جست‌وجوی استاد و پژوهشگر

Jure Leskovecمشاهده پروفایل

استاد

• Machine Learning
• Social Networks
• Data Mining
• +۴ مورد دیگر

Jure Leskovec is a Professor of Computer Science at Stanford University, affiliated with the Stanford AI Lab, Machine Learning Group, and the Center for Research on Foundation Models. He holds academic appointments in the Department of Computer Science and is a member of Bio-X, the Institute for Human-Centered Artificial Intelligence (HAI), and the Wu Tsai Neurosciences Institute. Leskovec earned his BSc from the University of Ljubljana (2004), PhD from Carnegie Mellon University (2008), and postdoctoral training at Cornell University. His research focuses on social networks, data mining, machine learning, and computational biomedicine, with contributions to graph neural networks, drug discovery, and AI applications in healthcare. His work has been applied to combat the COVID-19 pandemic and integrated into products at major tech companies. Leskovec’s publications reflect his expertise in network analysis, medical AI, and biological systems. His recent work includes foundational contributions to graph neural networks (e.g., PyG) and medical AI frameworks. His research has garnered numerous awards, including the Microsoft Research Faculty Fellowship and ICDM Research Contributions Award. Leskovec advises numerous doctoral and postdoctoral researchers, contributing to over 200 publications. His interdisciplinary collaborations span computational biology, healthcare analytics, and social systems, with a focus on leveraging AI to address real-world challenges.

Boro Jakimovskiمشاهده پروفایل

استادیار

• Grid computing
• High-performance computing
• Parallel and distributed processing
• +۱ مورد دیگر

Boro Jakimovski is an Assistant Professor at the Institute of Informatics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University in Skopje. He specializes in Grid computing, High-performance computing, and Parallel and distributed processing, with significant contributions to international projects like the European Grid Initiative and SEE-GRID series. PhD in Informatics (2010) - Thesis: Modelling and verification of Grid workflows MSc in Informatics (2004) - Thesis: Communications in Grids BSc in Informatics (2000) - Graduated top of class His research focuses on optimizing computational grids through adaptive workflows and genetic algorithms. He teaches courses such as Distributed Operating Systems and Software Construction, while previously tutoring foundational informatics topics including Algorithms and automata, Data structures, and Parallel processing. Publications span 18 international conferences and 1 journal article, with a notable awarded paper at MII 2003 . Key projects include FP7 coordination for Pan-European infrastructure and leadership in SEE-GRID initiatives as Grid Infrastructure Manager for Macedonia. Scientific Awards : Awarded paper at MII 2003 International Conference Grants : Participated in 15+ international projects (FP6, FP7, TEMPUS, UNESCO, DAAD, INTERREG III) International Engagement : Lectured at 20+ workshops, visited 10+ universities/summer schools Specializations include Grid infrastructure development, having completed professional visits to institutions like CERN (Switzerland), Humboldt University (Germany), and Software Technology Research Laboratory (UK). He chairs Macedonia's coordination in European Grid Initiative projects and contributes to curriculum development across SEE countries.

Kobus Barnardمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Scientific Applications
• +۳ مورد دیگر

Kobus Barnard is a Professor in the Department of Computer Science at the University of Arizona, with his office located in GS 708. His research bridges computer vision, machine learning, and interdisciplinary scientific applications across diverse domains. Education: Ph.D. from Simon Fraser University (1999) His research interests focus on extracting meaningful insights from complex data through computer vision and probabilistic modeling. Key areas include machine learning for environmental monitoring (flood detection, plant disease analysis), social dynamics (interpersonal coordination, emotional coregulation), astronomy (transient classification), and multimodal learning (visual-linguistic integration). His work consistently applies deep learning to real-world problems requiring high-resolution data interpretation. Analysis of his 2022-2025 publications reveals three dominant trends: (1) Environmental applications using satellite imagery for flood mapping and agricultural monitoring, (2) Cognitive modeling of human teams and emotional dynamics through probabilistic frameworks, and (3) Astronomical data analysis leveraging host galaxy properties for transient classification. These threads demonstrate his commitment to solving practical scientific challenges through computational innovation. While scientific awards aren't documented in available sources, his leadership in projects like FloodPlanet and ToMCAT indicates significant contributions to data infrastructure. His advising and grant activities remain unreported in the source material, though his extensive interdisciplinary collaborations suggest substantial mentorship impact. Barnard's work operates at the intersection of multiple scientific communities, evidenced by applications spanning neuroscience, agriculture, astronomy, and social science. His current focus on high-resolution data fusion and multimodal modeling positions him at the forefront of real-world AI deployment.

Muhammad Humayounمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Computational Linguistics
• Natural Language Processing
• +۵ مورد دیگر

Dr. Muhammad Humayoun is a Senior Lecturer at Karlstad University, Sweden, specializing in informatics education and computational linguistics research. He holds a Ph.D. from University of Grenoble Alpes (2012) and M.Sc. from Chalmers University (2006). His academic career spans over 15 years across Pakistan and Sweden, including teaching roles at COMSATS University, University of Central Punjab, and Higher Colleges of Technology. Research Focus: His work centers on NLP applications for under-resourced languages like Urdu/Punjabi, including text summarization, abusive language detection, and formalization of mathematical texts. He has developed linguistic resources (corpora, lexicons) and contributed to plagiarism detection systems in programming courses. Teaching Contributions: Designed and taught over 15 courses across multiple universities, including advanced programming, AI, and cloud computing modules. Currently teaches graduate-level courses like 'Legal Tech, AI and Rules-as-Code' and undergraduate software engineering courses at Karlstad University. Awards: Recognized for Urdu threat detection system (3rd place, 2021) and top rankings in Urdu fake news competitions. His work on Urdu summarization corpora has been widely cited in computational linguistics research.

Engin Erzinمشاهده پروفایل

استاد

• Artificial Intelligence
• Multimedia Systems
• Computer Vision
• +۶ مورد دیگر

Engin Erzin is a Professor at Koç University's College of Engineering, leading the KUIS AI Lab and Multimedia, Vision and Graphics Lab . His research focuses on AI-driven human-centric systems, affective computing, and multimodal interaction analysis. He has contributed extensively to robotics, speech processing, and human-robot interaction through over 70 peer-reviewed publications since 2008. Research interests include: Affective computing and emotion recognition from speech/gestures Human-robot interaction and socially engaging agents Speech-driven animation and gesture synthesis Multimodal data fusion for interaction analysis Deep learning applications in robotics and biomedical engineering Recent work emphasizes: Developing adaptive pHRI controllers for manufacturing tasks Creating engagement measurement frameworks for human-machine interfaces Advancing Turkish speech recognition through self-supervised learning Designing multimodal databases for interaction studies Labs: KUIS AI Lab : Focuses on AI applications in robotics and human-computer interaction Multimedia Lab : Specializes in vision, graphics, and audiovisual analysis

Jill L McNitt-Grayمشاهده پروفایل

استاد

• Biomechanics
• Multijoint Movement
• Motor Control
• +۷ مورد دیگر

Dr. Jill L. McNitt-Gray is a Professor of Biological Sciences and Biomedical Engineering at the University of Southern California (USC), serving as Director of the USC Biomechanics Research Laboratory. She also leads the Integrative and Evolutionary Biology Graduate Program, focusing on interdisciplinary research at the intersection of genomics, evolution, and physiology. Her academic roles include joint appointments in Biomedical Engineering and affiliations with the Center for Robotics and Embedded Systems, Center for Excellence in Genomic Science, and the Department of Veterans Affairs. Education: PhD in Biomechanics (Pennsylvania State University, 1989), MA in Biomechanics (UNC Chapel Hill, 1985), and AB in Mathematics/Statistics (Miami University, 1980). Her research explores mechanisms of multijoint movement control, injury prevention, and human performance optimization across sports, music, and clinical populations. She pioneered biomechanical analysis of wheelchair propulsion mechanics and movement strategies in athletes and musicians. Research Interests: Biomechanics of physically-demanding movements, motor control dynamics, neuromuscular coordination, injury prevention in sports/dance/music, rehabilitation engineering, and comparative biomechanics in mammals. She integrates experimental techniques, computational modeling, and field studies to address these topics. Awards: Recognized as a Fellow of the National Academy of Kinesiology (2023), International Society of Biomechanics (2015), and American Society of Biomechanics (2013). Honored with the Hay Award (2016), Harmon Brown Award (2016), and USC Distinguished Professorship (2016–2019). Her mentorship was acknowledged via the Mellon Award (2010) and leadership of STEM outreach programs. Labs/Teams: Directs USC Biomechanics Research Lab and collaborates with the Sports Science, Engineering, and Technology Academy. Leads the GREU mentorship program and consults for USC Athletics, the Colburn School of Music, and Rancho Los Amigos Rehabilitation Center.

• Privacy-Preserving Algorithms
• Differential Privacy
• Federated Learning
• +۶ مورد دیگر

Dr. Michael Shekelyan is a Lecturer (Assistant Professor) in Computer Science at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science. He holds a PhD in Computer Science from the Libera Università di Bolzano (2018) and a Diploma in Media Informatics from the University of Munich (2014). His research focuses on developing algorithms and data structures for managing large and sensitive datasets, with a particular emphasis on privacy-preserving techniques like differential privacy and federated learning. He has held postdoctoral roles at the University of Warwick and King's College London before joining QMUL in 2023. Research Interests: Privacy-preserving algorithms, differential privacy, federated learning, data management systems, randomized algorithms, and efficient query processing. His work bridges theoretical foundations with practical applications, aiming to enable secure data sharing while preserving individual privacy. Teaching: Leads undergraduate modules in Database Systems and Operating Systems at QMUL. His teaching emphasizes foundational concepts in computer science through rigorous coursework and practical projects. Grants and Funding: Currently supervises a PhD studentship titled 'Privacy-Preserving Algorithms: Unlocking Data Sharing for Medical Sciences & Machine Learning', funded by QMUL and open to UK home students. The role involves exploring privacy-preserving frameworks for collaborative data analysis. Professional Contributions: Serves as a reviewer for top-tier conferences (NeurIPS, ICML, SIGMOD, ICDE) and journals (IEEE TKDE, Data & Knowledge Engineering). Actively involved in conference organization, including NeurIPS Area Chair (2024) and ICDT Proceedings Chair (2024). Labs and Collaborations: Affiliated with the Centre for Fundamental Computer Science at QMUL, fostering interdisciplinary research in theoretical and applied computing. Engages with industry partners on privacy-enhancing technologies and data management solutions.

• Renaissance literature and culture
• Textual editing
• Book history/bibliography
• +۵ مورد دیگر

Sarah Neville is an Associate Professor jointly appointed in English and Theatre, Film, and Media Arts at The Ohio State University. Her expertise spans Renaissance literature, textual editing, book history, and Shakespearean performance studies, with a focus on how media technologies shape knowledge production and authority. Associate Editor, New Oxford Shakespeare (2016-17) Associate Coordinating Editor, Digital Renaissance Editions General Textual Editor, Linked Early Modern Drama Online Founder, Lord Denney’s Players academic theatre company Her 2022 monograph Early Modern Herbals and the Book Trade redefines scientific authority through printers' economic practices. She currently edits 2 Henry VI for the Arden Shakespeare. Recent publications demonstrate her interdisciplinary approach: 2023: Digital tool development (Database of Early English Playbooks) 2021: Textual theory in transatlantic context 2020: Digital performance adaptation and women's printing practices 2019: Digital commentary evolution Scientific awards include: 2020 Paul W. Brown Excellence in Teaching Award 2018 Columbus City Council commendation for innovative theater Her work intersects textual scholarship with material culture studies, particularly examining print capitalism's role in shaping scientific discourse during the Renaissance.

Shuting Wangمشاهده پروفایل

استادیار

• Big Data in Marketing
• Data Science/Analytics
• IT Strategy
• +۱۰ مورد دیگر

Shuting Wang is an Assistant Professor in the Paul H. Chook Department of Information Systems and Statistics at Baruch College's Zicklin School of Business. With a PhD in Management Information Systems from Temple University and prior degrees in Operations Management and Logistics Management, her research focuses on social media risks, fake news detection, and digital health platforms. PhD: Temple University (Management Information Systems) MSc: Shanghai University of Finance and Economics (Operations Management) BSc: Zhongnan University of Economics and Law (Logistics Management) Her expertise spans Big Data Marketing , Social Media Analytics , Technology Strategy , and Digital Health . Current research examines: Fake news mitigation through multimedia elements Telemedicine accessibility via SMS technology Social media's impact on business reputation FinTech startup success factors Psychological impacts of digital appearance Cybersecurity effects on startup funding Key Scientific Awards : Research Cluster Interdisciplinary Incentive Grants (2025) Eugene M. Lang Fellowship (2021) Presidential Fellowship at Temple University (2014) Full Tuition Scholarship at Shanghai University of Finance and Economics (2009) Active in teaching roles including Data Mining for Business Analytics and Database Management, she has received grants from the National Science Foundation and CUNY Central Office. Her work has been featured in outlets like NPR and Campaign US.

Jorge Cambaمشاهده پروفایل

دانشیار

• Intelligent Computer-Aided Design (CAD) Systems
• Digital Manufacturing Processes
• Digital Product Model Quality Assurance
• +۵ مورد دیگر

Jorge Camba is an Associate Professor at the School of Engineering Technology and holds a courtesy appointment in the Department of Computer Graphics Technology at Purdue University . He also serves as a Senior Research Scientist (by courtesy) in the Department of Industrial Engineering at the University of Naples Federico II , Italy. PhD in Systems and Engineering Management (Universidad Politécnica de Valencia, Spain) MSc in Digital Media (East Tennessee State University) MSc in Computer Science (Universidad de Vigo, Spain) His research explores intelligent CAD systems , digital manufacturing , and mixed reality environments , focusing on model quality assurance , design intent communication , and collaborative design tools . Recent work investigates spatial cognition in CAD education , geometric variability analysis , and annotation-driven knowledge management . Key trends in his publications include parametric modeling strategies , 3D annotation systems , and XR applications in design evaluation. Awards include the Purdue Faculty Scholar (2021) and I3B Fellow (2021). He has presented at conferences on topics like Industry 4.0 , space habitat design , and digital product quality .

Codina Bonilla, Lluísمشاهده پروفایل

دانشیار

• Web Positioning
• Semantic Web
• Information Systems
• +۷ مورد دیگر

Lluís Codina Bonilla is an Associate Professor at Pompeu Fabra University's Faculty of Communication, specializing in Journalism and Audiovisual Communication. As a founding member of the DigiDoc Research Group (SGR-01103) and Director of the Cybermedia Observatory, he bridges Information Science and Digital Communication through research on SEO, content curation, and digital media systems. PhD in Information Science (Universitat Autónoma de Barcelona) Co-founder of academic journal Hipertext.net Principal Investigator for multiple Spanish national R&D projects Research Interests: His work focuses on Search Engine Optimization (SEO) for news media, Semantic Web applications in journalism, and content curation systems. Recent studies explore AI applications in content creation and academic research. Academic Contributions: With over 200 articles and 6 books (including Design and SEO for Content-Intensive Websites ), his publications analyze digital media quality assessment, information architecture, and media verification. His 21 doctoral theses (all cum laude) highlight his role as a mentor in digital communication. Premio Roblón 2021 for Investigator of the Year Multiple UPF Social Council Awards for Teaching Quality Nominated Scimago Best Scientific Article Recognized Researcher Tranches (CNEAI/AQU) Academic Infrastructure: Leads the Cybermedia Observatory and contributes to UPF's SEO Media Lab, while maintaining affiliations with the Catalan Society of Communication and Institute of Catalan Studies. His teaching spans Journalism, Audiovisual Communication, and Research Master's programs.

• Geomatics
• 3D Modeling
• Digital Photogrammetry
• +۸ مورد دیگر

Filiberto Chiabrando is an Associate Professor at the Department of Architecture and Design (DAD) of Politecnico di Torino, with a secondary appointment as Adjunct Associate Professor at Michigan Technological University (USA). He serves as Deputy Coordinator of the Doctoral College for Architectural and Landscape Heritage and is Secretary of the ISPRS Working Group on UAS & Small Multi-sensor Platforms. His work bridges geomatics, photogrammetry, and cultural heritage preservation. Academic Affiliations Politecnico di Torino (Main Institution) Michigan Technological University (Adjunct Appointment) Research Leadership Coordinator of PIC4SeR Interdepartmental Center Principal Investigator for HERITALISE, Common Grounds, POSEIDON, ARCHIM3DES, and ResCult projects Chiabrando's research focuses on 3D modeling , UAV photogrammetry , underwater cultural heritage documentation , and HBIM-GIS integration . He specializes in SLAM systems , laser scanning , and rapid mapping for architectural conservation. His work aligns with SDGs 9 (Innovation), 11 (Sustainability), and 17 (Partnerships). His recent projects emphasize multitemporal marine vegetation mapping (POSEIDON), cloud-based heritage digitization (HERITALISE), and advanced 3D metric surveying in marine environments (ARCHIM3DES). He has developed open-source education platforms like POSER for underwater photogrammetry training. Scientific Awards Licinio Ferretti Award (ASITA, 2009 & 2010) Best Paper Awards: Sensors (2013), CIPA (2013) Editorial Roles Editorial Board: Geomatics Journal (2021-), ISPRS International Journal (2019-) As a PhD advisor, he has mentored 7 doctoral students in architectural heritage, including Alessio Calantropio (2019-2023) on underwater heritage and Alessandra Spreafico (2019-2023) on the Turin 1911 Exposition. He leads commercial contracts with organizations like DJI GmbH, World Food Programme, and UNICEF for UAV and geospatial applications.

• Digital Humanities
• Early Modern Literature
• Corpus Linguistics
• +۴ مورد دیگر

Heather Froehlich is an Assistant Specialist in Research Engagement at the University of Arizona Libraries, specializing in digital humanities and corpus linguistics. She holds affiliations with Literature Faculty, English Applied Linguistics, and RCTE (Research, Creation, and Teaching Excellence). Her work bridges traditional literary studies with modern computational methods, focusing on early modern texts, Shakespearean drama, and gender representation. Her research interests include quantitative literary analysis, corpus-based studies using tools like AntConc, and the integration of digital methods into pedagogy. Notable projects involve analyzing Aphra Behn’s works, transcribing recipe manuscripts, and exploring nuclear physics discourse through text corpora. Publications span topics from early modern drama’s social structures to postdoctoral labor advocacy. She actively promotes research data management and collaborates on interdisciplinary projects such as the Early English Books Online review and the Philosophical Magazine Nuclear Physics Corpus . Her contributions include advancing digital humanities pedagogy through EEBO-TCP integration in teaching and advocating for equitable academic labor practices via the Postdoctoral Laborers Bill of Rights .

Ahmet Tekalpمشاهده پروفایل

استاد

• Digital Image Processing
• Video Compression
• Motion-Compensated Video Filtering
• +۵ مورد دیگر

Ahmet Tekalp is a Professor in the Department of Electrical and Computer Engineering at Koc University's College of Engineering since 2001. He holds dual citizenship in Turkey and the USA, with prior academic roles at the University of Rochester (1986-2005) and research positions at Eastman Kodak (1984-1987) and Rensselaer Polytechnic Institute (1981-1984). He chairs the Electronics and Informatics Group at TUBITAK since 2004 as a part-time position. B.S. (1980) in Electrical Engineering & Mathematics, Bogaziçi University M.S. (1982) and Ph.D. (1984) in Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute His research focuses on digital image and video processing, including video compression, motion-compensated filtering for high-resolution applications, video segmentation, object tracking, content-based video analysis, multi-camera surveillance processing, and digital content protection. He has led numerous European and U.S. grants, including FP7 STREP projects and NSF awards, emphasizing applications in sensor networks, visual databases, and medical imaging. His scholarly work spans diverse areas such as superresolution reconstruction, head gesture animation, 3DTV streaming, and reversible data hiding. He has played pivotal roles in editorial boards, including serving as Editor-in-Chief of Signal Processing: Image Communication, and has contributed to major standards bodies like ISO MPEG and ANSI NCITS. Member, Turkish Academy of Sciences (TUBA) Fellow, IEEE Fulbright Senior Scholarship (1999) TUBITAK Science Award (2004) IEEE Signal Processing Society Distinguished Lecturer (1998) He has led multiple international research collaborations and projects, including European FP6/FP7 networks and NATO programs, with substantial grant funding from NSF, NYSTAR, and industry partners like Eastman Kodak, Xerox, and Siemens.

• Computer Vision
• Robotics
• Human-Computer Interaction
• +۴ مورد دیگر

Włodzimierz Kasprzak is a Professor at the Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology. His research focuses on computer vision, robotics, human-computer interaction, and machine learning. He has contributed to advancements in human action classification, skeleton-based feature analysis, and multimodal interface design. Research Highlights: Development of lightweight classification models for human actions in video using skeleton-based features. Advances in multi-stream fusion techniques for image and video analysis. Design of embodied agent systems for cybersecurity event visualization and control. Awards and Recognition: 2024: Individual First Class Rector's Award for Scientific Achievements (2022-2023) 2021: Medal of the Commission of National Education 2011: Golden Cross of Merit His work integrates theoretical contributions with practical applications in robotics, surveillance systems, and human-centered technologies.