جست‌وجوی استاد و پژوهشگر

Gelareh Mohammadiمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Artificial Intelligence (AI)
• Computational Psychology
• +۵ مورد دیگر

Associate Professor Gelareh Mohammadi leads the Human-Centered Computing Research Group and serves as Associate Head of School (Engagement) at UNSW Sydney's School of Computer Science and Engineering. Her research focuses on accessible technologies that integrate human-computer interaction, AI, and computational psychology to enhance user-centered systems. She specializes in emotion recognition, virtual reality applications, and AI-driven design solutions. Education details are not explicitly provided in the text, but her extensive publication record indicates deep expertise in interdisciplinary fields. Her work bridges technical innovation with psychological principles, addressing challenges in healthcare, education, and interactive systems. Research interests include: Emotion analysis through VR and physiological signals Generative AI for UI/UX and creative applications Human-AI collaboration in design processes Cognitive load measurement in interfaces Alzheimer's disease biomarkers via data mining Her recent publications (2023–2025) highlight advancements in multimodal emotion recognition, stress detection systems, and AI-driven design tools. Notable contributions include the EmoStim database and DesignRepair framework. She has pioneered VR-based emotion elicitation studies and developed GAN models for facial expression synthesis. Current projects emphasize human-centric AI applications, with focus areas in healthcare technology, educational interfaces, and immersive gaming experiences. She collaborates on interdisciplinary initiatives involving psychology, biomedical engineering, and software engineering.

• Visual Analytics
• Information Visualization
• Computational Linguistics
• +۳ مورد دیگر

Menna El-Assady is an Assistant Professor at ETH Zurich's Department of Computer Science , leading the Interactive Visualization and Intelligence Augmentation Lab (IVIA) . She works at the intersection of data analysis, visualization, computational linguistics, and explainable AI , focusing on combining machine learning with visual analytics for text data. Current affiliations: ETH Zurich (Department of Computer Science, AI Center) Previous roles: Research Fellow at ETH AI Center, Research Associate at University of Konstanz, Doctoral Student at OntarioTech University Research Interests El-Assady's work focuses on human-AI collaboration , particularly through: Interactive systems for topic model refinement and language model explainability Visual analytics frameworks for argumentation analysis and digital humanities Explainable AI solutions for medical decision support and political deliberation Trust calibration mechanisms in generative AI and recommender systems Scientific Contributions Developed explAIner - a visual analytics framework for explainable machine learning Created LingVis - integrating computational linguistics with visual analytics Designed VALIDA and VisArgue for analyzing political debates and rhetoric Co-organized workshops: ArgVis , Vis4DH , VisLR , and VISxAI Academic Recognition Best Paper Award: Honorable Mention (IEEE Trans. on Visualization and Computer Graphics, 2018) 2024 VGTC Visualization Significant New Researcher Award

• Recommender Systems
• Federated Learning
• Augmented Reality Applications
• +۵ مورد دیگر

Dr. Saikishore Kalloori Saikishore is a Lecturer in the Department of Computer Science at ETH Zurich, specializing in areas such as Recommender Systems, Federated Learning, and Augmented Reality Applications. His research focuses on developing privacy-aware collaborative systems, improving news and advertising recommendations, and enhancing user interaction through advanced AR interfaces. His work integrates machine learning techniques with real-world applications, addressing challenges like cold-start recommendations and cross-silo data collaboration. Recent contributions explore ethical AI in news curation, AR-driven tourism experiences, and federated learning frameworks for corporate environments. Notable projects include the EB-NeRD news recommendation dataset and cross-silo federated learning architectures. His research emphasizes balancing algorithmic accuracy with user-centric design principles, particularly in sequential task guidance systems and occlusion effects in AR interfaces. Professional activities include organizing RecSys Challenges (2022-2024) focused on practical recommendation problems like fashion purchase prediction and privacy-preserving ad systems. He maintains active collaborations with industry partners to bridge academic research and real-world deployment.

• Rehabilitation Engineering
• Biomechanics
• Human-Computer Interaction
• +۶ مورد دیگر

Xianta Jiang is a research-focused academic at Simon Fraser University's School of Computing Science, specializing in rehabilitation engineering and biomedical computing. With a prolific publication record spanning from 2006 to 2025, Jiang has established expertise in force myography, prosthetic control systems, and human-computer interaction for medical applications. Jiang's research interests center on biomechanics, wearable sensor technologies, and surgical training systems. Their work bridges computer vision with rehabilitation engineering, particularly in facial image processing applications for medical contexts. Recent publications demonstrate a strong focus on diffusion models and generative AI techniques applied to medical image restoration and prosthetic control. The research trajectory shows a clear evolution from fundamental biomechanics research (early work on ankle joint power estimation and gait analysis) to more complex applications involving AI-driven prosthetic control and facial image processing. The 2023-2025 publications reveal a strategic pivot toward leveraging advanced computer vision techniques for medical applications. Jiang collaborates extensively with M. Stella Atkins, Bin Zheng, and Carlo Menon, forming a core research group at Simon Fraser University focused on biomedical computing applications. This collaborative network spans multiple publications in high-impact venues including IEEE Transactions, Sensors, and Frontiers journals.

• Speech Recognition
• Human-Computer Interaction
• Virtual Reality
• +۱۱ مورد دیگر

José Miguel Salles Dias is a researcher at the University of Lisbon, affiliated with the Instituto Superior Técnico and INESC-ID. His work spans speech recognition, human-computer interaction, virtual reality, and machine learning, with a focus on assistive technologies for the elderly, urban mobility analysis, and privacy-preserving systems. Key Research Areas: Speech recognition for elderly users, multimodal interfaces, virtual reality environments, and urban transport analytics. Notable Contributions: Development of gesture-based interaction systems, energy consumption prediction models, and speech interface tools for minority languages. His publications reflect trends in integrating machine learning with real-world applications, including health data systems, bike-sharing optimization, and immersive VR environments. While no explicit awards are listed, his collaborations with institutions like INESC-ID and participation in conferences like INTERSPEECH and Eurographics highlight his academic engagement.

• Multimodal Interaction
• Artificial Intelligence
• Human-Computer Interaction
• +۳ مورد دیگر

Hung-Hsuan Huang is an academic researcher focused on multimodal interaction, embodied conversational agents, and educational technology. His work spans topics such as virtual agent behavior, gamified learning systems, and nonverbal communication analysis. Collaborating frequently with institutions like Osaka University, he has published extensively in venues including HCI, ICMI, and IVA conferences. His research often integrates machine learning techniques with human-computer interaction challenges, particularly in educational and collaborative environments. Key research areas include: (1) Designing virtual agents for tutoring and teacher training, (2) Multimodal assessment systems using speech and body language analysis, (3) Gamification mechanisms for knowledge refinement and skill evaluation, and (4) Cross-cultural interaction frameworks for virtual guides. Recent work emphasizes applications in language proficiency assessment and teacher training simulations. Notable contributions include developing frameworks for integrating embodied conversational agents, simulating group discussion dynamics, and creating virtual classroom environments for skill evaluation. His methodologies often combine deep learning with behavioral analysis to address challenges in human-agent collaboration.

• Human-Computer Interaction
• Affective Computing
• Multimedia Systems
• +۲ مورد دیگر

Andrej Kosir is a researcher at the University of Ljubljana's Faculty of Electrical Engineering, specializing in multimedia systems and human-computer interaction. His core research examines physiological signal analysis for affective computing applications, including advertising engagement measurement and cognitive load prediction in automotive interfaces. Research Focus: His work spans multimedia ad exposure modeling, physiological computing, and recommender systems. Recent studies analyze biometric responses to advertising content and develop metrics for evaluating user engagement through physiological signals like heart rate and pupillary response. Publication Trends: Kosir's 15 most recent publications (2010-2025) demonstrate consistent focus on affective computing applications. Earlier work centered on recommender systems and affective labeling, while recent publications emphasize physiological signal processing in automotive and advertising contexts. Methodologically, his work combines machine learning with psychophysiological measurement techniques.

Mladen Vidovićمشاهده پروفایل

پژوهشگر

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

Mladen Vidović is a researcher at the Faculty of Informatics and Computing, Singidunum University. His work focuses on artificial intelligence, machine learning, and applied informatics, with a particular emphasis on synthetic dataset generation, remote rendering, and educational technology. Articles : 12 recent publications covering AI applications, semantic segmentation, and data science Research Interests : Synthetic data creation, machine learning workflows, and interactive software systems His research outputs include collaborations on tools like Autonomous Grader for educational assessment and Microraptor Gui for remote rendering monitoring. Notable projects involve leveraging Kohonen Self-Organizing Maps for anomaly detection and developing end-to-end learning approaches for stereo vision tasks. While no explicit awards or student advisories are documented in the available texts, his publications indicate active participation in academic conferences such as Sinteza and ICIST, contributing to advancements in AI and informatics.

Mohammad Nayeem Teliمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Machine Learning
• Data Science
• +۳ مورد دیگر

Mohammad Nayeem Teli is a Senior Lecturer in the Department of Computer Science at the University of Maryland, College Park. He holds a PhD and M.S. in Computer Science from Colorado State University and a B.E. in Electronics and Communications from National Institute of Technology, Srinagar. His research focuses on Computer Vision, Machine Learning, and Data Science, with notable projects in vaccine design using protein language models, memory-efficient diffusion models, assistive technology for visually impaired individuals, and robotic navigation in dynamic environments. He has taught courses such as Introduction to Machine Learning , Computer Vision , and Data Science , winning the Excellence in Teaching Award (2018-2019). His work includes collaborations with institutions like Harrisburg University and National Institute of Technology, Srinagar, where he previously served as an Assistant Professor. He is an IEEE Senior Member and has received awards like the Best Oral Presentation Award at IEMTRONICS 2021. His research spans vaccine design with protein models, medical imaging optimization, and assistive robotics. Current projects explore invertible diffusion models for 3D medical imaging and LiDAR-based navigation aids for the visually impaired. Publications highlight contributions to adversarial robustness in autonomous vehicles, face recognition challenges, and resource allocation in online gaming systems.

• Wireless Communications
• Signal Processing
• Image Steganography
• +۵ مورد دیگر

Dr. Peter Vial is a Senior Lecturer at the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong. He holds a PhD in Electrical Engineering and has over three decades of experience in academia and industry. His academic journey includes a Bachelor's (1987), Master's (1997), and PhD (2009) from the University of Wollongong. Before academia, he worked at BHP Steel (1981-1991) and transitioned into teaching roles from 1992, becoming a Lecturer in 2004 and Senior Lecturer in 2022. Research Interests: Dr. Vial’s work focuses on wireless communication systems, including MIMO, spread spectrum, and ultra-wideband (UWB) technologies. He also explores signal processing applications in medical imaging (e.g., capsule endoscopy), steganography, energy harvesting, and robotics. His research integrates machine learning and embedded systems for practical solutions in healthcare, telecommunications, and sensor networks. Teaching & Supervision: Dr. Vial teaches courses in telecommunications, digital signal processing, and electronics. He has led laboratory development in embedded systems and supervised over 15 postgraduate students, including current PhD candidates in Delay Tolerant Networks (DTN), 60GHz Ad Hoc networks, and UWB channel measurements. His supervision spans topics like AI-driven sign language recognition, steganography, and energy-efficient generator design. Grants & Funding: He led an internal grant (2008-2009) developing an immersive learning platform for microcontroller education. His research has been supported by institutional funding, with outputs published in journals like Neurocomputing , Signal Processing , and IEEE Sensors . Labs & Teams: Dr. Vial has developed engineering laboratories in embedded Internet systems, telecommunications, and digital signal processing. He collaborates with industry partners and interdisciplinary teams on projects combining hardware/software systems for healthcare, energy, and robotics.

Stacey Watsonمشاهده پروفایل

استادیار

• Usable Security
• Accessibility in Technology
• Cybersecurity Education
• +۳ مورد دیگر

Dr. Stacey Watson is an Assistant Professor in the Department of Computer Science at the University of Waterloo, part of the School of Computer Science. Her research focuses on usable security and accessibility, particularly for visually impaired and deaf communities, while also advancing cybersecurity education in computer science curricula. She holds a Ph.D. from the University of North Carolina at Charlotte (2018), an M.Sc. from Columbus State University (2013), a B.Ed. from Brock University (1999), and a B.A. from York University (1989). Her work bridges technical security solutions with human-centered design, addressing challenges such as accessible authentication methods for disabled users and improving student engagement through innovative teaching strategies. Recent research includes developing haptic authentication systems (e.g., VibroAuth) and single-input PIN solutions (OneButtonPIN) to enhance accessibility while preventing eavesdropping. She has also explored interdisciplinary cybersecurity education and the integration of embedded systems security into undergraduate courses. Watson’s publications span topics like end-of-use electronics management, non-malicious user vulnerabilities, and gamification in education. While no specific awards are listed, her contributions reflect a commitment to inclusive technology and pedagogical innovation. She is actively involved in curriculum development, emphasizing minimal-intervention strategies to enhance student preparedness and motivation.

• Human-Computer Interaction
• Computer Vision
• Accessibility Technology
• +۲ مورد دیگر

Tom Desrumeaux is a Visiting Researcher at the Centre for Robotics, Queensland University of Technology (QUT), currently engaged as a French intern collaborating with Dr. Laurianne Sitbon's research initiatives. His institutional affiliation places him within QUT's premier robotics research hub focused on real-world technological applications. His primary research centers on developing an innovative "magic mirror" system that translates spoken language into sign language in real-time, directly addressing communication barriers for the deaf and hard-of-hearing community. This work integrates Computer Vision for gesture recognition, Human-Computer Interaction principles for intuitive interfaces, and specialized Sign Language Processing algorithms. The project exemplifies QUT's commitment to Accessibility Technology through robotics, with potential applications extending to educational tools and public service interfaces. The Centre for Robotics provides the infrastructure for this research, operating within QUT's broader framework of equity-driven technological innovation as reflected in their public commitment to diversity and inclusion initiatives.

• Digital Image Processing
• Signal Processing
• Soft Computing
• +۵ مورد دیگر

Prof. Annamária Várkonyiné Kóczy is a Professor at the Department of Informatics within the Faculty of Economics and Informatics at J. Selye University. She holds a joint appointment as a professor at Óbuda University's Institute of Software Design and Software Development. Her academic journey includes: Electrical Engineering studies (Measurement and Control) at Technical University of Budapest (1975-1981) Mechanical Engineering degree (Mechanical Engineer-Teacher) from the same institution (1978-1983) PhD in Computer Science from Technical University of Budapest (1996) DSc (Doctor of Sciences) from Hungarian Academy of Sciences (2010) Habilitation from Széchenyi István University (2017) Her research spans digital signal processing, soft computing, and hybrid techniques for complex systems, with applications in medical diagnostics, intelligent control, and sustainable technologies. She leads projects in computational intelligence and has developed novel algorithms for real-time processing in resource-constrained environments. Recent publications demonstrate strong focus on AI-driven solutions: machine learning for bioacoustic analysis (beehive swarming), fuzzy logic optimizations for edge computing, medical imaging diagnostics (COVID-19 detection), and sustainable energy control systems. Her work consistently bridges theoretical models with practical implementations in healthcare, environmental monitoring, and industrial diagnostics. She has secured multiple research grants including: OTKA K 105846: Intelligent Space and robotics (2012-2017) OTKA K 78576: Intelligent techniques in signal/image processing (2009-2013) GVOP-3.3.1: Intelligent 3D modeling systems (2006-2007) EU Structural Funds projects on vehicle industry collaborations She mentors graduate researchers in applied informatics and leads international collaborations across Europe and Asia, focusing on intelligent systems development.

Alexander Pachaمشاهده پروفایل

مدرس

• Optical Music Recognition
• Deep Learning
• Music Information Retrieval
• +۳ مورد دیگر

Dr. Alexander Pacha is an External Lecturer at TU Wien, specializing in Optical Music Recognition (OMR) and deep learning applications. His work focuses on advancing OMR systems through graph neural networks, dataset development (e.g., DeepScoresV2), and music score analysis. He leads projects like DeepOMR and contributes to the Mixed Reality Lab and Virtual Meeting Room initiatives. Key research areas include music symbol detection, staff/measure segmentation, and cross-document alignment in music scores. Research interests span computer vision, artificial intelligence, and software tools for music information retrieval. His work bridges theoretical advancements with practical applications in digital libraries and music technology. Notable contributions include self-learning OMR frameworks and benchmarking tools for music object detection. Labs & Teams: Mixed Reality Lab (exploring AR/VR in music contexts), Virtual Meeting Room (collaborative digital environments).

• Visual Analytics
• Data Visualization
• Machine Learning
• +۳ مورد دیگر

Cagatay Turkay is a Professor in the Department of Computer Science at the University of Warwick, UK. Previously affiliated with City University London, his research focuses on visual analytics, data visualization, and integrating machine learning techniques into interactive systems. He has contributed to advancements in dashboard design, uncertainty quantification in AI, and healthcare applications. His work emphasizes bridging computational methods with human-centric interfaces to enhance decision-making in fields like epidemiology, cybersecurity, and finance. Key roles: Organizer of EuroVis workshops on Visual Analytics, contributor to NFDI4DataScience infrastructure projects. Research interests include: Human-Computer Interaction, Explainable AI, and FAIR data principles. His publications span journals like IEEE Transactions on Visualization and Computer Graphics and conferences such as AAAI and CHI. He has pioneered frameworks for visualizing complex data patterns, including TransforLearn for transformer models and LEVA leveraging large language models.