جست‌وجوی استاد و پژوهشگر

Adriane B. Randolphمشاهده پروفایل

استاد

• Brain-Computer Interfaces
• Neuromarketing
• Neural Processing
• +۹ مورد دیگر

Dr. Adriane B. Randolph is a Professor and Executive Director of the BrainLab at Kennesaw State University’s Coles College of Business. Her work bridges neuroscience and information systems, focusing on brain-computer interfaces (BCIs) and their applications in assistive technologies, consumer behavior, and educational tools. Primary Affiliation: Kennesaw State University School: Coles College of Business Department: Information Systems Research interests include: Developing BCIs to assist individuals with locked-in syndrome (e.g., cerebral palsy, ALS) Neuromarketing studies on brand placement and consumer decision-making Exploring neural responses to workplace productivity and video games Designing systems to enhance cognitive engagement in educational settings Recent publications highlight interdisciplinary applications of BCIs in healthcare, education, and cybersecurity. Notably, her 2022 work in the Journal of Information Systems Education outlines a neuro-IS course, while 2020’s SAIS conference paper details IoT integration in BCI systems for locked-in patients. Scientific contributions include: 2020: Best Paper in Track, Southern Association for Information Systems (SAIS) Annual Conference Dr. Randolph mentors students in the BrainLab, fostering collaboration between undergraduate and graduate researchers. Her lab partners with institutions like Georgia Tech and the National ALS Association to advance BCI applications, with a mission to improve quality of life through non-invasive technologies.

María Dolores Porto Requejoمشاهده پروفایل

استاد

• Cognitive Linguistics
• Discourse Analysis
• Metaphor Studies
• +۳ مورد دیگر

María Dolores Porto Requejo is a Professor at the Department of Modern Philology (Universidad Autónoma de Madrid), specializing in Cognitive Linguistics and Discourse Analysis . She is a key member of the research group DICo: Discurso, Identidad y Cognición , focusing on socio-cognitive aspects of discourse. PhD in English Philology (Universidad Autónoma de Madrid, 2004) Her research focuses on: Multimodal metaphor analysis Discourse strategies in digital media Socio-cultural embodiment in linguistic representations Emotion and attention dynamics in narratives Metaphor's role in political and social contexts Recent publications analyze metaphorical constructions of social change (water metaphors), polarization in digital news, and multimodal storytelling. Her work appears in journals like Discourse and Society , Metaphor and Symbol , and Language and Communication . She has contributed to various international conferences on cognitive linguistics, discourse analysis, and digital communication, including presentations at: 13th International Conference of the Spanish Cognitive Linguistics Association (2024) 21st International Congress of Linguists (2024) Waterphors 2024 conference (2024)

Tillman Weydeمشاهده پروفایل

عضو هیئت علمی

• Machine Learning
• Signal Processing
• Data Analysis
• +۵ مورد دیگر

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

• Interactive Machine Learning
• Audiovisual Composition
• Computational Creativity
• +۳ مورد دیگر

Mick Grierson is a Researcher at Goldsmiths, University of London , specializing in Interactive Machine Learning , Audiovisual Composition , and Computational Creativity . His work bridges Music Technology , Human-Computer Interaction , and Assistive Technology , with a focus on making machine learning accessible for creative applications. He has developed open-source software like Maximilian and collaborated on projects involving Brain-Computer Interfaces and Digital Musical Instruments for rehabilitation. Research Interests : Interactive Machine Learning Generative AI for Audiovisual Art Accessibility in Music Technology Collaborative Coding Environments Rehabilitation through Digital Instruments Neural Network Applications Selected Projects : NoiseBear - Wireless controller for disabled children Plundermatics - Real-time media segmentation Event-Maximillian - Brainwave music interfaces

• Human-Computer Interaction
• Social Computing
• Artificial Intelligence
• +۵ مورد دیگر

Bongwon Suh is a Professor in the Department of Computer Science at the Korea Advanced Institute of Science and Technology (KAIST), College of Computing. With a prolific publication record spanning over two decades, Suh has established himself as a leading researcher in Human-Computer Interaction, Social Computing, and Artificial Intelligence applications. His research interests focus on Human-Computer Interaction, Social Computing, Artificial Intelligence, Large Language Models, Information Visualization, Recommender Systems, Multi-Agent Systems, and Accessibility Technologies. Suh's work often explores the intersection of social dynamics and technological systems, examining how AI and interactive systems can enhance human experiences in diverse contexts including education, entertainment, communication, and accessibility. Recent publications (2023-2025) demonstrate a strong focus on Large Language Model applications, with significant contributions in social simulation for education, conversational AI systems, multi-agent coordination, and accessibility technologies. His work frequently appears in top-tier venues including CHI, CSCW, UIST, and SIGIR, reflecting the high impact of his research. Suh has collaborated extensively with researchers across KAIST and internationally, with frequent co-authors including Changhoon Oh, Kyusik Kim, Hyungwoo Song, and Jeongwoo Ryu. His research program consistently bridges theoretical insights with practical applications, particularly in developing systems that enhance human social experiences through technology.

Ning Chengمشاهده پروفایل

استادیار

• Neurodevelopmental Disorders
• Autism Spectrum Disorder
• Fragile X Syndrome
• +۵ مورد دیگر

Ning Cheng is an Assistant Professor (Teaching & Research) at the University of Calgary's Faculty of Veterinary Medicine, with affiliations to the Alberta Children's Hospital Research Institute (ACHRI) and Hotchkiss Brain Institute (HBI). Their research focuses on neurodevelopmental disorders, particularly autism and Fragile X Syndrome, using rodent models to investigate mechanisms and develop experimental therapeutics. PhD in neuroscience from Johns Hopkins School of Medicine Postdoctoral work on neurological disorders at NIH Research spans molecular mechanisms, neural circuitry, and translational approaches to address social, communication, and behavioral challenges in autism spectrum disorders. The lab utilizes in vivo recording/modulation of brain activity, biochemical analyses, and multidisciplinary collaborations. Recent publications highlight expertise in EEG biomarker discovery, auditory processing abnormalities, ketogenic diet interventions, and ERK pathway modulation in mouse models of neurodevelopmental conditions. Key technologies developed include wireless cortical hemodynamic monitoring systems (TinyIOMS) and open-source electrophysiology tools (OSERR). As part of ACHRI's Precision Medicine & Disease Mechanisms program and HBI's Neurodevelopment/SCNIP strategic initiatives, Cheng contributes to university-wide efforts in Brain and Mental Health (2015-2021) and Child Health and Wellness (2020-2025).

• Environmental Systems Analysis
• Chemical Risk Assessment
• Life Cycle Assessment (LCA)
• +۳ مورد دیگر

Sverker Molander is a Full Professor at the Environmental Systems Analysis group at Chalmers University. His research integrates systems approaches to analyze human-induced environmental change and its mitigation, with a focus on chemical risk assessment, material flows, and renewable energy systems. He actively collaborates with social scientists to examine technology-society-ecosystem interfaces and participates in international programs like Sida's collaboration with Universidade Eduardo Mondlane in Mozambique. SETAC Global Science Committee member Baltic Sea Foundation research delegation Kamprad Family Foundation scientific reviewer His work employs environmental risk assessments, life cycle analyses, and substance flow modeling, particularly examining: Toxicological impacts of nanomaterials Renewable energy environmental interactions Chemical exposure limit inconsistencies Multidisciplinary approaches to sustainability Risk communication in chemical supply chains Climate-chemical pollution intersections Recent publications demonstrate expertise in: Ecotoxicity extrapolation methods Machine learning for toxicity prediction Circular tungsten flows Marine energy collision risks Climate-adapted chemical management His research connects technical systems with societal and ecological considerations, emphasizing indicator development and interdisciplinary collaboration.

Nathir Rawashdehمشاهده پروفایل

استادیار

• Image Processing
• Autonomous Vehicles Perception
• Mobile Robot Applications
• +۷ مورد دیگر

Nathir Rawashdeh is an Assistant Professor in the Department of Applied Computing at Michigan Technological University , with an affiliated appointment in Electrical and Computer Engineering . He is a Senior Member of the IEEE and a member of the Institute of Computing and Cybersystems (ICC) and Great Lakes Research Center . Education: Ph.D., Electrical Engineering, University of Kentucky, 2007 MS, Electrical and Computer Engineering, University of Massachusetts, Amherst, 2003 BS, Electrical Engineering, University of Kentucky, 2000 Dr. Rawashdeh's research focuses on unmanned vehicle perception , image analysis , control systems , and mechatronics , with applications in autonomous driving, winter weather adaptation, and industrial automation. His work includes sensor fusion, deep learning, and AI-enhanced manufacturing solutions. Recent publications highlight advancements in winter weather autonomous driving , UV disinfection robotics , and AI-driven industrial inspection systems . His research spans mechatronics curriculum development, industry 4.0 integration, and cross-cultural educational initiatives. Scientific Awards: Senior Member of the IEEE Dr. Rawashdeh has secured over $2 million in funding from organizations including the NSF , Ford Motor Co. , NIST , and the European Commission . His grants support projects like GPU clusters for research, winter weather autonomous driving standards, and UV sterilization robotics. He leads the Mobile Robotics Lab at Michigan Tech, focusing on collaboration and innovation in autonomous systems and mechatronics research.

Oğuzhan Atabekمشاهده پروفایل

دانشیار

• Educational Technology
• Human-Computer Interaction
• Digital Literacy
• +۷ مورد دیگر

Oğuzhan Atabek is an Associate Professor of Educational Technology at the Department of Curriculum and Instruction , Akdeniz University . With 42 publications (WoS), 16 h-index (WoS), and 520 h-index (Scholar), his research focuses on technology integration , distance education , and human-computer interaction in pedagogical contexts. Research Interests: Artificial Intelligence in Education Digital Writing and Anxiety Psychological Aspects of Technology Use Music Education Technology Teacher Training Innovations Scientific Recognition: Elsevier Outstanding Reviewer Award (2018) Current Affiliations: Member of Nilay Özaydın's Lab at Akdeniz University. Collaborates internationally on educational technology applications and psychological dimensions of digital learning.

Emmanouil Z. Psarakisمشاهده پروفایل

دانشیار

• Image Processing
• Computer Vision
• Machine Learning
• +۷ مورد دیگر

Emmanouil Z. Psarakis is an Associate Professor at the Department of Computer Engineering & Informatics , University of Patras, Greece. Born in 1963, he has been affiliated with the university since 2005 and is a member of the Signal Processing and Communications Lab . His academic journey includes teaching courses such as Signals and Systems Theory , Digital Signal Processing , and Computer Vision and Graphics . PhD in Computer Engineering and Informatics, University of Patras (1991) Dr. Psarakis is renowned for his research in image processing , computer vision , and signal processing , with applications in biomedical imaging , seismology , and robotics . His work spans deep learning , filter design , and 3D reconstruction , reflecting a multidisciplinary approach. His 15 most recent publications (2020–2025) focus on sign language recognition , adversarial defense , 3D shape analysis , and medical imaging . These works integrate machine learning , stochastic modeling , and computer vision to address challenges in video summarization , image inpainting , and seismic signal analysis . Dr. Psarakis has supervised over 10 PhD students , including Fotini Fotopoulou (2016–2019) and Panagiotis Georgantopoulos (2020–2023). He has participated in EU-funded , Hellenic , and bilateral R&D projects related to biomedical signal processing , robot vision , and forest fire monitoring . He leads the Signal Processing and Communications Lab , which collaborates with institutions like the Computer Technology Institute and international universities. His contributions include filter design , image alignment , and stereopsis techniques , with a focus on practical implementations in telecommunications and medical diagnostics .

Dominique Durandمشاهده پروفایل

استاد

• Neural engineering
• Computational neuroscience
• Neural interfacing
• +۹ مورد دیگر

Dominique Durand is a Professor of Biomedical Engineering at Case Western Reserve University and Director of the Neural Engineering Center. His research focuses on neural engineering, computational neuroscience, and neuromodulation, particularly for epilepsy treatment and neural interface development. Professor, Biomedical Engineering Director, Neural Engineering Center Research interests include: Neural interfacing and prostheses Non-linear dynamics of neural systems Control of epilepsy via electrical stimulation Carbon nanotube (CNT) yarn electrodes for chronic neural recording Computational modeling of neural activity Ephaptic coupling mechanisms in seizure propagation Recent work examines: Transcranial direct current stimulation (tDCS) effects on seizures Low-frequency stimulation for seizure suppression Neural activity in tumors for cancer-state determination Advanced electrode designs for peripheral nerve interfaces Autonomic nervous system modulation in disease Laboratory affiliations include the Neural Engineering Center, which develops technologies for neural system analysis and therapeutic interventions.

Franc Solinaمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• 3D Documentation
• +۶ مورد دیگر

Franc Solina is a Full Professor at the Faculty of Computer and Information Science , University of Ljubljana, Slovenia. He holds a Ph.D. from the University of Pennsylvania and has been active in academia since the 1990s. Education: Dipl.Ing. (1979) and M.S. (1982) in Electrical Engineering, University of Ljubljana Ph.D. (1987) in Computer and Information Science, University of Pennsylvania Research Interests: His work spans Computer Vision (superquadric modeling, underwater archaeology documentation), Human-Computer Interaction (interactive art installations, sign language technology), and Air Transport Applications (machine learning for aircraft trajectory prediction). He also explores Color-Based Applications and Visual Expression in art-technology intersections. Publication Trends: Franc's 15 most recent articles focus on superquadric modeling (1990-2004), underwater archaeology (2013-2015), and machine learning applications (2020). His work bridges theoretical computer vision with practical implementations in art and aviation. Students: He has supervised notable students like Marko Hrastovec (2018 thesis on aircraft trajectory prediction) and Tim Oblak (2020 work on superquadric deep learning). Labs & Teams: A key member of the University of Ljubljana's Computer Vision Laboratory , he collaborates with international researchers in projects like the Slovenian sign language web dictionary and air traffic safety initiatives .

• Geotechnical Engineering
• Site Characterization
• Novel Sensing Technology
• +۶ مورد دیگر

Pradeep U. Kurup is a Distinguished University Professor in the Department of Civil and Environmental Engineering at the Francis College of Engineering, University of Massachusetts Lowell. He has been serving at UMass Lowell since 1997, progressing from Assistant Professor to Associate Professor (2001), Full Professor (2005), and ultimately to University Professor (2014), which is the highest faculty honor at UMass Lowell. Dr. Kurup's educational background includes: Ph.D. in Civil and Environmental Engineering (1993) from Louisiana State University M.Tech. in Civil Engineering (1987) from Indian Institute of Technology - Madras, India B.Tech. in Civil Engineering (1985) from University of Kerala, India Dr. Kurup's research focuses on the intersection of geotechnical engineering and advanced sensing technologies. His work spans multi-sensor data fusion for site characterization, novel sensing technology applications, finite element modeling, artificial neural networks for soil mechanics, calibration chamber testing, soil-structure interaction, and "Seeing-Ahead Techniques" for trenchless technologies. His recent publications demonstrate a strong trend toward integrating machine learning techniques with geotechnical instrumentation, particularly in developing electronic noses and tongues for environmental monitoring and contamination detection. Dr. Kurup has received numerous awards and honors, including University Professor (2014), Diplomat Geotechnical Engineering (2012), NSF CAREER Award (1999-2003), and CERF Career Development Award (1999). Dr. Kurup has secured substantial research funding from NSF, Federal Highway Administration, EPA, and U.S. Army Research Office. His research collaborations span academia, industry, and government agencies globally, including partnerships with Geoprobe Systems Inc., Fugro Engineers Inc., Norwegian Geotechnical Institute, and several international universities. Dr. Kurup leads research in innovative sensing technologies for geoenvironmental applications, including electronic noses for detecting hazardous chemicals and explosives, electronic tongues for heavy metal detection, and advanced cone penetrometer systems for subsurface characterization.

Ryoma Hattoriمشاهده پروفایل

استادیار

• Reinforcement Learning
• Decision Making
• Number Sense
• +۴ مورد دیگر

Ryoma Hattori is an Assistant Professor at the University of Florida, based at the UF Scripps Biomedical Research campus in Jupiter, FL. His laboratory, the Hattori Lab, focuses on neural mechanisms underlying cognitive functions, learning, and their disruption in autism. Dr. Hattori received his educational degrees from prestigious institutions: Ph.D. in Molecular and Cellular Biology from Harvard University (2016) A.M. in Molecular and Cellular Biology from Harvard University (2012) B.S. in Biophysics and Biochemistry from the University of Tokyo (2010) His research interests center on decision making, reinforcement learning, and number sense, using systems and computational approaches. The lab employs techniques such as in vivo 2-photon imaging, optogenetics, virtual reality behaviors, and machine learning to investigate neural activity and plasticity dynamics in mice. A significant focus is understanding how these processes are impaired in autism spectrum disorder. Analysis of his recent publications reveals a strong emphasis on computational neuroscience and neural circuit mechanisms. His work spans from developing advanced imaging and analysis tools to uncovering fundamental principles of value coding and meta-reinforcement learning, with applications in both basic neuroscience and artificial intelligence. Dr. Hattori has received numerous scientific awards, including: Outstanding Mentor Award 2025 from Society of Research Fellows, UF Scripps SFARI Bridge-to-Independence Award 2022-Current from Simons Foundation Warren Alpert Distinguished Scholar Award 2021-2024 from Warren Alpert Foundation Postdoctoral Grant Award 2021-2022 from The KANAE Foundation And several fellowships during his postdoctoral and graduate training. As a principal investigator, Dr. Hattori leads multiple active grants, including the Shenoy Undergraduate Research Fellowship in Neuroscience (2025-2026) and a project on "Neural activity and plasticity dynamics for reinforcement learning in autism" funded by the Simons Foundation. His mentorship has been recognized with the Outstanding Mentor Award. The Hattori Lab is a dynamic research group utilizing cutting-edge technologies to explore the neural basis of cognition, with a particular interest in translational implications for autism and related disorders.

Guy Rosmanمشاهده پروفایل

دانشیار مدعو

• Machine Learning
• Surgical Computer Vision
• Human-Aware Robotics
• +۳ مورد دیگر

Guy Rosman is an Adjunct Associate Professor at Duke University, affiliated with both the Department of Surgery and the Department of Biostatistics & Bioinformatics. He has extensive academic and industry experience, including postdoctoral work at MIT/CSAIL and roles at IBM Research, RAFAEL Ltd., Medicvision, Invision Biometrics (Intel RealSense), and the Toyota Research Institute, where he leads the Human Aware Interaction & Learning team. Education: Ph.D., MSc, and BSc from the Technion - Israel Institute of Technology in Computer Science. Dr. Rosman’s research focuses on applying machine learning and inference techniques to surgical computer vision, human-aware robotics, autonomous driving, and sensor modeling. His work bridges robotics, AI, and medical applications, emphasizing human-centric systems and real-time learning. Recent publications highlight his contributions to generative robot simulation, surgical event prediction, driver safety interfaces, and shared autonomy. These works span robotics, machine learning, and AI applications in surgery and autonomous systems, with a recurring emphasis on human-aware algorithms and sensor-driven modeling. Scientific Awards: Technion-MIT Post-Doctoral Fellowship, Jacobs-Qualcomm Fellowship. Dr. Rosman’s industry leadership includes developing AI-driven robotics and sensor systems, while his academic roles involve collaborative research across Duke’s departments and MIT/CSAIL. He also co-edited the 2021 book Artificial Intelligence in Surgery , underscoring his interdisciplinary focus.