جست‌وجوی استاد و پژوهشگر

• Multicore Computing
• Program Analysis
• Virtual Machine Optimization
• +۴ مورد دیگر

Daniele Bonetta is an Assistant Professor in the Department of Computer Science at Vrije Universiteit Amsterdam and holds an ancillary role as a Medewerker (Employee) at Eindhoven University of Technology since June 2020. His primary affiliation is with the Faculty of Science, where he contributes to the Network Institute as well. His research focuses on optimizing virtual machines, parallel programming models, and dynamic compilation techniques, with a particular emphasis on multicore systems and distributed computing environments. Bonetta has also been involved in teaching advanced courses such as Advanced Network Programming and contributes to the Accelerator-Centric Computing Ecosystems program. His research interests are centered around improving the performance of managed runtimes, including virtual machine optimization, dynamic taint analysis, and efficient data processing in polyglot environments. He has explored topics such as speculative optimizations for JSON data access, columnar array storage transformations, and scalable solutions for virtual memory oversubscription. His work frequently addresses challenges in distributed systems, cloud computing, and cross-language program analysis. Bonetta’s recent publications (2023-2025) highlight advancements in transparent scale-out mechanisms for virtual memory, automated supernode generation in interpreters, and dynamic query engines embedded in polyglot runtimes. His contributions to the field include both theoretical frameworks and practical implementations, often leveraging the GraalVM and Truffle frameworks for polyglot execution. While no formal awards are listed, his extensive publication record (47+ outputs) demonstrates significant scholarly impact. His teaching portfolio includes courses on network programming and systems architecture, reflecting his dual focus on both theoretical research and applied computer science education.

Adam Fourneyمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Human-Computer Interaction
• Multi-Agent Systems
• +۳ مورد دیگر

Adam Fourney is a Senior Principal Researcher at Microsoft Research's Human-AI eXperiences (HAX) group in Redmond. He holds a Ph.D. and M.Math. from the University of Waterloo and a B.Sc. from the University of Ottawa. His work focuses on AI agents collaborating with humans to complete complex tasks, including projects like AutoGen and Magentic-One. He previously studied web search, intelligent assistants, and information systems at the University of Waterloo. Education: Ph.D. (Computer Science), University of Waterloo M.Math. (Computer Science), University of Waterloo B.Sc. (Computer Science), University of Ottawa His research interests span Human-AI collaboration, multi-agent systems, AI ethics, and AI-assisted programming. He explores how AI systems can support human tasks while addressing challenges like uncertainty, communication breakdowns, and alignment with human goals. His work bridges technical innovation with user-centered evaluation, emphasizing real-world usability and societal impact. His recent articles highlight advancements in interactive AI debugging, alignment of AI tools with human needs, and leveraging search data for public health insights. Notably, he received a Best paper honorable mention at CHI 2024 for work on AI-assisted programming costs. Adam has collaborated extensively with researchers across Microsoft and academia, contributing to open-source tools like AutoGen Studio and foundational studies in human-LLM interactions. His interdisciplinary approach combines technical rigor with insights from user behavior and social dynamics.

Anteneh Ayansoمشاهده پروفایل

استاد

• Information Systems
• E-Government
• Data Privacy
• +۷ مورد دیگر

Anteneh Ayanso is the Department Chair and Professor of Information Systems at the Goodman School of Business, Brock University. His academic role combines leadership in the Finance, Operations and Information Systems Department with research and teaching expertise in information systems and technology-driven business solutions. His research focuses on interdisciplinary areas including E-Government development, data privacy, artificial intelligence in retail, social network analysis, and ICT policy. Notable contributions include studies on technology provider networks, media sentiment impacts on housing markets, and healthcare system efficiency. Ayanso has published extensively in top-tier journals, with recent work addressing pandemic-era economic resilience, AI applications in retail performance, and multi-dimensional bias analysis in language models. His work bridges technology adoption, public policy, and business strategy. He has collaborated on projects involving healthcare technology, social media analytics, and global ICT development indices. His applied research emphasizes practical solutions for organizations and governments navigating digital transformation challenges.

Sergio Grecoمشاهده پروفایل

استاد

• Database Theory
• Data Integration
• Inconsistent Data Processing
• +۳ مورد دیگر

Sergio Greco is Full Professor at University of Calabria's DIMES Department, Coordinator of the Computer Engineering Degree, and Vice-president of the Computer Engineering national Group. His research spans database theory, data integration, inconsistent data processing, and computational logic. Research Focus: Development of theoretical frameworks for data management including argumentation frameworks, knowledge base querying under inconsistency, and decentralized learning systems. Recent work integrates machine learning with formal reasoning methods. Honors: Best Paper Award at International Conference on Logic Programming (2020) Best Paper Award at RuleML Symposium (2014) Leads projects on cybersecurity and data management funded by EU and Italian Ministry of Research, coordinating national and international research groups.

Sanjeev Kumar Srivastavaمشاهده پروفایل

دانشیار

• Geographical Information Systems (GIS)
• Remote Sensing
• Natural Resources Management
• +۳ مورد دیگر

Associate Professor Sanjeev Kumar Srivastava is an academic in the Department of Geospatial Analysis at the University of the Sunshine Coast (UniSC), Queensland, Australia. He holds a PhD in Geographical Sciences from The Australian National University and specializes in GIS, remote sensing, and natural resource management. His teaching focuses on spatial science courses, including GIS, remote sensing, and geospatial analysis, employing innovative pedagogical methods like field-based learning and immersive visualization. Dr. Srivastava's research emphasizes fire ecology, natural resource conservation, and GIS education. He leads projects funded by organizations such as the Asia-Pacific Network Global Change Research and the Australian Koala Foundation. Notable awards include the 2018 Asia-Pacific Spatial Excellence Award and a 2013 OLT Citation for teaching excellence. Education: PhD in Geographical Sciences, Australian National University Committees: SmartSat CRC Education & Training College Member Spatial Information and Cartography Commission Co-chair His research spans GIS applications in disaster management (e.g., cyclone tracking, wildfire modeling) and ecosystem conservation (e.g., Sundarbans World Heritage Site). He actively supervises HDR and Honours students on topics like bushfire risk mitigation and koala habitat recovery.

Fahad Dogarمشاهده پروفایل

دانشیار

• Networking
• Distributed Systems
• Cloud Computing
• +۵ مورد دیگر

Fahad Dogar is an Associate Professor in the Department of Computer Science at Tufts University's School of Engineering, with a secondary appointment at the Jonathan Tisch College of Civic Life. He leads the NAT (Networking At Tufts) research group and serves as Director of the Master Software Systems Program since 2022. His academic journey includes a Ph.D. from Carnegie Mellon University (2012), undergraduate studies at Lahore University of Management Sciences (LUMS) in Pakistan (2005), and postdoctoral research at Microsoft Research UK. Dogar's research focuses on designing technologies for social impact across multiple computer science domains. His primary interests include networking and distributed systems, with recent emphasis on data center networking, future Internet architectures, and the application of large language models for accessibility. Notably, his work spans cloud-based systems, mobile and wireless technologies, and developing practical solutions for resource-constrained environments in developing regions. Networking and distributed systems architecture Cloud computing infrastructure and optimization Human-Computer Interaction for accessibility Generative AI applications for social impact Technologies for developing regions Augmented reality networking requirements His publication record shows consistent output with 36 publications including two significant papers in 2024 focusing on LLM-powered applications for autistic users and machine learning job scheduling. His research has appeared in top-tier venues including ACM SIGCOMM, Usenix NSDI, and ACM MobiCom. Gold medal from the president of Pakistan for top computer science student LUMS Vice Chancellor Alumni Achievement Award (2021) VMWare Early Career Faculty Fellowship (2019) Facebook/Oculus Faculty Fellowship (2017) Tisch Faculty Fellowship (2017-2018) Dogar has secured substantial research funding including an NSF Core Medium award ($850K) as sole PI for 'Slack-Aware Networking' (2021-2025), Meta/Facebook funding ($150K) for networking support for telepresence applications (2020-2022), and multiple NSF awards totaling over $1 million. His teaching portfolio includes courses on Networks, Computing for Developing Regions, and special topics in Generative AI for Social Impact. During his 2023 sabbatical, he served as Senior Fellow with the Burnes Center for Social Change at Northeastern University, demonstrating his commitment to civic technology applications.

Chung Hwan Kimمشاهده پروفایل

استادیار

• Computer Systems Security
• Cyber-Physical Security
• Software Security
• +۲ مورد دیگر

Dr. Chung Hwan Kim is an Assistant Professor in the Department of Computer Science at UT Dallas' Erik Jonsson School of Engineering. His research focuses on system security, including embedded systems protection, trusted execution environments, and automated bug detection. He directs the Software & Systems Security Laboratory and holds affiliated appointments in Electrical Engineering. Key research areas include developing compartmentalization techniques for embedded devices (TZ-DATASHIELD), securing GPU computations via CPU enclaves, and fuzzing methods for autonomous driving systems. His publications demonstrate consistent innovation in hardware-assisted security and vulnerability detection. Dr. Kim received the UT Dallas New Faculty Research Award (2021) and was a CSAW Best Paper Finalist (2018). His industry experience includes prior work at NEC Labs developing security solutions for enterprise systems.

Tony Russell-Roseمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Information Retrieval
• Natural Language Processing
• +۳ مورد دیگر

Tony Russell-Rose is Reader in Computer Science at Goldsmiths, University of London. He holds a PhD in Computer Science from Nottingham Trent University and directs UXLabs, specializing in complex information-centric applications. His research integrates natural language processing, information retrieval, and user experience. Research interests include human information interaction, professional search systems, complex query formulation, and visual interfaces for information exploration. He collaborates with City University's School of Informatics and Sheffield University's Information Retrieval group. Publications focus on search strategy formulation, visual query interfaces, and professional search practices. Recent works emphasize transparency, reproducibility, and explainability in information retrieval systems. Awards: Royal Academy of Engineering Visiting Professor

Bin Yangمشاهده پروفایل

استاد

• Computer Science
• Data Management
• Machine Learning
• +۹ مورد دیگر

Bin Yang is a Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, artificial intelligence, and machine learning, with emphasis on spatiotemporal data analysis, representation learning, and time series forecasting. He leads projects like aSTEP (spatio-temporal data analytics) and Light-AI for Cognitive Power Electronics. Key contributions include advancements in trajectory data processing, anomaly detection, and lightweight neural architectures. Research interests span machine learning, data mining, intelligent transport systems, and material science applications. Notable awards include the IJCAI 2019 Distinguished PC Member and Sapere Aude Research Leader (2018). He has supervised six PhD students and contributed to over 119 publications. His work is supported by grants from Villum Foundation and EU initiatives. Yang is involved in interdisciplinary collaborations, including data-driven decision-making frameworks and environmental monitoring systems. Labs and teams include the Daisy Center for Data-intensive Systems and AI for the People initiatives. Projects emphasize real-world applications in smart cities, traffic forecasting, and sustainable technologies. His research bridges theoretical foundations with practical implementations in domains like oceanography and crowdsourcing systems.

• 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.