جست‌وجوی استاد و پژوهشگر

Ahmet M. Tekalpمشاهده پروفایل

استاد

• Digital Image Processing
• Digital Video Processing
• Video Compression
• +۷ مورد دیگر

Ahmet M. Tekalp is a Professor of Electrical and Computer Engineering at Koc University , Istanbul, Turkey, since 2001. Previously, he held a full-time professorship at the University of Rochester (1986-2005) and part-time roles such as Chair of the Electronics and Informatics Group at TUBITAK, Turkey. His work bridges academic and industrial research, with affiliations to institutions like Eastman Kodak Company and Rensselaer Polytechnic Institute. Education: BS (1980), Electrical Engineering & Mathematics (High Honors), Bogaziçi University MS (1982) & PhD (1984), Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute (RPI) Research Interests: Digital image and video processing Video compression and streaming Motion-compensated video filtering for high-resolution Video segmentation and object tracking Content-based video analysis and summarization Multi-camera surveillance video processing Digital content protection Scientific Awards: Member, Turkish Academy of Sciences (TUBA) Fellow, IEEE Fulbright Senior Scholarship (1999) TUBITAK Science Award (2004), Turkey's highest science award Grants and Contracts: FP6 Network of Excellence, SIMILAR (2003-2007), Euro 6 Million FP6 Network of Excellence, 3DTV (2004-2008), Euro 6 Million FP7 STREP projects (DIOMEDES, SARACEN) with Euro 3 Million budgets NSF grants spanning wireless sensor networks, visual databases, and MRI motion artifact suppression Industry partnerships with Eastman Kodak, Xerox, Siemens Corporate Research Professional Activities: Editor-in-Chief, Signal Processing: Image Communication (Elsevier) Member, ERC-Advanced Panel on Informatics Editorial roles in IEEE journals and other publications Active in ISO/IEC and ANSI standards committees

• Corpus Linguistics
• Terminology
• Discourse Analysis
• +۱۱ مورد دیگر

Dr. Sandrine Peraldi is an Assistant Professor in Linguistics at the School of Languages, Cultures and Linguistics, University College Dublin (UCD). She currently serves as Head of Linguistics and Deputy Head of School, and coordinates the Graduate Diploma in Localisation. With a PhD from Paris Diderot University, her career includes over a decade as Research Director at ISIT in Paris, where she led interdisciplinary research and international collaborations. Her educational background includes: PhD in Theoretical, Descriptive and Automatic Linguistics, Paris Diderot University MLitt, Paris Diderot University Master’s in Language Industry and Specialised Translation Certification in University Teaching and Learning, UCD Dr. Peraldi's research focuses on Corpus Linguistics, Terminology, Discourse Analysis (especially in professional contexts), Intercultural Communication , and Translation Studies , with a strong emphasis on machine translation and post-editing. Her work bridges cognitive, technological, and professional dimensions of language use. Her recent publications reveal a clear trajectory toward the multimodal analysis of virtual workplace communication, particularly how engagement and non-verbal cues function in online meetings. She has also contributed significantly to metaphor analysis in political discourse and the integration of corpus tools in translation workflows. Her scientific contributions are recognized through active participation in peer review for journals such as Meta , TEANGA , and International Journal of Organisations , and editorial leadership as former Editor-in-Chief of the Bulletin du CRATIL . She has secured major funding from the European Commission (TransCert, QUALETRA, PICT, AGORA), UKRI-AHRC, and the National Forum for Teaching and Learning. She supervises PhD students and leads research projects such as the Interactional Variation Online project. She is also involved in professional service through the Human Research Ethics Committee and the EMT assessor network. Dr. Peraldi leads several research and teaching initiatives, including the ENEOLI Cost Action on lexical innovation and the development of scenario-based intercultural learning resources.

J. Stephen Downieمشاهده پروفایل

استاد

• Information Retrieval
• Digital Libraries
• Digital Humanities
• +۴ مورد دیگر

J. Stephen Downie is a Professor and Interim Executive Associate Dean at the School of Information Sciences, University of Illinois. He also serves as the Associate Dean for Research and Co-Director of the HathiTrust Research Center. His academic roles include leadership in digital libraries, digital humanities, and music information retrieval (MIREX). He holds a PhD in Library and Information Science from the University of Western Ontario. Research interests focus on information retrieval systems, multimedia MIR, political economy of communication networks, and database/web technologies. He co-founded ISMIR and directs the annual MIREX evaluation initiative. His work bridges computational analysis, cultural heritage preservation, and digital tool development. Recent scholarly output includes studies on plant systematics (Apiaceae family) and cultural heritage technologies. His projects involve collaborative research on digital libraries, data capsules, and federated repository systems. Notable organizational roles include leadership in HathiTrust and academic service in the National Center for Supercomputing Applications. Teaching responsibilities include doctoral seminars and independent studies. Active projects span computational text mining, structural analysis of music information, and accessibility initiatives for academic content.

Sushil Awaleمشاهده پروفایل

پژوهشگر

• Multimodal Information Retrieval
• Question Answering
• Knowledge Graphs
• +۳ مورد دیگر

Sushil Awale is a Research Associate at the Visual Analytics Research Group, TIB Hannover , Germany, and a PhD candidate at Leibniz Universität Hannover , supervised by Prof. Dr. Ralph Ewerth. His research focuses on Multimodal Information Retrieval , Question Answering , and Knowledge Graphs . Previously, he worked as a Student Assistant in the Language Technology Group at Universität Hamburg, developing NLP-driven scholarly systems. M.Sc. in Intelligent Adaptive Systems (2020–2023), Universität Hamburg B.Sc. in Computer Science (2015–2020), Tribhuwan University, Nepal His research interests span patent domain analysis , multimodal systems , and language resources for under-resourced languages . Recent work includes visual patent search interfaces and large vision-language models for classification tasks. Publications highlight contributions to scholarly knowledge graphs (e.g., DBLP-QuAD dataset) and AI-enhanced research advisory systems (ARDIAS). He also contributed to preprocessing Nepali language corpora and enriching Hindi WordNet via knowledge graph techniques. Currently affiliated with TIB’s Visual Analytics Group, he actively organizes events like the Scholarly Question Answering over Linked Data workshop at ISWC 2023.

Michele Lanzaمشاهده پروفایل

استاد

• Software Engineering
• Software Visualization
• Software Evolution
• +۷ مورد دیگر

Michele Lanza is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), Lugano, where he co-founded the faculty in 2004. He is the founder and director of the Software Institute (since 2017) and leads the REVEAL research group, focusing on software visualization, evolution, and analytics. He holds a PhD from the University of Bern (2003), where he also earned his MSc (1999), and was a postdoctoral researcher at the University of Zurich. Research Interests: Software Engineering Software Visualization (notably the 'City Metaphor') Mining Software Repositories (MSR) Software Evolution and Analytics Program Comprehension Reverse Engineering and Architecture Recovery His recent publications (2023–2025) emphasize immersive software visualization in virtual reality, automated documentation, code refactoring, and empirical studies on developer behavior and documentation. There is a strong trend toward human-centric, visual, and data-driven approaches, often leveraging VR and interactive tools for deeper software understanding. Scientific Awards: Ernst Denert Award (2003) Credit Suisse Teaching Award (2007, 2009) Best Paper Awards (SANER 2024, VISSOFT 2022, ICPC 2016) Most Influential Paper Award (MSR 2010) Advising and Grants: Prof. Lanza has supervised over 13 PhD students and numerous MSc and BSc theses, fostering a vibrant research group. He leads multiple funded projects, including SNF grants (FORCE, TUML, INSTINCT, PROBE, ESSENTIALS, BIGDATA), FFL (CSRD), and industry R&D initiatives. Funding supports travel, hardware, software, and PhD positions, enabling cutting-edge research in software engineering. Labs and Teams: He leads the REVEAL research group and the Software Institute at USI, which serve as hubs for innovation in software visualization, mining, and evolution. These teams are highly collaborative, interdisciplinary, and active in top-tier conferences (ICSE, FSE, ICSME, MSR, VISSOFT).

Raymond Chengمشاهده پروفایل

پژوهشگر

• Security
• Privacy
• Distributed Systems
• +۵ مورد دیگر

Raymond Cheng is a Researcher and blockchain lecturer with a focus on security, privacy, and distributed systems. He earned his Ph.D. in Computer Science from the University of Washington and holds degrees in Physics, Electrical Engineering, and Computer Science from MIT. His research spans blockchain scalability, privacy-preserving protocols, and decentralized infrastructure. Key projects include Kariba Labs , MASQ Foundation , and Open Source Observer , where he works on tools for public goods funding, secure smart contracts, and open-source analytics. Raymond's publications highlight advancements in blockchain-based databases (FalconDB), confidential smart contracts (Ekiden), and privacy-preserving messaging (Talek). His work often intersects with internet freedom and secure, scalable systems. He co-founded multiple organizations, including the Decentralization Institute and Public Goods Foundation , and has been featured in Forbes , Wired , and MIT Technology Review for his contributions to privacy and blockchain innovation.

Luis Velez Quinteroمشاهده پروفایل

استادیار

• Data Science
• Extended Reality (XR)
• Machine Learning
• +۴ مورد دیگر

Luis Velez Quintero is an Assistant Professor at Stockholm University within the Department of Computer and Systems Sciences (DSV) . He is affiliated with the Data Science Research Group and the Stockholm Technology & Interaction Research (STIR) group, focusing on Human–Computer Interaction. His research spans adaptive immersive systems, affective computing, and physiological signal analysis in extended reality (XR) environments. Education & Background : Holds a PhD in Computer and Systems Sciences from Stockholm University (2023), MSc in Health Informatics from Karolinska Institutet (2019), and BSc in Electronics Engineering from the National University of Colombia (2015). He has led the startup PortalSense since 2018, developing VR solutions for real estate visualization. Research Interests : Combines data science and ML with XR technologies to create context-aware systems for healthcare, education, and professional training. Key themes include: Adaptive VR/AR systems using real-time physiological and behavioral signals Biosignal integration for personalized user experiences Immersive technologies for cognitive assessment and skill development Publications : Over 20 peer-reviewed articles, including work on affective databases (AVDOS-VR), biosignal frameworks (Excite-O-Meter), and XR applications in cybersecurity education. Recent efforts explore third-person locomotion in VR and early-stage Alzheimer’s detection via spatial navigation tasks. Awards & Grants : Wallenberg Foundation Grant (2023-2025): Analyzing non-verbal communication in psychotherapy Swedish Institute Scholarship (2017-2019): Fully funded Master’s and PhD studies Seed funding for PortalSense from Fondo Emprender SENA Colombia (2022-2023) Advising & Projects : Lead researcher in projects like AVDOS-VR and CS:NO . Co-designed the Excite-O-Meter open-source plugin for real-time physiological analysis in VR. Active in industry collaborations for scalable health interventions and immersive training systems. Labs & Teams : Collaborates with multidisciplinary teams at STIR and DSV, advancing human-centered AI and adaptive XR technologies.

Lin Weisiمشاهده پروفایل

استاد

• Artificial and Augmented Intelligence
• Computer Science and Engineering
• Electrical and Electronic Engineering
• +۵ مورد دیگر

Prof. Lin Weisi is an Associate Dean (Research) and Professor at the College of Computing & Data Science, Nanyang Technological University (NTU). He holds the President's Chair in Computer Science and is a Fellow of IEEE and IET. His research focuses on image processing, video compression, multimedia communication, and AI-driven applications. He has authored over 400 refereed papers, holds 16 patents, and contributed to international standards. Notable contributions include the COVID-19 Test Strip Reader and databases like the Retargeted Image Subjective Quality Database . He leads the ROSE Lab and has supervised numerous students and researchers globally. His awards include Fellowships from SIET and excellence recognitions in China and Singapore. Educational Background: B.Sc./M.Sc. (Electronics/Digital Signal Processing, Sun Yat-Sen University), Ph.D. (Computer Vision, King’s College London). Research Interests: Perception-based modeling, neural network compression, AI for environmental monitoring, and perceptual quality assessment. His work bridges academic research and industrial deployment, emphasizing practical applications. Grants & Projects: Managed over 10 major projects in digital multimedia, including collaborations with institutions like the Institute for Infocomm Research and Tencent. Current initiatives include lightweight deep learning for image processing and AI-driven climate monitoring. Awards & Honors: Recognized as a Chartered Engineer, Honorary Fellow of SIET, and recipient of prestigious awards in China and internationally.

Josef Sivicمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Image and Video Retrieval
• Object Recognition
• +۳ مورد دیگر

Josef Sivic is a Research Fellow at the University of Oxford's Department of Engineering Science, part of the Visual Geometry Group. He works closely with Professor Andrew Zisserman. His research focuses on computer vision, object recognition, and video retrieval. Sivic holds a PhD from the University of Oxford (thesis on visual search) and a Master's from Czech Technical University under Tomas Pajdla. Education: PhD in Computer Vision, University of Oxford Master's in Computer Science, Czech Technical University (Prague) His research interests include unsupervised visual object category recognition, person spotting in videos, and developing algorithms for image and video analysis. Notable contributions include work on object discovery in image collections and automatic naming of TV video characters. He has received the Best Industrial Paper Prize at BMVC 2006. His publications span topics like multi-segmentation techniques, person detection in videos, and object localization. Sivic's work bridges theoretical computer vision with practical applications in multimedia retrieval and machine learning.

Lei Chenمشاهده پروفایل

استاد

• Data-Driven Machine Learning
• Crowdsourcing-Based Data Processing
• Uncertain and Probabilistic Databases
• +۳ مورد دیگر

Lei Chen is a Chair Professor and Director of HKUST Big Data Institute at the Hong Kong University of Science and Technology , where he has served since 2005. His research spans data-driven machine learning , crowdsourcing systems , and uncertain database processing , with notable contributions in privacy-preserving spatial queries and graph neural networks . Ph.D. in Computer Science, University of Waterloo (2004) MS in Computer Science, Asian Institute of Technology (1997) BS in Computer Science, Tianjin University (1994) His work focuses on: Spatial Crowdsourcing - Efficient task assignment and privacy frameworks Graph Processing - Novel indexing for heterogeneous networks Explainable AI - Human-centric model interpretation techniques Uncertain Data - Probabilistic query processing with crowdsourcing Recent publications cluster around secure data federation , distributed graph training , and privacy-preserving mobility systems , reflecting his leadership in ACM and IEEE communities. Students include 15 active Ph.D. candidates and 20+ graduated researchers now at institutions like BeiHang University and Huawei Noah's Ark Lab . Awards: ACM Fellow (2024), VLDB Best Paper (2022), SIGMOD Test-of-Time Award (2015).

Shounak Roychowdhuryمشاهده پروفایل

دانشیار

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Shounak Roychowdhury is an Associate Professor of Practice at the School of Information, University of Texas at Austin. He holds a PhD in Computer Engineering from the University of Texas at Austin (2013) and an MS in Computer Science from the University of Tulsa (1997). His teaching focuses on foundational and advanced topics such as Computer Vision, Database Management, Programming, and Data Science. Recent courses include INF 385T: Special Topics in Information Science: Computer Vision (2025) and I 320D: Topics in Human-Centered Data Science: Database Design (2024). Roychowdhury's research spans Computer Science , Machine Learning , and Software Engineering , with a focus on probabilistic methods, fuzzy systems, and medical informatics. His work explores areas like fault localization in software, data clustering optimization, and applying generative models to healthcare analytics. He has also contributed to fuzzy logic applications in decision-making and pattern recognition. His publications highlight interdisciplinary approaches, including Alzheimer’s disease modeling with GANs and color space analysis in art through probabilistic divergences. While no scientific awards are listed, his work reflects sustained contributions to theoretical and applied computing. Roychowdhury advises no listed students but maintains an active teaching role. No specific grants or labs are mentioned, though his research aligns with computational and data-driven methodologies.

Sunil K. Prabhakarمشاهده پروفایل

استاد

• Database Systems
• Data Management
• Uncertain Data
• +۴ مورد دیگر

Sunil K. Prabhakar is a Professor of Computer Science at Purdue University, currently serving as the Vice Provost for Faculty Affairs and former Department Head. He holds a PhD from the University of California, Santa Barbara, and a BTech from the Indian Institute of Technology, Delhi. Education: PhD, Computer Science, University of California, Santa Barbara, 1998 MS, Computer Science, University of California, Santa Barbara, 1998 BTech, Electrical Engineering, Indian Institute of Technology Delhi, 1990 Research Interests: Focuses on database systems, uncertain data management, cloud database integrity, sensor databases, and digital rights management. His work emphasizes developing systems for probabilistic data, ensuring authenticity in outsourced databases, and scalable solutions for multimedia and sensor applications. Grants & Projects: NSF Grant IIS-1017990: Ensuring Integrity of Outsourced Databases NSF Grant IIS-09168724: Uncertain Data Management Students & Advising: Advised over 15 PhD and MS students, including Ryan Rossi (Palo Alto Research Center), Rohit Jain (Google), and Reynold Cheng (University of Hong Kong). Labs & Teams: Involved in projects like the ORION uncertain data management system, the C4E4 environmental cyberinfrastructure initiative, and collaborations with industry (e.g., Naval Surface Warfare Center).

Allen E. Tullosمشاهده پروفایل

استاد

• Critical Spatial Theory
• Digital Scholarship
• American Popular Music
• +۴ مورد دیگر

Allen E. Tullos is a Professor of History at Emory University and Co-Director of the Emory Center for Digital Scholarship. He holds joint appointments in American Studies (Graduate Institute of Liberal Arts) and affiliated roles in African American Studies, Women’s Studies, and the Department of History. His research focuses on critical spatial theory, digital scholarship, American popular music, and the U.S. South. Tullos earned his PhD in American Studies from Yale University (1985), with earlier degrees from the University of North Carolina and the University of Alabama. Key roles include co-founding the peer-reviewed journal Southern Spaces , producing award-winning documentaries (e.g., A Singing Stream ), and directing the Poets in Place multimedia series. His book Habits of Industry won the Charles S. Sydnor Prize. Tullos has secured major grants from the NEH, Mellon Foundation, and Emory’s Digital Scholarship initiatives. Teaching spans undergraduate and graduate courses in American Studies, Southern History, and digital media. He has advised over 30 PhD students, many now in academic or museum leadership roles. Tullos’s work bridges traditional scholarship with digital innovation, emphasizing regional narratives and public humanities. Grants include the NEH’s Trans-Atlantic Slave Trade Database enhancement and Emory’s Sickle Cell Information Center redesign. His service includes advisory roles for the American Routes radio program, Encyclopedia of Alabama, and Folkstreams documentary archive.

CHANG Ee Chienمشاهده پروفایل

دانشیار

• Information Security
• Cloud Security
• Adversarial Machine Learning
• +۶ مورد دیگر

CHANG Ee-Chien is an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He serves as the Lead Principal Investigator of the National Cybersecurity R&D Laboratory (NCL) and previously served as Deputy Director of the Center for Technology, Robotics, Artificial Intelligence and the Law (TRAIL) from 2019 to 2022. He also chaired the Joint Academic Committee for the Bachelor of Computing in Information Security program from 2016 until April 2023. Dr. Chang received his Ph.D. in Computer Science from New York University in 1998, following his M.Sc. and B.Sc. in Mathematics from the National University of Singapore in 1993 and 1991 respectively. He completed postdoctoral work with DIMACS at Rutgers University and NEC Labs America. His research focuses on information security, multimedia security, and their intersection. His work spans from foundational research in cryptographic techniques for noisy data and image watermarking to contemporary challenges in data privacy, cloud security, and adversarial machine learning. Dr. Chang has published extensively in top-tier security and computer science venues including CCS, EUROCRYPT, USENIX Security, and ACM Multimedia. Analysis of his recent publications reveals a strong emphasis on practical security solutions using hardware features like Trusted Execution Environments, innovative approaches to watermarking using generative models, and addressing emerging threats in machine learning systems. His work bridges theoretical cryptography with real-world security challenges, particularly in cloud infrastructure and privacy-preserving technologies. Active leadership in National Cybersecurity R&D Laboratory Extensive service on program committees for major security conferences Consultancy roles with Huawei, i-Sprint, and Singapore Accreditation Council Media commentary on cybersecurity issues for major Singaporean outlets Dr. Chang has mentored numerous research fellows and students who have gone on to academic and industry positions worldwide. His educational contributions include developing cybersecurity curriculum and innovative teaching methods such as penetration testing using real-world university applications. He has taught core security courses including CS2107 Introduction to Information Security continuously since 2014.

Michael Winterمشاهده پروفایل

استاد

• Programming Languages
• Semantics of Programming Languages
• Program Verification
• +۵ مورد دیگر

Michael Winter is a Professor in the Department of Computer Science at Brock University, Canada. He holds a Habilitation from the University of the Federal Armed Forces, Munich (2002), a Ph.D. (Dr. rer. nat.) from the same institution (1998), and a Master of Computer Science (Dipl. Inform.) (1993). His research focuses on programming languages, semantics, program verification, relational methods, category theory, and fuzzy logic. He is the Managing Editor of the Journal on Relational Methods in Computer Science . Winter's academic roles include teaching courses such as COSC 2P05 (Programming Languages), COSC 3P91 (Advanced Object-Oriented Programming), and COSC 5P02 (Logic in Computer Science). He has advised numerous graduate and undergraduate students on topics including fuzzy relational analysis, program verification, and formal methods. His research contributions span over 100 publications in journals and conferences, emphasizing relational algebra, category theory, and their applications in computer science. His work integrates theoretical foundations with practical applications, such as developing tools like RelView for relational computation and exploring applications in ambient intelligence and data visualization. Winter collaborates internationally, contributing to conferences like RAMiCS and publishing in journals like Fuzzy Sets and Systems and Journal of Logical and Algebraic Methods in Programming .