Find Academic Supervisors

Evan GolubView profile

Lecturer

• Human Computer Interaction
• Educational Technology
• Ubiquitous Computing
• +3 more

Evan Golub is a Principal Lecturer and Researcher in the Department of Computer Science at the University of Maryland, and Assistant Director of the Human-Computer Interaction Lab (HCIL). He holds a Ph.D. in Computer Science from the University of Maryland (1999), an M.S. (1995), and a B.S. from Brooklyn College, CUNY (1991). His research focuses on Human-Computer Interaction (HCI), creativity support tools, educational technologies, and intergenerational design. He explores how technology can empower users of varying skill levels, particularly children and non-majors. His work emphasizes student involvement, integrating graduate and undergraduate collaboration into research and education. Key contributions include co-authoring Nothin' But Net: Computers, The Internet, Research & You (2001) and developing tools like Hit the Target , which visualizes crowdsourcing challenges. He has also authored a guidebook for TurningPoint clicker systems. Notable awards include a 2004 first runner-up Best Paper Award at the Consortium for Computing Sciences in Colleges. He actively teaches courses in computer science education and has contributed to curricular development across the university. Outside academia, Golub is an avid photographer and photojournalist, blending technical and creative pursuits. His work often bridges technology and societal impact, emphasizing ethical considerations in educational and home technologies.

Plinio MoritaView profile

Associate Professor

• Remote Patient Monitoring
• IoT in Healthcare
• mHealth Technology
• +7 more

Plinio Morita is an Associate Professor at the University of Waterloo's School of Public Health Sciences, with cross-appointments in Systems Design Engineering (University of Waterloo) and the Institute of Health Policy, Management and Evaluation (University of Toronto). He holds positions as a Research Scientist at the Centre for Global eHealth Innovation and Techna Institute (University Health Network). His research focuses on leveraging IoT, mHealth, and AI-driven technologies to improve healthcare delivery through remote patient monitoring, telehealth, and aging-in-place solutions. Morita directs the Ubiquitous Health Technology Lab (UbiLab), which develops systems that integrate data from wearable and ambient sensors to enhance population health surveillance and precision medicine. He emphasizes ethical design and equitability in technology deployment for vulnerable populations. Education: BEng in Electrical Engineering, University of Campinas, Brazil MSc in Biomedical Engineering, University of Campinas, Brazil PhD in Systems Design Engineering, University of Waterloo Postdoctoral Fellowship in Healthcare Human Factors, Techna Institute Research Interests: Population-level health surveillance via IoT Non-invasive monitoring systems (e.g., radar-based gait analysis) AI applications in infodemic management and clinical inquiry Ethics of smart health technologies and data governance His work bridges engineering, public health, and human factors to create scalable, user-centered solutions for chronic disease management and aging care. Professional Contributions: Editor for Journal of Medical Internet Research (JMIH and JMIR mHealth/uHealth) Member of IEC/SCC SyC Active Assisted Living Standards Council Professional Engineer (PEO Ontario) Lab & Teams: The Ubiquitous Health Technology (UbiLab) collaborates across disciplines to advance smart health ecosystems, with recent projects focusing on radar-based in-home monitoring and misinformation detection systems.

• Mobile Computing
• Distributed Systems
• Decentralized Applications
• +4 more

Dr. Dimitris Chatzopoulos is an Assistant Professor (Ad Astra Fellow) at the School of Computer Science, University College Dublin. He holds a PhD from The Hong Kong University of Science and Technology and academic qualifications in Computer Engineering from the University of Thessaly, Greece. His research focuses on privacy-preserving systems, AI-driven decentralized applications, mobile computing, blockchain technology, and combating fake news. Education: PhD in Computer Science and Engineering, The Hong Kong University of Science and Technology (2013–2018) MSc in Computer Engineering and Communications, University of Thessaly, Greece Professional Diploma in University Teaching & Learning, University College Dublin Research Interests: Mobile and distributed systems Decentralized AI and blockchain applications Privacy-enhancing technologies Extended reality (XR) interfaces Metaverse infrastructure Awards & Recognition: Heidelberg Laureate Forum Participant (2017) Grants & Projects: "AI-enabled decentralized sensing for mobile and distributed systems" (2023–2026) "DIGITISE: Cross-sector services for societal empowerment" (2024–2027) Ad Astra Fellowship (2020–2027) Teaching & Supervision: Module coordinator for courses such as Blockchain & Decentralisation, Cloud Computing, and Python OOP PhD thesis supervisor

James J.S. NortonView profile

Adjunct Professor

• Brain-Computer Interfaces
• Neurotechnology
• Steady-State Visual Evoked Potentials
• +3 more

James J.S. Norton is an Adjunct Professor in the Department of Electrical & Computer Engineering at the University at Albany, with concurrent roles as a Research Scientist at the National Center for Adaptive Neurotechnologies (Stratton VA Medical Center). His research focuses on developing innovative neurotechnologies including brain-computer interfaces (BCIs), spinal reflex conditioning systems, and epidermal electronic devices for medical applications. Education includes a Ph.D. in Neuroscience (University of Illinois, 2017), M.S. in Electrical and Computer Engineering (University of Illinois, 2019), and B.S. in Psychology (University of Florida, 2010). Research interests span BCI systems using SSVEP paradigms Microfluidic devices for cancer research Spinal reflex operant conditioning Wearable neurotechnology Neural signal processing algorithms with applications in rehabilitation medicine and assistive technologies. Publication analysis reveals a strong focus on translational neuroengineering, with recent work emphasizing: 1) Optimization of BCI classification methods, 2) Integration of flexible electronics in medical devices, 3) Development of new spinal reflex conditioning protocols, and 4) Applications of machine learning in neural signal processing. Awards and recognitions include: Best Paper Award at IEEE Ubiquitous Computing Conference (2018) National Science Foundation Integrative Graduate Education Fellowship (2012-2014) Web design recognition from President Obama for federal best practices (2011) Mentoring activities include advising 15+ graduate students and 50+ undergraduate researchers on projects ranging from microfluidic device development to neural signal processing algorithms. Secured funding from NSF, VA Medical Center, and University of Illinois program grants for research infrastructure development. Directs the Neurotechnology Research Laboratory at Albany Stratton VA Medical Center, focusing on adaptive neurotechnologies for rehabilitation. Collaborates with multi-institutional teams including UIUC, Wadsworth Center, and University of Florida on BCI development and applications.

Jesús FontechaView profile

Professor

• Ubiquitous Computing
• Smart Health
• mHealth
• +7 more

Dr. Jesús Fontecha is a Professor at the University of Castilla-La Mancha (UCLM), holding a position in the Department of Technologies & Information Systems. He serves as Secretary of the Department and is a researcher in the Modelling Ambient Intelligence Research Group (MAmI) and the Technological Institute of Information Systems (ITSI). His academic journey includes a Ph.D. awarded by UCLM in 2014. His research focuses on Ubiquitous Computing, Smart Health, mHealth, Context Awareness, Frailty Analysis, Gait Analysis, and Data Visualization . He has contributed over 18 JCR-indexed publications and sits on the editorial boards of multiple journals. Recent projects emphasize Healthcare collaborations with academic and corporate partners. Labs/Teams: MAmI Research Group and ITSI Institute. Contact: Email , Paseo de la Universidad 4, Ciudad Real, Spain.

Iván GonzálezView profile

Senior Lecturer

• Assistive Technologies
• Quantitative Gait Analysis
• Frailty Assessment
• +8 more

Dr. Iván González is a Senior Lecturer at the University of Castilla-La Mancha (UCLM), affiliated with the Faculty of Social Sciences and Information Technologies. He holds a M.Sc. and Ph.D. in Advanced Computer Technologies from UCLM. As a member of the MAmI Research Group, his work focuses on Assistive Technologies, Smart Health, and IoT-based solutions for healthcare monitoring. He has authored 16 JCR articles and supervised 2 PhD theses with 4 ongoing. Education: M.Sc. in Advanced Computer Technologies, UCLM Ph.D. in Advanced Computer Technologies, UCLM His research interests emphasize Quantitative Gait Analysis, Frailty assessment, and Mild Cognitive Impairment screening using wearable sensors and mobile technologies. Recent projects include the EU-funded TAICare initiative (2021-2023) and Just Move! (2022), focusing on movement analysis and cognitive health monitoring. Key Contributions: - Developed a 3D motion capture system for gait automation - Created emotion recognition algorithms using gait patterns - Designed energy-efficient wearable data storage systems - Pioneered conversational agents for IADL monitoring Academic Service: 2nd Academic Year Coordinator (2020, 2024–present) Computer Engineering Degree Coordinator (2020–2024) Lab Affiliation: MAmI Research Group (specializing in Ambient Intelligence and IoT solutions).

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +5 more

Wajahat Ali Khan is an Associate Professor in Artificial Intelligence at the University of Derby's College of Science and Engineering. His research focuses on AI-driven solutions for healthcare informatics, cybersecurity, and data integration. He leads interdisciplinary projects involving knowledge graphs, semantic web technologies, and clinical decision support systems. Research interests include applying machine learning to healthcare challenges such as disease subtyping, health data interoperability, and personalized medicine. He also explores cybersecurity in network systems and SDN environments. Key contributions include platforms like the Ubiquitous Health Profile (UHPr) for health data interoperability and the Intelligent Medical Platform for dialogue-based healthcare services. His publications span topics from anti-DDoS models to sentiment analysis for depression detection. Collaborations with institutions like Sungkyunkwan University (South Korea) highlight global impact. Khan’s work emphasizes bridging semantic gaps in healthcare systems through adaptive mediation frameworks and data-driven knowledge acquisition methods.

• Cybersecurity
• Reliability Engineering
• Intelligent Systems
• +3 more

Valeriu Ionut DIMIDOV is a Doctoral researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the Ubiquitous and Intelligent Systems department. His affiliation includes the Luxembourg Belval Campus, located at 29 boulevard JF Kennedy, L-1855 Luxembourg. His research focuses on advanced security technologies, reliable system architectures, and intelligent computing solutions. Research interests are centered around cybersecurity, trustworthy systems design, and the integration of intelligent algorithms into secure infrastructures. His work likely addresses challenges in modern ubiquitous computing environments, emphasizing reliability and security across diverse applications. No specific scientific awards or grants are explicitly mentioned in the provided text. He can be contacted via valeriu.dimidov@uni.lu for academic collaboration inquiries.

Jamie A WardView profile

Professor

• Wearable Computing
• Social Neuroscience
• Theatre and Performance Studies
• +5 more

Professor Jamie A Ward is Head of the School of Computing at Goldsmiths, University of London, and holds a Professorship in Computer Science. His research bridges wearable computing, social neuroscience, and theatre studies, focusing on understanding social interaction through body-worn sensors. He earned a PhD from ETH Zurich (2006) and a joint BEng in Computer Science/Electrical Engineering from the University of Edinburgh (2000), alongside a National Certificate in Professional Acting (2011). His work combines interdisciplinary methods such as: Using motion capture and physiological sensors to study autism and live performance Developing open-source wearable hardware like the Synchronisation Wand Collaborations with UCL Institute of Cognitive Neuroscience, Keio University, and DFKI Current projects include the 5-year ERC-funded Neurolive (live performance neuroscience) and SocSensors (wearable support for autistic children). Grants & Awards: ERC Grants (Neurolive/SocSensors) Marie Curie Fellowship (2006-2010) General Chair: Augmented Humans 2023 Key contributions include: Real-time physiology integration into music performances Sensor systems for measuring audience-actor synchrony Designing wearable tech for autism research He leads the Computing department and maintains visiting roles at UCL and Keio University.

• Extended Reality (XR)
• Human-Computer Interaction (HCI)
• Privacy and Security
• +3 more

Ass.-Prof. Dr. Pascal Knierim is an Assistant Professor at the Department of Computer Science, University of Innsbruck. He leads the Interactive Graphics and Simulation Group , focusing on Extended Reality (XR), Human-Computer Interaction (HCI), and privacy in digital environments. His research explores the societal impact of emerging technologies, including thermal imaging, drones, and AI integration with XR. Key areas of investigation include user perception in content blocking (e.g., 'Ad-Blocked Reality'), social behavior in VR (e.g., 'Navigating the Virtual Gaze'), and ethical design of mixed reality systems. His work bridges theoretical research with practical applications, such as privacy-aware smart home interfaces ('PriKey') and biometric identification via thermal imaging ('HotFoot'). Knierim’s publications often highlight trends in XR’s ethical implications, such as dark patterns in MR, and the intersection of AI with immersive technologies. His lab emphasizes collaboration, evidenced by contributions to frameworks like 'Lenssembly' for AR-based assembly instructions. His office hours are Monday to Friday, 09:00–13:00, and he is located at ICT 3N08, Technikerstraße 21a, Innsbruck.

• Avionics Communications Networks
• Heterogeneous Wireless Networks
• Software-Defined Networks
• +4 more

Dr. Muhammad Ali is a Post-Doctoral Research Staff at the Future Ubiquitous Networks Lab, within the School of Computer Science, Artificial Intelligence & Engineering at the University of Bradford, UK . His academic journey includes a BSc in Computer Science (2006, Comsats University Islamabad), MSc (2007), and PhD (2013) in Mobile & Satellite Communications from the University of Bradford. He has held roles as a Research Assistant at the Future Ubiquitous Networks Lab (2011–2015), Lecturer in Electrical Engineering and Computer Science at the University of Bolton (2016), and Lead Software Developer at Direct2Success (2016–2018). His research focuses on avionics communications networks , software-defined networks , artificial intelligence , and embedded systems . He has contributed to over 33 publications, including peer-reviewed journals and conference papers across interdisciplinary fields such as medical research, materials engineering, and computer science. His work is supported by EU, UK Innovation, and industrial grants. Ali is affiliated with the Future Ubiquitous Networks Lab , where he explores cutting-edge projects in network security, heterogeneous wireless systems, and desktop application development. Despite no listed students or awards, his technical expertise spans project leadership and multidisciplinary collaboration.

• Human-Computer Interaction
• Accessibility
• Assistive Technologies
• +12 more

Benjamin Gorman is a Lecturer at Bournemouth University's Department of Computing and Informatics, where he serves as Deputy Head of Department and Programme Leader for MSc Digital Health and MSc Internet of Things. He co-leads the Bournemouth University Computer Human Interaction (BUCHI) research group and actively contributes to accessibility-focused research in Human-Computer Interaction (HCI). PhD in Computer Science (Human-Computer Interaction) from the University of Dundee (2018) BSc (Hons) in Applied Computing from the University of Dundee (2012) His research focuses on accessibility and assistive technologies, particularly through metadata-driven media adaptation, generative AI applicability for disabled users, and inclusive FinTech design. He emphasizes collaboration with SMEs and community stakeholders through knowledge transfer partnerships. Recent publications highlight his work on emoji accessibility for visually impaired users, adaptive subtitles, and crypto technology inclusivity. These align with UN Sustainable Development Goals related to quality education, industry innovation, and good health. Exceptional Reviewer Recognition in SIGCHI venues As an educator, he leads postgraduate and undergraduate units in accessibility, user-centered web development, and ubiquitous computing. He also contributes to ACM SIGCHI as an Associate Chair and Program Committee member.

Kasthuri JayarajahView profile

Assistant Professor

• Mobile and Ubiquitous Sensing
• Deep Learning for IoT and Edge Computing
• Mobility-Driven Urban Analytics
• +3 more

Kasthuri Jayarajah is an Assistant Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). Her research focuses on mobile and ubiquitous sensing, deep learning for IoT/edge computing, mobility-driven urban analytics, and predictive cyber-physical systems. She holds a Ph.D. in Information Systems from Singapore Management University (2019), a Master of Computing from National University of Singapore (2013), and a B.S. in Electronic and Telecommunication Engineering from the University of Moratuwa (2010). Her work integrates wearable sensing technologies, machine learning, and collaborative systems to solve challenges in urban environments and human-technology interactions. Key research areas include cognitive load assessment via multimodal features, gaze-based AR systems, and lightweight collaborative intelligence frameworks for autonomous systems. She has developed frameworks like CALM for cognitive load measurement and GazeLight for AR-mediated human-robot systems. Dr. Jayarajah's research spans theoretical advancements (e.g., β-Decode for temporal artifact correction) and practical applications (e.g., AirDrop for air-ground teaming in navigation). Her contributions address edge computing constraints, adversarial IoT environments, and urban mobility analytics for smart cities. She teaches courses in mobile computing and sensor networks, bridging academic research with hands-on technical training. Leveraging interdisciplinary approaches, her work bridges computer science with urban planning, robotics, and human factors. Her lab explores innovations in wearable-assisted human-robot teams (TagTeam), lightweight vision models (ComAI), and mobility-driven predictive systems for urban operations.

Renjie HuView profile

Assistant Professor

• Machine Learning
• Data Science
• Computer Vision
• +2 more

Renjie Hu is an Assistant Professor in Information Science Technology at the University of Houston's Cullen College of Engineering, focusing on machine learning applications in computer vision and healthcare analytics. His research develops computational solutions for real-world challenges including medical diagnostics and algorithmic bias detection. Research interests include developing adaptive machine learning algorithms for imbalanced healthcare datasets, detecting biases in generative AI systems, and creating efficient visualization techniques. Current projects explore multi-view learning for enhanced computer vision tasks and clinical applications of predictive modeling. Recent publications (2019-2025) demonstrate innovation in extreme learning machines, healthcare data analysis, and human-computer interaction. Works consistently bridge theoretical algorithms with practical applications in healthcare and media analytics. Teaching responsibilities include courses on data science fundamentals and machine learning applications. Research collaborations extend to healthcare institutions for clinical data analysis projects.

• Mobile and ubiquitous user interfaces
• Interaction techniques
• Visual and ubiquitous analytics
• +5 more

Pourang Irani is an Adjunct Professor in the Department of Computer Science at the University of Manitoba's Faculty of Science. His research focuses on designing software tools for ubiquitous interaction and analytic tasks, emphasizing accessibility across devices and environments. He holds an email address associated with the University of British Columbia (UBC), suggesting potential cross-institutional collaborations. Research Interests: Mobile and ubiquitous user interfaces Visual and ubiquitous analytics Information visualization Navigation and distributed user interfaces Gaming and input device innovations While no specific grants, awards, or students are listed, his work bridges human-computer interaction and pervasive computing environments. No lab affiliations or future projects are detailed in the provided text.