Syed Ali Raza is a researcher affiliated with the University of Technology, Sydney (PhD 2018), with a former affiliation at the Institute of Business Administration, Karachi. His work focuses on reinforcement learning, robotics, and human-robot interaction. Key contributions include studies on social robots' question-answering services, human feedback integration in AI systems, and optimization of robotic movements in multi-agent scenarios. He has collaborated extensively with researchers like Mary-Anne Williams and Sajjad Haider. His research spans theoretical advancements in machine learning algorithms and practical applications in robotics competitions (e.g., RoboCup). Research interests emphasize computational reinforcement learning, reward shaping techniques, and ethical design of autonomous systems. Notable projects include privacy-first approaches for social robots and hybrid methods for humanoid robot locomotion. His work bridges theoretical AI advancements with real-world robotic implementations.
Svetlana Yarosh is a Professor at the University of Minnesota , focusing on Human-Computer Interaction (HCI) , Virtual Reality (VR) , and Social Support Systems . Her research explores technology's role in Online Health Communities , Intergenerational Communication , and Substance Use Recovery , emphasizing ethical design and participatory methods. Affiliation: University of Minnesota, Minneapolis, MN, USA Research Interests: Yarosh investigates Mediated Social Touch , XR for Children , and Collaborative Technologies in health and family contexts. Her work addresses Privacy in Online Communities , Dynamic of Recovery Support , and Ethical Frameworks for emerging technologies, particularly focusing on Stigmatized Populations and Peer Support Systems . Article Trends: Recent publications highlight VR Video applications in education, AR for Remote Reading , and Ethical Considerations in children's technology use. Themes include Community-Engaged Research , Interactive Volumetric Video , and Conflict Resolution through VR perspective-taking.
Dr. Keng Leng Siau is a Lee Kong Chian Professor of Information Systems at the School of Computing and Information Systems, Singapore Management University. Holding a PhD from the University of British Columbia, his research spans human-computer interaction, information systems management, and digital transformation. His work focuses on enhancing human-machine collaboration and developing future work technologies. Research interests include cybersecurity applications in lifestyle and wellness, privacy-preserving systems, and innovative pedagogical approaches for technology-enhanced learning. His contributions bridge theoretical frameworks with practical implementations in enterprise systems.
Marinko Sarunic is an Adjunct Professor at the School of Engineering Science , Simon Fraser University . He holds a PhD in Biomedical Engineering from Duke University and has been recognized as a Michael Smith Foundation for Health Research Scholar . His research focuses on biomedical imaging , particularly optical coherence tomography (OCT) , microscopy , and low-coherence interferometry , with applications in diabetic retinopathy , Alzheimer’s disease , and age-related macular degeneration . Dr. Sarunic's work spans adaptive optics , deep learning , and sensorless OCT systems , emphasizing clinical translation and open-source software development (e.g., OCTAVA ). His Google Scholar publications highlight multimodal imaging , vascular heterogeneity analysis , and AI-driven diagnostics for retinal diseases. His contributions include the Michael Smith Foundation for Health Research Scholar award. Though not currently teaching courses, his collaborations and leadership in retinal imaging and medical device innovation are pivotal for advancing non-invasive diagnostics in neurodegenerative and diabetic conditions .
Frank Reichert is a Professor of Mobile Systems at the University of Agder (UiA), affiliated with the Department of Information and Communication Technology under the Faculty of Engineering & Science. He served as UiA's Rector (2016-2019) and Dean of Engineering & Science (2007-2015). With over 30 years in fixed/wireless communication systems, he has led national initiatives like the SFI Offshore Mechatronics Center (200 MNOK budget) and established UiA's Mechatronics Innovation Lab. His industry experience includes roles at Ericsson (1995-2005) and founding Ericsson Cyberlab Singapore (1999). Education : PhD in Electrical Engineering from RWTH Aachen University (Germany). Early career included research at the Royal Institute of Technology (Sweden) and Televerket Radio (Sweden). Research Interests : Focus on mobile communication, e-learning innovation, IoT-driven telehealth, and lifelong learning. His work bridges academia and industry, emphasizing user-centric design, rapid prototyping, and future education technologies. Projects include multi-touch collaborative learning systems, AI-assisted educational tools, and digital health twin architectures. Grants & Leadership : Managed EU projects (e.g., FP4-ACTS OnTheMove, PRO-COM) and served on steering boards for Norwegian and EU research bodies. Current roles include advisor to UiA's strategic initiatives and contributor to national bullying/harassment prevention (UHRMOT). Labs & Teams : Co-founded the Mechatronics Innovation Lab, leading projects in VR rehabilitation solutions and smart healthcare systems. Active in research groups like Multimedia and e-Learning, and ReSex (Research in Sexology).
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
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.
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. 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 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.
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.
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.
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.
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
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.
