جست‌وجوی استاد و پژوهشگر

Jeremy Claude Barnesمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Sentiment Analysis
• Cross-lingual Learning
• +۷ مورد دیگر

Jeremy Claude Barnes is a postdoctoral researcher in the Department of Informatics at the University of Oslo, affiliated with the Language Technology Group. His work is centered on advancing natural language processing, particularly in sentiment analysis, cross-lingual transfer, and low-resource settings. Research Interests: Sentiment Analysis and Structured Sentiment Cross-lingual and Transfer Learning Negation and Speculation Detection Weak Supervision and Data Programming (e.g., skweak) Dialectal and Social Media NLP Norwegian Language Technology His recent publications show a strong focus on leveraging multi-task learning, graph-based parsing, and weak supervision to improve sentiment systems in both high- and low-resource languages. He has contributed significantly to Norwegian NLP through datasets and models. Scientific Contributions: Development of skweak , a weak supervision framework for NLP Creation of annotated datasets for Norwegian negation and dialects Advancements in structured sentiment analysis via dependency graphs Studies on emotion and sentiment transfer across languages Jeremy Barnes collaborates extensively with researchers at the University of Oslo, including Lilja Øvrelid, Erik Velldal, and Pierre Lison. He has not been mentioned as advising students or receiving awards in the available text. He is actively publishing and contributing to major NLP venues, indicating an ongoing and impactful research career.

• Wireless Communications
• Reconfigurable Intelligent Surfaces
• 5G/6G Networks
• +۷ مورد دیگر

Professor Robert Schober is a distinguished academic at Friedrich-Alexander-Universität Erlangen-Nürnberg, leading the Institute for Digital Communications within the Department of Electrical-Electronic-Communication Engineering. His extensive research portfolio spans wireless communications, reconfigurable intelligent surfaces, 5G/6G networks, molecular communications, and integrated sensing and communication systems. His research interests focus on cutting-edge wireless technologies including Reconfigurable Intelligent Surfaces (RIS), Non-Orthogonal Multiple Access (NOMA), UAV communications, and Simultaneous Wireless Information and Power Transfer (SWIPT). Professor Schober's work bridges theoretical foundations with practical implementations, particularly in next-generation wireless systems. His recent publications demonstrate significant contributions to 6G/B6G wireless communications, with particular emphasis on RIS-assisted systems, movable antenna technologies, integrated sensing and communication, and molecular communication paradigms. His research often explores performance tradeoffs, optimization techniques, and novel system architectures for future wireless networks. Professor Schober has received recognition through numerous high-impact publications in top-tier IEEE journals and conferences, establishing him as a leading researcher in next-generation wireless communications. His work consistently addresses both theoretical challenges and practical implementation considerations. His research group actively collaborates with international partners, as evidenced by the diverse authorship on his publications, and maintains strong connections with both academic and industry stakeholders in the telecommunications field.

• Morphosyntax
• Psycholinguistics
• Language Revitalization
• +۳ مورد دیگر

Christopher M. Hammerly is an Assistant Professor in the Department of Linguistics at the University of British Columbia, directing the Experimental Linguistics and Fieldwork Lab (ELF-Lab). He holds a PhD from UMass Amherst and dual undergraduate degrees from the University of Minnesota in Linguistics and Psychology. His research focuses on morphosyntax, psycholinguistics, and the revitalization of Anishinaabemowin (Ojibwe), leveraging computational tools and experimental methods. Key projects include developing speech synthesis systems for Indigenous languages and creating participatory educational technologies. His work bridges formal linguistic theory with applied language revitalization efforts, emphasizing community collaboration. Education: PhD in Linguistics, University of Massachusetts Amherst (2020) BA in Linguistics, University of Minnesota (2014) BS in Psychology, University of Minnesota (2014) Research interests integrate cognitive and formal approaches to syntax and morphology, particularly exploring how linguistic units like person/number systems participate in long-distance dependencies. He actively applies linguistic research to build curricula and technologies for language preservation, collaborating with Indigenous communities to ensure culturally responsive solutions. Recent work includes advancements in multilingual speech synthesis, low-resource machine translation for Ojibwe verbs, and participatory design frameworks for Indigenous language education tools. His talks emphasize bridging computational linguistics with community-based language revitalization, such as presenting at the University of Colorado Boulder on integrated learning platforms for Border Lakes Ojibwe.

Lene Antonsenمشاهده پروفایل

استاد

• Sami Linguistics
• Indigenous Language Technology
• Computational Linguistics
• +۱۲ مورد دیگر

Lene Antonsen is a Professor of Sami Linguistics at the Department of Language and Culture, Faculty of Humanities, Social Sciences and Teacher Education, UiT The Arctic University of Norway. Her research and teaching are centered on the linguistic and technological aspects of Sami languages, with a focus on language preservation, computational modeling, and pedagogy. University: UiT The Arctic University of Norway School: Faculty of Humanities, Social Sciences and Teacher Education Department: Department of Language and Culture Email: lene.antonsen@uit.no Research Interests: Lene Antonsen’s work spans Sami dialects, grammatical structures, language change, and the development of digital tools such as machine translation and digital dictionaries. She is deeply involved in applying language technology to support Sami language use in education and public life. Recent Research Trends: Her recent publications reflect a strong trend in computational linguistics for Indigenous languages, particularly focusing on rule-based NLP, morphological modeling, and the use of North Saami as a pivot for translating into other Saami languages. She explores both theoretical linguistic phenomena and practical applications in education and language revitalization. Scientific Contributions: While no formal awards are listed, her extensive publication record in journals like Acta Borealia , Morphology , and Nordlyd demonstrates significant scholarly impact. She is a key contributor to the GiellaLT infrastructure, a multilingual, rule-based NLP framework for minority languages. Teaching and Advising: She teaches courses in North Saami at both bachelor’s and master’s levels and supervises master’s and PhD students. Her pedagogical work includes integrating authentic texts into grammar exercises and linking language learning to practical activities. Research Groups and Projects: She is a member of the Giellatekno research group and involved in projects such as the development of digital resources for Sami languages and a 2023 writing seminar for publication. Her work often involves collaboration with Trond Trosterud, Laura Alexis Janda, and other experts in computational and Indigenous linguistics.

• Biomedical Signal Processing
• Unobtrusive Sensing
• Medical Devices
• +۵ مورد دیگر

Esteban J. Pino is an Associate Professor at Universidad de Concepcion, Chile, actively engaged in research at the intersection of biomedical engineering and healthcare technology. His work focuses on developing innovative medical devices and signal processing techniques for clinical applications. His research interests span biomedical signal processing , unobtrusive sensing , and medical device development , with particular emphasis on respiratory monitoring, cardiac diagnostics, and pediatric health interventions. Utilizing advanced computational models and machine learning, his work bridges engineering solutions with real-world medical challenges. The recent publications highlight a strong trend in portable diagnostic systems , neural signal interpretation , and digital health frameworks for chronic disease management and early childhood development. These contributions reflect a multidisciplinary approach combining engineering, neuroscience, and clinical medicine. Dr. Pino serves as an Associate Editor for Connected Health in Frontiers in Digital Health , contributing to the peer-review and editorial process in his domain. He collaborates extensively across international research networks, as evidenced by co-authorship with researchers from diverse institutions. Though no formal advisees are listed, his editorial role and publication record suggest active mentorship and leadership in the academic community. His work is centered on practical, deployable healthcare technologies, particularly in low-resource or home-based settings, aiming to improve diagnostic accessibility and patient outcomes.

Michael Greenbergمشاهده پروفایل

پژوهشگر

• Programming Languages
• Static Analysis
• Type Systems
• +۴ مورد دیگر

Michael Greenberg is a researcher at Stevens Institute of Technology. He actively contributes to programming language design, static analysis, and formal methods, with a focus on Datalog, SMT solvers, and type systems.

• Robotics
• Control Systems
• Cyber-Physical Systems
• +۴ مورد دیگر

Tomasz Winiarski is an Assistant Professor at the Institute of Control and Computation Engineering, part of the Faculty of Electronics and Information Technology at Warsaw University of Technology. His research focuses on robotic systems design, control systems engineering, and cyber-physical systems. He has contributed to projects involving ROS-based robotic frameworks, SysML metamodeling, and assistive robotics applications. Education: PhD in Automation and Robotics (2009). Research interests include: Robot Operating System (ROS) and metamodeling frameworks Impedance-controlled manipulators and human-robot interaction Cyber-physical systems design and validation Multi-agent robotic systems and task scheduling Awards include the Rector's Award for Scientific Achievements (2015) and the Medal of the National Education Commission (2018). He has published extensively on topics ranging from robotic control architectures to hardware-software co-design strategies. Key projects include the development of the MeROS metamodel, the Rico assistive robot platform, and the TaskER scheduling framework. His work emphasizes practical applications of robotics in industrial and healthcare contexts.

Ahmet Sayarمشاهده پروفایل

دانشیار

• Distributed Systems
• Big Data
• Data-Intensive Computing
• +۷ مورد دیگر

Assoc. Prof. Dr. Ahmet Sayar is an Associate Professor at the Department of Computer Engineering, Faculty of Engineering at Kocaeli University, Turkey. He holds an M.Sc. (2001) and Ph.D. (2009) in Computer Science from Syracuse and Indiana Universities, USA. His research focuses on Distributed Systems, Big Data, Data-Intensive Computing, Geographic Information Systems (GIS), and Exploratory Data Analysis (EDA). He has co-authored over 150 papers, 15 book chapters, and 1 book. Currently, he serves as Head of Student Affairs at Kocaeli University and as an associate editor for multiple journals. Education: M.Sc. in Computer Science, Syracuse University (2001) Ph.D. in Computer Science, Indiana University (2009) Research Interests: Parallel and Distributed Algorithms Big Data Analytics & Cloud Computing Machine Learning Applications (e.g., Image Processing, NLP) GIS and Remote Sensing Blockchain Technology for IoT and Logistics Recent Trends in Articles: His recent work emphasizes real-time data processing (e.g., video stream analytics), blockchain for supply chains, and AI-driven solutions for healthcare, transportation, and urban management. He explores ethical aspects of web scraping and low-code platforms for process automation. Advising & Grants: Advised 18 master’s/phd theses. Involved in TÜBİTAK projects and KOSGEB innovation programs. Member of editorial boards and national advisory committees. Labs/Teams: Leads university-level student affairs initiatives and collaborates on interdisciplinary projects involving distributed systems and big data frameworks.

Metafas Dimitriosمشاهده پروفایل

مدرس

• Real-Time Software development
• System-On-a-Chip design
• DSP architectures
• +۴ مورد دیگر

Metafas Dimitrios is a Lecturer in the Department of Electrical and Electronic Engineering at the University of West Attica, School of Engineering. His office is located in Building Z, Room ZB201. He holds a Doctoral Degree from the University of Patras (1993) and an Electrical Engineering Diploma (1987). His research focuses on Real-Time Software, System-On-a-Chip design, DSP architectures, and applications of AI/Machine Learning in games and education. Teaches courses such as Introduction to Programming, Algorithms and Data Structures, and UML-based system design methodologies. Active in interdisciplinary research, including educational technology and embedded systems. Recent work emphasizes AI-driven educational tools and reinforcement learning applications in gaming. Earlier contributions span wireless communication systems, VLSI design, and hardware-software co-development.

Dong Maمشاهده پروفایل

استادیار

• Mobile Computing
• Wearable Sensing Systems
• Health Monitoring
• +۳ مورد دیگر

Roles & Affiliations: Assistant Professor at Singapore Management University's School of Computing and Information Systems (since 2022). Visitor at University of Cambridge (April 2025–present), with planned move as Associate Professor in Jan 2026. Previously postdoc at University of Cambridge (2020–2022) and PhD from University of New South Wales (2019). Research Interests: Focuses on mobile/wearable computing, health monitoring via earables, and tiny machine learning on embedded devices. Develops systems to analyze human behavior (activity/interaction) and physiological states (e.g., vital signs) in real-world scenarios. Recent work includes respiratory monitoring using earbuds and energy-efficient sensing systems. Awards & Recognition: Google South Asia & Southeast Asia Research Award (2024) Mark Weiser Best Paper Award at IEEE PerCom (2024 & 2025) EPFL Engineering PhD Summit (2019): 1 of 11 worldwide Academic Service: Serves on TPC for major conferences (MobiCom, PerCom, CHI) and editorial boards (IMWUT). Organized workshops like BodySys@MobiSys'24 and co-chair roles in conference committees. Labs/Teams: Leads research groups in wearable sensing and edge AI at SMU. Collaborates with institutions like Nokia Bell Labs, CSIRO, and University of Cambridge on projects funded by ERC and industry grants.

Helen Yannakoudakisمشاهده پروفایل

مدرس ارشد

• Natural Language Processing
• Machine Learning
• Few-Shot Learning
• +۵ مورد دیگر

Helen Yannakoudakis is a Senior Lecturer in Natural Language Processing at King's College London's Department of Informatics, affiliated with the University of Cambridge's NLIP Group. She holds a PhD from the University of Cambridge and has served as a Turing Fellow and Fellow of the Higher Education Academy. Her research focuses on machine learning for NLP, including few-shot learning, meta-learning, and societal applications like hate speech detection and educational tools. She has won the NeurIPS 2020 Hateful Memes Challenge and led the development of Write&Improve, an automated writing assessment system. Education: PhD in Natural Language Processing (University of Cambridge), MPhil in Computer Speech, Text & Internet Technology (Cambridge), BSc in Computer Science (Athens University of Economics & Business). Research Interests: Few-shot learning, multilingual NLP, abusive language detection, mental health detection, and automated language teaching. Her work bridges machine learning and education, with applications in bias mitigation and ethics in AI. Publications: Over 20 peer-reviewed papers in top venues (ACL, NeurIPS, EMNLP) covering topics like GEC, hate speech detection, and meta-learning frameworks. Recent work includes prompting LMs for language education and commonsense-enhanced transformers for comprehension. Awards & Roles: Area Chair for ACL 2025/NeurIPS 2024, co-founder of Kinhub (AI education tools), and contributor to the English Profile Programme. Her research emphasizes ethical AI and real-world societal impact.

• Medical Information Systems
• IoT for Healthcare
• Software Development Methodologies
• +۳ مورد دیگر

Dragan Jankovic is a prominent researcher at the University of Niš, Faculty of Electronic Engineering , Department of Computer Science and Informatics. His work spans multiple disciplines with a focus on Medical Information Systems , IoT for Healthcare , and Multi-Valued Logic applications. Collaborating extensively with researchers like Petar Rajkovic and Aleksandar Milenkovic, Jankovic has contributed to the evolution of resource-aware systems, software development methodologies, and digital logic optimization.

K. G. Karthikeyanمشاهده پروفایل

دانشیار

• Computer Architecture
• Machine Learning
• Parallel Computing
• +۳ مورد دیگر

K. G. Karthikeyan is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Madison. His research focuses on cutting-edge advancements in computer architecture, machine learning, and hardware acceleration. Primary Affiliation: Civil and Environmental Engineering Additional Affiliation: Environmental Chemistry and Technology His work spans multiple domains including: Computer architecture optimization GPU acceleration techniques Dataflow processing models Transformer efficiency improvements Moore's Law alternatives Hardware-software co-design Research trends from his publications show a strong emphasis on: Breaking traditional computing limitations Developing energy-efficient architectures Creating flexible acceleration frameworks Advancing deep learning hardware Exploring von Neumann alternatives Pioneering open-source computing platforms

Jing Yangمشاهده پروفایل

دانشیار

• Machine Learning
• Wireless Communications
• Information Theory
• +۴ مورد دیگر

Jing Yang is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Virginia, with a secondary appointment (by courtesy) in the Department of Computer Science. Previously, she was an Assistant and then tenured Associate Professor at the Pennsylvania State University. Her educational background includes a B.S. from the University of Science and Technology of China (USTC), and M.S. and Ph.D. degrees from the University of Maryland, College Park, all in Electrical Engineering. Dr. Yang's research spans machine learning, wireless communications and networking, and information theory. Her current focus includes transformers and large language models (LLMs), multi-armed bandits and reinforcement learning, privacy-preserving machine learning, federated learning and distributed/decentralized learning, and machine learning applications in wireless communications. She has developed innovative approaches that bridge theoretical foundations with practical wireless networking applications, particularly in the areas of timely data transmission and resource optimization. Her recent publications demonstrate a strong trend toward integrating large language models with wireless communication systems, developing privacy-preserving federated learning techniques, and advancing theoretical understanding of reinforcement learning algorithms. Her work consistently addresses fundamental challenges in information theory while developing practical solutions for next-generation wireless networks. NSF CAREER award 2015 WICE Early Achievement Award 2020 IEEE TCCN Exemplary Editor Award 2024 N2Women: Stars in Computer Networking and Communications 2020 Dr. Yang has advised numerous PhD students who have gone on to successful careers in academia and industry. Her research is supported by multiple NSF grants including the CAREER award, as well as collaborations with Intel and the Department of Energy. She leads projects focused on when next-generation wireless networks meet machine learning, timely computing and learning over communication networks, and distributed differentially private data synthesis. Her research group at UVA focuses on developing theoretical foundations and practical algorithms for machine learning in wireless networks, with particular emphasis on privacy-preserving techniques, reinforcement learning applications, and efficient transformer implementations for communication systems.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۱۲ مورد دیگر

Ahmet Cüneyd Tantuğ is an Associate Professor in the Department of Artificial Intelligence and Data Engineering at the Faculty of Computer and Informatics, Istanbul Technical University (ITU). He has been a core faculty member since 2007 and is among the founders of the ITU Natural Language Processing Group. He has held key administrative roles, including Vice Dean (2011–2015) and Head of IT Department at ITU (2012–2020). BSc, MSc, PhD: Istanbul Technical University, Computer Engineering Guest Researcher: University of Copenhagen, Centre for Language Technology (2006–2007) Dr. Tantuğ’s research spans artificial intelligence, natural language processing, machine learning, and deep learning, with a focus on Turkish and other agglutinative languages. His work includes named entity recognition, dependency parsing, machine translation, word sense disambiguation, and text normalization. He has developed linguistic resources for Turkish and low-resource languages such as Amharic, and has contributed to financial AI and temporal expression extraction. His recent publications highlight advancements in Turkish NLP, including optimal vocabulary sizing, tokenization granularity for LLMs, and transformer-based models for named entity recognition. He has led multiple research projects funded by TÜBİTAK, the European Union, and the Ministry of Development. Scientific awards include: Bedri Karafakioğlu Special Award (2000) Siemens Excellence Award (2007) TeknoGirişim Sermaye Desteği Ödülü (2010) He has supervised numerous master’s and PhD students, with theses on topics such as dependency parsing, named entity recognition, and text normalization. He has also served as a consultant for private sector projects in banking, software, and telecommunications, and as a referee for TÜBİTAK, TEYDEB, and the Ministry of Industry and Technology. Dr. Tantuğ leads and participates in active research projects including Turkish text normalization from user-generated content and improving dependency parsing with augmented features. He is a founding member of the ITU Natural Language Processing Group, which continues to be a central hub for NLP research in Turkey.