جست‌وجوی استاد و پژوهشگر

Michael L. Riveraمشاهده پروفایل

استادیار

• Digital Fabrication
• Human-Computer Interaction
• 3D Printing
• +۶ مورد دیگر

Michael L. Rivera is an Assistant Professor at the ATLAS Institute and the Department of Computer Science at the University of Colorado Boulder. He leads the Utility Research Lab, a highly interdisciplinary group that invents and investigates digital fabrication technology, tools, and techniques with the goal of advancing science and engineering while positively impacting people, society, and the environment. Dr. Rivera completed his Ph.D. and M.S. in Human-Computer Interaction at the Human-Computer Interaction Institute of Carnegie Mellon University, where he was advised by Scott Hudson as part of the DevLab. Before Carnegie Mellon, he earned a M.S.E in Computer Graphics and Game Technology and a B.S.E in Digital Media Design from the University of Pennsylvania. He also previously worked as a software engineer at Facebook. His research spans the intersection of digital fabrication, human-computer interaction, and material science. Dr. Rivera's work focuses on developing novel fabrication techniques such as desktop biofibers spinning, electrospinning, and sustainable material processing with everyday waste products like coffee grounds. His research has significant implications for sustainable manufacturing, tangible interfaces, and accessible technology design. Analysis of his recent publications reveals a consistent focus on making digital fabrication more accessible, sustainable, and interdisciplinary. His work bridges computer science, material engineering, and design, with particular emphasis on open-source hardware development, computational design tools, and applications for social good. The research demonstrates a progression from fundamental fabrication techniques toward more applied, socially conscious applications. CRA/CCC Computing Innovation Fellowship Google - CMD-IT Dissertation Fellowship Carnegie Mellon University Sansom Endowed Presidential Fellowship Adobe Research Fellowship Honorable Mention Xerox Technical Minority Scholarship Dr. Rivera is currently recruiting PhD students to join the Utility Research Lab. His research has been supported by various fellowships and grants throughout his career, including industry partnerships with Google and Adobe. His work demonstrates strong potential for future funding in sustainable manufacturing and accessible technology. The Utility Research Lab, directed by Dr. Rivera, is a highly interdisciplinary research group focused on inventing and investigating digital fabrication technology. The lab has developed several notable projects including the Desktop Biofibers Spinning Machine (presented at CHI 2024), desktop electrospinning technology (CHI 2019), and systems for 3D printing with spent coffee grounds. The lab maintains an active GitHub presence with numerous open-source repositories related to their research.

María del Carmen Benavides Cuéllarمشاهده پروفایل

استاد

• Systems Engineering and Automation
• Cybersecurity
• IoT Network Security
• +۶ مورد دیگر

María del Carmen Benavides Cuéllar is a Professor at the Department of Electrical, Systems and Automation Engineering within the College of Industrial, Informatics and Aerospace Engineering at the University of Leon. Her research focuses on Systems Engineering and Automation, with particular emphasis on Cybersecurity, IoT Networks, Ontology-Based Knowledge Representation, and Intelligent Distributed Systems. Doctorate in Control Engineering (University of Leon, 2009) Currently leads research in Cybersecurity and IoT Her recent publications span topics from Cybersecurity in IoT 5G networks to Medical AI applications for Parkinson's disease severity analysis. She has contributed significantly to LiDAR-based navigation systems and Social Network Analysis in healthcare contexts. Key research areas include: Ontology-based knowledge representation for control engineering Distributed intelligent systems and middleware development Biomedical applications of deep learning Social media analysis using NLP techniques She has supervised multiple research projects at the intersection of Computer Science and Healthcare, with notable works in nursing management and adolescent alcohol consumption studies. Her lab SECOMUCI focuses on cybersecurity and knowledge management in cyber-physical systems.

• Acoustics
• Psychoacoustics
• Spatial Audio
• +۷ مورد دیگر

Iain McGregor is an Associate Professor at the School of Computing Engineering and the Built Environment, Edinburgh Napier University. His work bridges acoustics, psychoacoustics, and human-computer interaction to advance audio technologies in mixed reality and IoT environments. Current Research Focus Designing auditory contracts for smart devices Developing ethical sound frameworks Creating perceptually adaptive audio systems His recent publications explore: 2025: Auditory contracts in IoT 2025: Adaptive sound ethics 2025: Perceptually stabilizing audio 2023: Spatial audio in metaverse Scientific Grants: £99,711 Royal Academy of Engineering (2024-2025) £24,999 Innovate UK (2024-2026) Multiple AHRC grants (2022-2025) PhD Supervision: Dynamic robotic personality adaptation (2024) Adaptive game sound design (2022) Exosolar planetary sonification (2015-2021)

• Acoustics
• Finite Element Analysis
• Ultrasonics
• +۷ مورد دیگر

Marc Arnela Coll is an Assistant Professor at the Engineering Department of La Salle Digital Engineering School, where he actively contributes to research in acoustics, vibration control, and sustainable building technologies. His work spans interdisciplinary domains, integrating engineering, environmental science, and human comfort in architectural contexts. His research interests focus on acoustics , finite element analysis , ultrasonics , and sustainable materials , with applications in noise and vibration reduction, sound insulation, and eco-friendly construction. He explores innovative solutions such as acoustic black holes, recycled concrete walls, and ultrasonic waste classification. The trends in his recent publications (2022–2025) reflect a strong emphasis on both theoretical and applied acoustics, with increasing integration of sustainability and human-environment interaction. His work appears in high-impact journals such as Applied Acoustics , Waste Management , and Chaos, Solitons and Fractals , covering topics from urban soundscapes to biomedical voice modeling. Scientific Awards: No scientific awards listed in the provided text. Advising and Grants: While no formal students are listed, Marc Arnela Coll leads and participates in multiple funded research projects. He serves as Principal Investigator (PI) for projects such as Bettair V and Aria , and as a key researcher in initiatives like ABHSSYS and Inhabiting Gaudí . These projects are supported by internal grants, research contracts, and collaborative agreements, reflecting strong institutional and interdisciplinary support. Labs and Teams: He is a core member of the Human-Environment Research group at La Salle Digital Engineering School, collaborating closely with researchers such as O. Guasch, R. M. Alsina-Pagès, and M. Freixes Guerreiro. His work is deeply embedded in team-based, project-driven research environments focusing on acoustic innovation and sustainable design.

• Digital Signal Processing
• Spectral Analysis
• Pattern Recognition
• +۷ مورد دیگر

Maria Ragousi is a faculty member in the Department of Electrical and Electronic Engineering at the University of West Attica, affiliated with the School of Engineering. She holds a PhD in Digital Signal Processing and Pattern Recognition from NTUA (1994), an MSc from the University of Virginia (1990), and a Diploma in Electrical Engineering from NTUA (1987). Her academic role is as a Lecturer, focusing on courses such as Digital Signal Processing, Biomedical Signal Processing, and Educational Technologies. Education: PhD (1994): Digital Signal Processing & Pattern Recognition, NTUA MSc (1990): Digital Signal Processing, University of Virginia Diploma (1987): Electrical Engineering, NTUA Her research interests span Digital Signal Processing (DSP), Spectral Analysis, Pattern Recognition (including neural networks and genetic algorithms), Biomedical Signal Processing, Wireless Sensor Networks for environmental monitoring, and E-Learning technologies. She has contributed to over 30 peer-reviewed publications, including work on EEG-based person identification, environmental sound classification, and educational data mining. Recent research emphasizes integrating machine learning into education and developing tools for environmental acoustic monitoring. She has collaborated on projects like the ESOUNDMAPS initiative, deploying wireless sensor networks for real-time environmental sound mapping. Her work also explores active learning methodologies in physics education and visualization of e-learning platform data. Maria advises courses at both undergraduate and postgraduate levels, including specialized programs in medical signal analysis and smart electronic systems. She actively participates in academic governance and has led several educational innovation projects funded by national and international grants.

Sapountzaki Galiniمشاهده پروفایل

استادیار

• Greek Sign Language (GSL) Grammar
• Deaf Education
• Educational Technology for Sign Languages
• +۳ مورد دیگر

Sapountzaki Galini is an Assistant Professor at the Department of Special Education, University of Thessaly, specializing in Greek Sign Language (GSL). She has held this position since January 2012 and teaches courses on GSL linguistics and methodology. Her work focuses on language acquisition in deaf communities, educational accessibility, and technology-enhanced learning platforms for sign languages. Education: PhD in Linguistics (2005) from the University of Bristol Diploma in GSL Interpreting (1997) Bachelor’s in Philology (1994) from the Athens School of Philosophy Research Interests: Dr. Sapountzaki’s work bridges theoretical linguistics and applied education. She explores grammar structures in GSL, particularly tense/aspect markers, and advocates for bilingual education for deaf students. Her projects include developing e-learning platforms like SL-ReDu for GSL recognition and assessment, emphasizing 3D modeling and multimodal data fusion. She also examines the impact of language deprivation on deaf children and strategies for remote GSL instruction during crises like the pandemic. Grants & Advising: No specific grants listed, but her work is supported by projects like SYNENNOISI and DIANOIMA. She has advised on curricula for deaf education programs and collaborates with institutions like the Neuropsychology Laboratory and Pedagogical Institute. Her teaching spans special education teacher training and interpreter education. Labs/Teams: Collaborates with the Institute of Speech Processing (ISL) and the University of Thessaly’s Special Education Committee. Active in designing GSL video texts and accessibility tools for public schools.

• Machine Learning
• Computer Vision
• Neural Networks
• +۵ مورد دیگر

Tahiya Chowdhury is an Assistant Professor of Computer Science at Colby College. Her research focuses on intersections of machine learning, computer vision, and human-centric AI applications. She teaches courses including CS166 (Computational Thinking: Computer Vision), CS232 (Computer Organization), and CS343 (Neural Networks). Her work emphasizes ethical AI, multimodal interaction analysis, and sustainable technology solutions. Research interests span feature reliability in open-source tools, autism interaction studies using non-verbal cues, and urban policy compliance monitoring via vision-language sensing. Her projects include semantic segmentation frameworks for environmental monitoring and frameworks for marine debris cleanup without human labels. She explores user-centric approaches in street view image quality ranking and child-centered AI ethics. Her publications from 2021-2025 reflect a trend toward applied AI in healthcare (e.g., Medbuds medication tracking), environmental sustainability (atoll imagery analysis), and pandemic-era communication studies. Despite prolific output, no scientific awards are listed in the provided materials. Advising and grant information are not documented here. Her work integrates hardware-software systems like the Maestro ambient sensing platform, emphasizing practical deployments in smart environments while addressing privacy challenges. Key themes include reducing labeling efforts in IoT systems and designing socially responsible AI interfaces for diverse user groups.

Viveka Lyberg Åhlanderمشاهده پروفایل

استاد

• Speech Therapy
• Communication in Education
• Acoustics in Classrooms
• +۱۲ مورد دیگر

Viveka Lyberg Åhlander is a Professor at Åbo Akademi University in the Faculty of Humanities, Psychology and Theology, specializing in Speech Therapy. Her research focuses on communication and sound environments in schools, particularly examining speaker comfort and listening effort in educational settings. She is actively involved in intervention research, teacher training programs, and interdisciplinary collaborations related to health, cognition, and minority language education. Her research interests span Speech Therapy , Classroom Acoustics , Voice Ergonomics , Language Development , and Professional Voice Use . She investigates how acoustic environments affect teachers’ vocal health and students’ cognitive processing and linguistic comprehension. Her work integrates psychology, education, and health sciences, with a strong emphasis on practical interventions. The trends in her recent publications show a consistent focus on vocal health across professions (education and healthcare), acoustic design in learning and work environments, and accessibility in media for people with visual impairments. Her research employs both qualitative and quantitative methods, including scoping reviews, intervention studies, and cognitive experiments. She has been recognized with several scientific awards: Harry Elvins legat (2022) Hedersmedlem i Finska Röstergonomisällskapet (2020) Studenternas ros (2020) Viveka Lyberg Åhlander has supervised academic work and is actively involved in grants and research projects, including a current project on word art as pedagogy funded by Svenska kulturfonden (2023–2025). She organizes research networks and conferences, such as the Ordkonstnätverket and seminars on medical humanities. She also contributes through editorial work, peer review, and public engagement, including participation in the Knowledge Cabaret at Turku Swedish Theatre, reflecting cultural impact. She is a key figure in interdisciplinary research connecting speech therapy, education, and health, leading projects that bridge academic research with real-world applications in schools and healthcare settings.

David Stillمشاهده پروفایل

استاد مدعو

• Music Production
• Architectural Acoustics
• Theatre Design
• +۴ مورد دیگر

David Still is an Adjunct Professor in the Department of Music Production at Lebanon Valley College . He holds a B.S. from The Pennsylvania State University and has authored publications in fields spanning Architectural Acoustics , Theatre Design , and Digital Audio Networks . Education: B.S., The Pennsylvania State University His research focuses on Acoustic Design for performance spaces, 3D Auralization , and HVAC Sound Control , with applications in both music production and transportation noise analysis . Articles highlight his work on psychoacoustics , frequency spectrum shifts , and 3D visualization techniques for acoustical optimization. Current courses taught include PHY 205: Physics of Sound and IXD 153: Electronics for Designers . He previously served as Sr. Recording Engineer and Operations Manager at Schoolhouse Recording Studio (Westport, Connecticut, 1976-1984), contributing to Grammy Award-winning projects like Muddy Waters' Hard Again . His expertise extends to stage rigging , theatrical lighting systems , and IMAG/Broadcast Video , reflecting interdisciplinary work in live performance technology .

Nathan Weiszمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Auditory Perception
• Neural Oscillations
• +۷ مورد دیگر

Nathan Weisz is a Professor of Physiological Psychology in the Department of Psychology at the University of Salzburg , where he leads the Salzburg Brain Dynamics Lab and the MEG Laboratory at the Center for Cognitive Neuroscience Salzburg (CCNS). He has previously served as Associate Professor at the University of Trento’s CIMeC and as an Emmy Noether Group Leader at the University of Konstanz. . Doctorate: Department of Psychology, University of Konstanz (2001–2004) Diploma in Psychology: Catholic University of Eichstätt (1996–2001) His research focuses on understanding how the brain processes acoustic stimuli, particularly speech, using electrophysiological methods such as MEG and EEG. He investigates neural mechanisms in challenging listening environments (e.g., the 'cocktail party' problem), the role of neural oscillations in perception and memory, multisensory integration (e.g., audio-visual speech), and the development of tinnitus following hearing loss. His work has direct implications for hearing rehabilitation and cochlear implantation. The recent publications highlight advanced applications of M/EEG in decoding conscious perception across modalities, the role of alpha desynchronization in auditory working memory, and predictive neural activity in the auditory system. These reflect a strong trend in cognitive electrophysiology , predictive coding , and neural dynamics of perception . Nathan Weisz has not been mentioned as receiving specific scientific awards in the provided text. He advises graduate students in psychology and neuroscience, though specific names are not listed. His research is supported by institutional and likely external funding given his leadership roles and publication record. He leads a prominent research group focused on non-invasive brain imaging and cognitive dynamics. He leads the Salzburg Brain Dynamics Lab , which operates within the Center for Cognitive Neuroscience Salzburg (CCNS), utilizing MEG and EEG to study brain dynamics in perception and cognition.

Jyoti Joshi Dhallمشاهده پروفایل

مدرس ارشد

• Affective Computing
• Multimodal Behaviour Analytics
• Digital Health
• +۴ مورد دیگر

Jyoti Joshi Dhall is a Senior Lecturer in the Department of Human Centred Computing at Monash University, where she conducts interdisciplinary research at the intersection of artificial intelligence, behavioral analytics, and digital health. Her work contributes to UN Sustainable Development Goals, particularly in health and well-being. Her research focuses on affective computing , multimodal behavior analytics , and human-centered AI , with applications in mental and physical health monitoring. She employs advanced machine learning techniques to analyze behavioral signals such as facial expressions, speech, and body movements for detecting conditions like pain, apathy, and depression. Recent publications show a strong trend in applying deep learning models—such as LSTM-DNN and anomaly detection networks—to clinical and assistive technologies. Her work appears in top-tier venues including IEEE conferences and the ACM Handbook series, reflecting impactful contributions to multimodal user interfaces and emotion-aware systems. She has collaborated with international researchers and her work has been cited in Scopus and referenced in patents. Although no specific awards are listed, her research has attracted attention from news outlets and academic platforms like Mendeley. Jyoti Joshi Dhall advises students and likely supervises research projects in human-centered computing, though specific advisees are not listed. Her research is supported by institutional and possibly external grants, given the scope and publication record. She is part of a broader research network focused on AI for healthcare, contributing to both theoretical and applied advancements in the field. She is affiliated with a research team or lab working on multimodal interaction and affective computing, though the specific lab name is not mentioned in the provided text.

• Multimodal Sarcasm Detection
• Pragmatic Language Understanding
• Human-Machine Interaction
• +۳ مورد دیگر

Xiyuan Gao is an external researcher at Campus Fryslân, Graduate School, University of Groningen (RUG), Netherlands. Their research focuses on pragmatic language understanding in human-machine interaction, particularly multimodal sarcasm detection using textual, audio, and visual cues. Gao's work explores how prosodic variation, semantic incongruity, and facial expressions can be modeled to understand language beyond literal content. Key research areas include pragmatic computing, affective computing, and the development of computational models for sarcasm that account for emotional and cultural context. Recent publications (2024-2025) demonstrate a focus on deep learning approaches, such as graph attention networks and attention-based fusion, for multimodal sarcasm detection. The research emphasizes the functional trade-offs between different modalities and the role of emotional incongruity, with applications in improving human-machine interaction.

Ian Laneمشاهده پروفایل

دانشیار

• Natural Language Processing
• Speech Recognition
• Machine Translation
• +۵ مورد دیگر

Ian Lane is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin Engineering school, serving as Program Director for the Natural Language Processing Professional Master's Degree Program. He joined UCSC in Fall 2022 after an extensive career spanning academia and industry. His research centers on computational systems that understand spoken human language, spanning speech recognition, transcription, meaning interpretation, and contextually appropriate responses. Key research areas include: Natural Language Processing for real-world applications Conversational AI systems development Speech-to-speech translation technologies Multimodal interaction (audio-visual integration) Language technologies that learn through real-world interaction His recent publications demonstrate strong focus on hallucination detection in LLMs, tabular data understanding, explainable AI, and robust speech recognition systems. Current work emphasizes "in the wild" language technologies that adapt through user interaction. Dr. Lane has received recognition through impactful industry applications including Jibbigo (the first mobile speech translation app) and military translation systems deployed in Iraq and Afghanistan. He actively mentors students and collaborates across UCSC's Silicon Valley Campus programs including Games and Playable Media and Human-Computer Interaction. His vision includes integrating NLP with virtual environments for language learning and skill acquisition.

George P. Kafentzisمشاهده پروفایل

مدرس

• Speech Signal Processing
• Emotion Recognition in Speech
• Deep Learning
• +۵ مورد دیگر

George P. Kafentzis is a Lecturer in the Computer Science Department at the University of Crete, where he teaches Physics for Engineers (CS-112), Digital Signal Processing (CS-370), and Signals and Systems (CS-215). He is a core member of the Speech Signal Processing Lab within the Multimedia Informatics Labs, focusing on advanced signal processing methodologies. His educational background includes a Ph.D. in Signal Processing and Telecommunications from MATISSE Doctoral School (University of Rennes 1) and a Ph.D. in Computer Science and Engineering from the University of Crete (2014), a Master of Science in Computer Science (2010), and a Bachelor's degree in Computer Science (2008), all from the University of Crete. Research interests span speech, audio, and biosignal processing with emphasis on sinusoidal modeling, emotion recognition from speech, deep learning applications, pathological speech analysis, and music signal processing. His work bridges theoretical signal processing with clinical and engineering applications, particularly in non-invasive vocal fold pathology detection through glottal analysis. Recent publications demonstrate a strategic pivot toward cough sound analysis for respiratory diagnostics using AI, while maintaining core expertise in adaptive sinusoidal models for speech transformations. Publication trends reveal an evolution from fundamental speech modeling (2010-2016) toward applied health informatics (2021-present), with increasing focus on real-world diagnostic systems leveraging cough acoustics. Over 50% of recent work integrates deep learning with traditional signal processing for medical applications, particularly in low-resource settings. Graduate student Scholarship - Institute of Computer Science, FO.R.T.H. (2008-2010) Undergraduate Scholarship - Institute of Computer Science, FO.R.T.H. (2007-2008) As an active industry collaborator, Kafentzis has served as Signal Processing Engineer at Hyfe AI (2022-2025) and contractor for VoiceSignals and Toshiba Research Europe. His teaching portfolio includes a widely adopted textbook Continuous and Discrete Time Signal Processing (2019), which integrates MATLAB implementations with theoretical foundations. Current research leverages his signal processing expertise in cough monitoring systems validated through multicenter clinical trials. He leads projects in the Speech Signal Processing Lab including Novel Deep Learning Architectures for Automatic Speech Recognition and Speech Emotion Recognition and Visualization Techniques, with recent work extending to Greek-language pathological speech analysis and respiratory health monitoring systems.

• Graph-based Learning
• Multimodal Learning
• Generative AI
• +۷ مورد دیگر

Seungbae Kim is an Assistant Professor at the Bellini College of Artificial Intelligence, Cybersecurity, and Computing at the University of South Florida. He directs the Connected Social Artificial Intelligence Lab (CSAIL) and co-directs the Artificial Intelligence Research Group (AIR) within the university. Previous Affiliation: Postdoctoral Researcher at UCLA's Communication Department under Professor Jungseock Joo. Education: PhD in Computer Science from UCLA, affiliated with the Scalable Analytics Institute (ScAi) under Professor Wei Wang. His research integrates graph-based learning , multimodal learning , and generative AI to advance responsible AI applications in healthcare, mental health, and social systems. Key methodologies include Graph Neural Networks (GNNs) , diffusion models , and cross-modal alignment . Recent publications focus on depression detection , algorithmic fairness , and social media analytics . While his work explores AI for social good , no scientific awards are explicitly mentioned. His research groups emphasize interdisciplinary collaboration between AI , healthcare , and social sciences .