensively to academic governance, including roles on Academic Council and Governing Authority committees. Dr. Murphy holds a BA (Mod) in Theoretical Physics from Trinity College Dublin (TCD), a PhD from DCU (2003) on Information Theory models for Biological and Artificial Vision, and a part-time MA in Pure Mathematics from Maynooth University (2015). His research focuses on: Biological and Artificial Vision: Including Information Theoretic models and the work of Stephen Grossberg. Secure Data Analytics: Particularly leveraging SGX-enabled applications for data ownership control. Algebraic Number Theory: Exploring elliptic curves and Apéry's Constant. IoT and Edge Computing: Focusing on secure processing for IoT applications. Human Sensory Augmentation and Multimedia Information Retrieval. In addition to his teaching and leadership roles, Dr. Murphy has supervised numerous PhD and Master's students to completion. He has secured funding as Principal Investigator or co-Investigator on national and EU-funded research projects. He is affiliated with DCU's Entwine Research Centre. Outside academia, Dr. Murphy is Honorary Secretary of the Irish Light Aviation Society, holds a Private Pilot’s License, and is involved in aircraft restoration projects, including a 1940 Piper J5 and a Vans RV-8.

Sven Hertlingمشاهده پروفایل

استاد

• Knowledge Graph Generation
• Ontology Matching
• Knowledge Graph Integration
• +۳ مورد دیگر

Dr. Sven Hertling is a Substitute Professor for Data Science at the University of Mannheim, affiliated with the Data and Web Science Group. His research focuses on Knowledge Graph Generation, Ontology Matching, and Knowledge Graph Fusion. He teaches courses such as Knowledge Graphs, Data Mining, and Database Technologies. Notable awards include the Best Demo at ESWC 2021 and Best Paper at the Knowledge Graphs and Semantic Web Conference (KGSWC) 2022. Education: PhD in Computer Science (implied by role). His research interests span ontology alignment, large language model integration, and scalable knowledge graph systems. Recent work includes frameworks like KGrEaT for knowledge graph evaluation and tools like MELT for ontology matching analysis. He has contributed to over 50 publications, with a focus on ontology alignment evaluation (OAEI) and semantic web technologies. Key projects include the Software Campus initiative's GUI search engine and DBkWik, integrating knowledge from thousands of Wikis. Grants: €100,000 from Software Campus for the SuGraBo project. Advising: Coordinates OAEI challenges and chairs ESWC 2023. He actively serves on program committees for ISWC, ESWC, and other conferences, emphasizing community engagement in semantic web research.

Haopeng Zhangمشاهده پروفایل

استادیار

• Natural Language Processing
• Generative AI
• AI4Science (Healthcare, Linguistics, Sensing)
• +۳ مورد دیگر

Haopeng Zhang is an Assistant Professor in the Department of Information and Computer Sciences at the University of Hawaii at Mānoa, leading the ALOHA Lab. He holds a Ph.D. from the University of California, Davis (advised by Dr. Jiawei Zhang), dual M.S. degrees from Georgia Tech (Electrical Engineering and Computational Science), and a B.S. from UIUC (Electrical Engineering). His research focuses on NLP, Generative AI, AI4Science, and Graph Mining, emphasizing biomedical applications, multimodal reasoning, and workflow generation. Recent achievements include organizing workshops at EMNLP and ACL, receiving grants from NSF and OpenAI, and developing tools like StrucSum and MermaidFlow. Education: Ph.D., Computer Science, UC Davis (2024) M.S., Electrical Engineering & Computational Science, Georgia Tech B.S., Electrical Engineering, UIUC Research interests span structural summarization, LLM applications in healthcare and linguistics, and graph-based NLP systems. His work bridges theoretical advancements with practical tools, including the ALOHA Lab's contributions to reliable summarization systems and multimodal benchmarks. Notable contributions include the DomainSum benchmark and Wi-Chat wireless sensing framework. Key awards include UH travel grants, OpenAI credits, and NSF computing allocations. He actively serves on conference committees (ACL, KDD) and reviews for top journals (ACM TKDD, IEEE transactions). Teaching responsibilities include Advanced AI and Machine Learning courses at UH Mānoa. Lab activities focus on AI-driven solutions for scientific domains, with ongoing projects in biomedical event extraction and low-resource language support.

Melinda Hodkiewiczمشاهده پروفایل

استاد

• Maintenance Engineering
• Asset Management
• Data Science
• +۶ مورد دیگر

Professor Melinda Hodkiewicz is a leading academic at the University of Western Australia (UWA), affiliated with the School of Engineering's Mechanical Engineering department. Her work focuses on advancing maintenance, asset management, and safety practices through data-driven approaches, particularly in Technical Language Processing (TLP) and industrial ontologies. She has held significant roles such as the BHP Fellow for Engineering for Remote Operations (2015–2022) and leadership in the $8.8M Australian Government-funded Training Centre for Transforming Maintenance through Data Science. Research interests include applying TLP to maintenance and safety texts, ontology development for industrial interoperability, and advancing standards like ISO 23726. Awards include the MESA Medal (Lifetime Achievement in Asset Management) and Fellow of the Australian Academy of Technology and Engineering (ATSE). She has contributed to international standards (ISO 55000 series) and served on boards of organizations like NOPSEMA and MRIWA. Her work aligns with UN SDG 4 (Quality Education) and SDG 9 (Industry, Innovation & Infrastructure). Key contributions include developing the Industrial Ontology Foundry's Maintenance Working Group, creating open-source tools like OpenBoltRF for wind turbine analysis, and advancing semantic quality assurance frameworks for maintenance procedures. Her research bridges technical language processing with industrial applications, enhancing safety and operational efficiency in sectors like mining, energy, and offshore engineering. Education: BA(Hons) in Metallurgy (University of Oxford, 1985), PhD in Engineering (UWA, 2014) Grants: ARC Training Centre for Transforming Maintenance (2019–2025), ARC Hub for Offshore Floating Facilities (2014–2021) Advisory Roles: Standards Australia EL-069 (Automation Systems), ISO TC184/SC4 (Industrial Data)

• Computer Vision
• Machine Learning
• Object Detection
• +۷ مورد دیگر

Du Huynh is an Associate Professor at the School of Physics, Mathematics and Computing, Department of Computer Science and Software Engineering, The University of Western Australia (UWA). She holds a 0.8 FTE appointment and has served as Graduate Research Coordinator since 2013. Her research focuses on Computer Vision, Machine Learning, Object Detection, and Video Analytics with applications in mineral processing, intelligent transportation systems, and medical imaging. She has secured over $3M in ARC grants and is a Chief Investigator in the Australian Centre for Quantum Growth ($18M funding). Education: BSc (Hons) and PhD in Computer Science from UWA. Prior to UWA, she lectured at Murdoch University for five years. Research Highlights Developed algorithms for automated mineral ore analysis, pedestrian trajectory prediction, and surgical instrument detection. Received three Best Paper Awards (ICPR2014, Kenneth Clarke Journal 2019, AusDM2022) and multiple award nominations. Editorial roles include PLOS One, Journal on Artificial Intelligence, and guest editorships for special issues in CVIU and Electronics. Grants & Projects Lead investigator in quantum computing algorithms for real-time optimization ($3M ARC funding). Collaborations with industry (e.g., Main Roads WA) on traffic video analytics and drone-based prediction systems. Academic Contributions Developed courses in Computer Vision, Machine Learning, and Java Programming. Supervised numerous HDR students and served on technical committees for WACV, ICCV, and DICTA conferences.