جست‌وجوی استاد و پژوهشگر

Lonneke van der Plasمشاهده پروفایل

دانشیار

• Cross-lingual NLP
• Computational Semantics
• Computational Creativity
• +۴ مورد دیگر

Prof. Lonneke van der Plas is an Associate Professor in Natural Language Processing (NLP) at the University of Lugano (USI) since October 2024. She leads the Computation, Cognition & Language group at Idiap Research Institute (since 2021) and holds adjunct roles in USI's Faculty of Informatics. Previously, she was an Associate Professor at the University of Malta (2014–2020) and Junior Professor at the University of Stuttgart (SFB 732). She earned her PhD in Humanities Computing from the University of Groningen and an M.Phil in Computer Speech and Language Processing from the University of Cambridge. Her research focuses on cross-lingual NLP, computational creativity, and low-resource languages. Key projects include the NCCR Evolving Language (Swiss National Science Foundation, 2024–2028), C-LING (computational models of creativity), and SEM24 (multilingual skill extraction for HR). She has supervised multiple PhD students and postdocs, including notable advisees such as Molly Petersen and Mete Ismayilzada. Her work spans theoretical linguistics and applied NLP, with collaborations in cognitive science, finance, and healthcare. Awards include the ELSI Best Paper Award (2020) for work on societal impacts of AI ethics. Current initiatives include open PhD positions in NLP for cognitive modeling and mental health applications. Education: PhD (University of Groningen), M.Phil (University of Cambridge) Key Projects: NCCR Evolving Language, C-LING, SEM24, LT-BRIDGE Grants: SNSF, Innosuisse, Hasler Foundation Lab/Team: Computation, Cognition & Language Group at Idiap

• Artificial Intelligence
• Cognitive Neuroscience
• Robotics
• +۳ مورد دیگر

Prof. W.F.G. Haselager is a Professor of Artificial Intelligence at Radboud University Nijmegen, affiliated with the Donders Institute for Brain, Cognition and Behaviour and the Donders Centre for Cognition. He holds dual expertise in philosophy, psychology, and AI, focusing on societal implications of emerging technologies. His research integrates empirical methods (e.g., robotics, computational modeling) with philosophical inquiry into agency, responsibility, and human self-understanding. Education: MSc degrees in Philosophy and Psychology, PhD (1995) from Vrije Universiteit Amsterdam. Teaching responsibilities include bachelor/master programs in AI and Cognitive Neuroscience. Active in public engagement through lectures/workshops on AI ethics, neurotechnology, and free will. Key research themes include neuroethics, AI equity, and brain-computer interfacing. Current projects include the ELSA Lab (AI for Health Equity) and 'Healthy Data' initiatives addressing algorithmic bias and medical AI oversight. He advises Zander Labs on neurotechnology ethics and co-leads multi-institutional grants exploring conversational AI and neurodiverse education. Media appearances include Dutch TV/NOS coverage of brain implants and podcasts on AI sentience. Ancillary activities include the 'Pim Haselager Lectures' series and advisory roles in neurotechnology ethics.

• Event Cognition
• Human-Robot Interaction
• Visual Working Memory
• +۴ مورد دیگر

Frank Papenmeier is a Professor in the Department of Psychology at the University of Tübingen, within the Faculty of Science. His research focuses on event cognition, human-robot interaction, visual working memory, and visual attention. He coordinates the 'Coordination Cognitive Psychology and Research Methods' research group. His work explores how people perceive and interact with dynamic environments, including studies on event segmentation, cognitive offloading, and aesthetic judgments. He has contributed to over 100 peer-reviewed articles, with recent work addressing topics like the impact of framing on art perception and the role of AI in education. Papenmeier's research integrates experimental methods with interdisciplinary approaches, including collaborations on teleoperation systems and AI-based tutoring. He has presented at major conferences such as the European Society for Cognitive Psychology and the Psychonomic Society. His lab emphasizes methodological rigor, evidenced by contributions to replication databases and open science initiatives. Education: Not explicitly stated in the text, but his titles include Dr. rer. nat. (Doctor of Natural Sciences) and Diplom-Psychologe (Psychology Diploma). Research Interests: His primary areas include event cognition, human-robot interaction (e.g., helping behavior toward robots), visual working memory (e.g., spatial configuration processing), and cognitive offloading (e.g., impact on memory and performance). He also investigates aesthetic judgments and narrative comprehension through eye-tracking and experimental paradigms. Articles Trends: Recent work addresses applied topics like cookie consent interfaces, AI in education (e.g., R programming tutors), and perceptual effects in 3D cinema. His studies often bridge cognitive theory with real-world applications, such as usability design and social robotics. Labs/Teams: Leads the research group 'Coordination Cognitive Psychology and Research Methods' at the University of Tübingen. Collaborates with interdisciplinary teams on projects involving robotics, AI, and human-computer interaction.

Salvatore T. Marchمشاهده پروفایل

استاد

• Business Intelligence
• Information Systems
• Forecasting
• +۵ مورد دیگر

Salvatore T. March is a Professor specializing in Information Systems, Business Intelligence, and Design Science. He holds leadership roles as Editor-in-Chief of ACM Computing Surveys and has served on editorial boards for prestigious journals like MIS Quarterly. His research focuses on conceptual modeling, database design, and process theory in project management. March has organized major conferences such as the International Conference on Conceptual Modeling and contributed to advancing methodologies in distributed database systems. Education: Ph.D., Operations Research, Cornell University, 1978 M.S., Operations Research, Cornell University, 1975 B.S., Industrial Engineering & Operations Research, Cornell University, 1972 Research Interests: March’s work emphasizes the intersection of theoretical frameworks and practical systems design. Key areas include: Design Science Methodology Conceptual Modeling for Active Information Systems Process Theory in Project Management Ontology Engineering for Semantic Technologies Temporal Dynamics in Business Systems His contributions bridge academic rigor and real-world IT applications, particularly in manufacturing and service industries. Publications & Impact: With over 150 publications, March’s work spans foundational topics like distributed database design to modern challenges in predictive maintenance and digital surveillance ethics. His recent focus includes meta-theoretical debates in information systems research. Grants & Labs: While specific grants are not listed, his leadership roles indicate sustained funding in systems research. Active involvement in editorial and conference committees highlights his role in shaping the discipline’s future directions.

Hedayat Zarkoobمشاهده پروفایل

پژوهشگر

• AI in Education
• Educational Technology
• Machine Learning Applications
• +۳ مورد دیگر

Hedayat Zarkoob is a Researcher in the Department of Computer Science at the University of British Columbia (UBC), where he completed his PhD under Prof. Kevin Leyton-Brown. His work focuses on AI applications in education, particularly in peer grading systems, active learning, and large-scale classroom engagement. He is actively involved in teaching within UBC's Master of Data Science (MDS) program and the Computer Science department, leading courses on privacy, algorithms, communication, and societal impacts of technology. Education: PhD in Computer Science, UBC (supervised by Kevin Leyton-Brown) MSc in Computer Science, Simon Fraser University (supervised by Andrei Bulatov) Research Interests: Zarkoob's research bridges AI and education, with emphasis on scalable assessment tools (e.g., Mechanical TA 2), classroom engagement platforms (Agora), and AI-driven conference review systems. His work combines algorithm design, educational technology, and human-AI collaboration. Recent Projects: Agora, an open-source tool for student participation in large courses; Mechanical TA 2, a peer-grading system with algorithmic support; and AAAI 2021 workflow innovations. Teaching Roles: Upcoming courses include DSCI 541, 553, 542, 512, and CPSC 430. He has co-taught CPSC 430 (Computers and Society) since 2023.

• AI & Innovation
• Digital Transformation
• Fintech
• +۵ مورد دیگر

David Shrier is a Professor at Imperial College Business School, specializing in AI & Innovation. He co-directs the Trusted AI Alliance and serves as interim Academic Director of the Centre for Digital Transformation. His work bridges academia and industry, focusing on digital transformation, fintech, and ethical AI. He holds visiting roles at MIT School of Engineering and has pioneered educational innovations, including creating highly successful online courses that generated over $1 billion in academic revenue. Founder of Trusted AI Alliance and co-developer of the Trust::Data Initiative. Interim Academic Director, Imperial's Centre for Digital Transformation. Visiting Scholar at MIT School of Engineering, collaborating on commercialization models. His research interests include AI governance, fintech innovation, cybersecurity, and data privacy. He has advised governments and organizations globally, including the European Parliament and Commonwealth Secretariat. His books, such as Global Fintech (2022) and Basic AI (2024), explore technology's societal impact. He chairs startups like Orbu.AI and serves on NASDAQ-listed GRIID's board. Recipient of the 2022 Choice Award for Global Fintech . Launched initiatives such as the Oxford Cyber Security for Business Leaders program and the UN Data Academy.

• Traditional Chinese Medicine (TCM)
• Data Mining
• Medical Informatics
• +۴ مورد دیگر

Associate Professor Josiah Poon is affiliated with the School of Computer Science at the University of Sydney. His research focuses on applying data mining and IT techniques to Traditional Chinese Medicine (TCM), particularly analyzing herbal combinations for effective treatments. He collaborates with institutions in China to improve TCM evidence and has contributed to clinical data analysis, medical informatics, and multimodal AI systems. Teaching includes courses such as INFO1003 (Foundations of IT) and INFO9003 (IT for Health Professionals). Current research students are Rina CABRAL (Multimodality Representation), Yan LI (Long Document Comprehension), and Xiaobin LU (Financial Decisions). Research highlights include developing algorithms to quantify TCM efficacy, analyzing complementarity in herbal combinations, and applying machine learning to healthcare data. Notable projects include a randomized controlled trial on pneumococcal vaccination (2021) and a Google-funded multimodal health detection system (2020). Key areas of expertise span TCM informatics, medical data analytics, and AI-driven healthcare solutions. His work bridges Eastern/Western medicine through computational methods, emphasizing evidence-based practices in TCM.

• Machine Learning
• Artificial Intelligence
• Computer Science
• +۳ مورد دیگر

Prof. Felix Bießmann holds a professorship in Computer Science and Media at Berlin University of Applied Sciences' Department VI. His research focuses on machine learning applications in diverse fields including healthcare, urban planning, environmental science, and robotics through his Cognitive Algorithms Lab. He teaches courses such as Machine Learning, Deep Learning, and Data Science Workflows, alongside roles at TU Berlin and Korea University. Education: PhD (Dr. rer. nat.) in Natural Sciences Research interests span machine learning theory and practical implementations across domains like computer vision, generative AI, and sensor data analysis. His work addresses challenges in automated systems, healthcare monitoring, and sustainable technologies. Recent student theses explore topics like license plate recognition, adaptive game soundtracks, and bird song detection using TinyML. Collaborations include projects with the Charité Berlin and Robert-Koch Institute. Lab: Cognitive Algorithms Lab (developing machine learning methods/applications) Contact: felix.biessmann@bht-berlin.de | Office D138, Berlin University of Applied Sciences.

• Microchannel Engineering
• Proton Exchange Membrane Fuel Cell
• Two-phase Flow
• +۷ مورد دیگر

Eon Soo Lee is an Associate Professor in the Department of Mechanical and Industrial Engineering at the New Jersey Institute of Technology (NJIT). His primary research focuses on advanced materials engineering, biomedical microfluidics, and assistive technologies for individuals with disabilities. He has led federally funded projects including 'I-Corps: Multiplex Diagnostic Assay Using Interdigitated Nano-Sensing Technology' (NSF, 2023-2025) and 'Innovative Nano Catalysts for Automobile and Fuel Cell Applications' (NSF, 2018). Research Interests: Lee's work spans interdisciplinary areas including: Development of N-doped graphene/MOF composites for energy applications Microfluidic systems for blood plasma separation and antigen detection Design of accessible technologies for visually impaired users, including VR audio descriptions and remote sighted assistance systems Grants and Projects (select): National Science Foundation (2023): $500K for multiplex diagnostic assays National Science Foundation (2018): $300K for nano-catalysts in fuel cells Multiyear collaborations with industry partners on biosensor integration Innovation Highlights: Developed AIGuide: AR hand-guidance system for visual impairments Pioneered omnidirectional audio descriptions for VR music performances Published extensively in Carbon , Biomicrofluidics , and ACM/IEEE accessibility venues

• Machine Learning
• Feature Selection
• Internet of Things
• +۵ مورد دیگر

Liang Hu is a Professor at De Montfort University's School of Computer Science and Informatics, with extensive research in machine learning, feature selection, and Internet of Things applications. His work bridges theoretical advancements in multi-label learning with practical implementations in IoT security and edge computing. PhD from Jilin University (1999) Active researcher with 178 publications (2005-2025) Key collaborator with Hongtu Li, Feng Wang, and Wanfu Gao His research focuses on multi-label feature selection , graph neural networks , and IoT security , developing novel frameworks for heterogeneous information networks, privacy-preserving federated learning, and threat detection in smart environments. His recent work integrates large language models with trigger-action programming systems. Analysis of his 15 most recent publications reveals strong emphasis on multi-view learning (40% of papers), IoT security applications (33%), and graph-based representation learning (27%), demonstrating consistent innovation in handling complex label correlations and heterogeneous data structures. His scientific contributions include novel feature selection methodologies that balance personalized and shared features while minimizing redundancy across multiple views and labels. Liang Hu leads research in edge intelligence and secure IoT programming, with recent projects developing conflict detection frameworks (CCDF-TAP) and privacy-preserving federated graph learning for smart home ecosystems. His work bridges theoretical machine learning with practical cybersecurity implementations.

• Pervasive Sensing
• Tiny Machine Learning (TinyML)
• Edge AI
• +۷ مورد دیگر

Prof. Eiman Kanjo is a Professor of Pervasive Sensing & TinyML and Head of the Smart Sensing Lab at Nottingham Trent University. She leads the Smart Nottingham and Smart Campus initiatives, focusing on impactful applications of mobile sensing, wearable tech, and edge AI. Her work bridges academia, industry, and community, emphasizing privacy-preserving AI for mental health, environmental monitoring, and social prescribing. Education: PhD in Computer Science (2005), University of Abertay Dundee. Formerly a Research Associate at the University of Cambridge and researcher at the University of Nottingham’s Mixed Reality Lab. Collaborates with organizations like the tinyML Foundation, Health Data Research UK (HDRUK), and the Alan Turing Institute. Research Interests : Pervasive computing, TinyML, Edge AI, wearable devices, environmental sensing, mental health technologies, and community-driven solutions for urban wellbeing. She pioneered early mobile sensing systems like NoiseSPY (2010) and MobSens (2009). Key Projects : 5G Connected Forest (£10m DCMS grant) : Smart environmental monitoring in Sherwood Forest. TagWithMe : AI-driven proximity-based games for community wellbeing. EPSRC Green+ Network : Tech for healthier environments. Awards & Recognition : Top 50 Women in Engineering (2023). Outstanding Educator of the Year Award (EDGE AI Foundation, 2023). 2021 Vice-Chancellor’s Outstanding Research Team Award (Smart Sensing Lab). Grants & Collaborations : Over £10m in funding from EPSRC, InnovateUK, MOD, and DEFRA. Partners include Nottingham City Council, tinyML Foundation, Health Data Research UK, and industry stakeholders. Labs & Initiatives : Leads the Smart Sensing Lab , developing technologies for Green Social Prescribing at Rufford Country Park and Highbury Mental Health Hospital.

Ashish Guptaمشاهده پروفایل

استاد

• Deep Learning
• Machine Learning
• AI
• +۲ مورد دیگر

Ashish Gupta holds the Globe Life Professor title in the Department of Business Analytics & Information Systems at Auburn University and serves as an Adjunct Professor in the Department of Computer Science and Software Engineering. His research focuses on Deep Learning, Machine Learning, AI, Natural Language Processing, and Social Network Analytics. Education: Ph.D. in Management Science and Information Systems from Oklahoma State University. Research trends in his articles emphasize AI-driven solutions for misinformation detection, healthcare analytics, smart grids, and educational pedagogy. Notable themes include real-time fake news detection, pandemic impact studies, and predictive modeling in healthcare and agriculture. No scientific awards or grants are explicitly listed. He advises no formally listed students. His work integrates computational methods with societal challenges, particularly in healthcare, education, and agriculture. Collaborations span interdisciplinary domains, though specific lab affiliations are not mentioned.

Xiaonan Guoمشاهده پروفایل

استادیار

• Cyber-physical Systems Security
• Mobile Device Security
• IoT and Wearable Technologies
• +۳ مورد دیگر

Xiaonan Guo is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University. His research focuses on security and privacy in cyber-physical systems, mobile device security, IoT, mobile healthcare, and machine learning applications in mobile computing. He holds a PhD in Computer Science from the Hong Kong University of Science and Technology. His work spans innovative applications of mmWave technology for authentication, health monitoring, and activity recognition, alongside contributions to privacy-preserving systems and mobile deep learning optimization. Recent research emphasizes contactless human concentration monitoring, secure mobile DNN execution, and universal adversarial attacks against mmWave-based systems. Xiaonan’s publications reflect a strong focus on mobile and IoT-driven healthcare solutions, wearable device security, and cross-technology localization. His articles often bridge theoretical advancements with real-world applications in smart healthcare systems and pervasive computing environments.

• Human-Computer Interaction (HCI)
• Virtual/Augmented Reality (VR/AR)
• User Experience (UX)
• +۶ مورد دیگر

Vassilis Charisis is a Professor of Creative Technologies and Associate Dean of Research and Innovation at the School of Arts and Creative Industries, Edinburgh Napier University . He holds a PhD and MPhil in Human-Computer Interaction (HCI) and VR/AR from the University of Glasgow and serves as a Visiting Professor at the University of Nicosia (Cyprus) and University of West Attica (Greece). Former roles include Professor of HCI and VR/AR at Glasgow Caledonian University Founder and Director of VRS Lab and VRDS Lab Director of Visual, Affective and Pervasive Systems (VAPS) research group His research spans Human-Computer Interaction , Virtual/Augmented Reality , User Experience (UX) , Artificial Intelligence , and Medical Simulation . With over £12.5M in research funding and 100+ publications, he focuses on: Automotive Engineering : AR/VR interfaces, collision avoidance systems Healthcare Applications : Dialysis training, telemedicine Consumer Electronics : UX optimization, gesture recognition Recent publications highlight trends in XR for geriatric rehabilitation , AI-driven AR HUD systems , and IoT security frameworks . His work integrates AI, immersive environments , and user-centered design across domains. Scientific Awards International awards for automotive design (FIAT, Opel) Professional memberships: MIET, FBCS, FRSA, FDSRI, SFHEA He advises on PhD supervision (e.g., Kweku Bram Larbi) and contributes to advisory committees like the Scottish Arts and Humanities Alliance . His projects include: VR Dialysis Training Systems (Kidney Research UK, NHS) noPILLLS in the Water (EU FP7, £7.5M) Collision Avoidance AR Interfaces for emergency vehicles

• Smart and Sustainable Grids
• Intelligent Systems
• Bioengineering
• +۴ مورد دیگر

Dr. Gregorio López López is an Associate Professor at the School of Engineering (ICAI) of Universidad Pontificia Comillas and a member of the Institute for Research in Technology (IIT). His research focuses on Smart and Sustainable Grids, Intelligent Systems, and Bioengineering. He holds a PhD in Telecommunications Engineering from Universidad Carlos III de Madrid (2014), recognized with the Extraordinary PhD Dissertation Award and CISCO-COIT Prize. Education: PhD in Telecommunications Engineering (UC3M, 2014), MSc and BSc in similar fields. His research interests include M2M communications optimization, IoT cybersecurity, and smart grid technologies. He has led over 17 national/EU projects including eFORT and InteGrid. His work spans 64 conference papers and 31 journal publications. Key awards: CISCO-COIT Prize (2015), Extraordinary PhD Award (2015), Deloitte Prize (2021), Lyntia Prize (2022). He advises 4 PhD students, teaches telecommunications subjects, and contributes to cybersecurity initiatives like the RAYUELA project. His lab focuses on integrating cybersecurity with smart grid systems and youth tech safety.