جست‌وجوی استاد و پژوهشگر

Jannik Wolffمشاهده پروفایل

پژوهشگر

• Generative Models
• Multimodal Learning
• Probabilistic Machine Learning
• +۶ مورد دیگر

Jannik Wolff is a Researcher and Ph.D. Candidate at TU Berlin's Machine Learning Group, advised by Prof. Klaus-Robert Müller and Shinichi Nakajima. He is also a Research Associate at the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Previously, he worked at SAP AI Research. His research focuses on generative models for multimodal data, probabilistic modeling, and applications in computer vision and inverse problems. He holds a Master’s degree from TU Berlin and a patent for graph-based priors in zero-shot learning. Key research interests include generative models (e.g., diffusion models, transformers), probabilistic ML, and multimodal learning. He has published peer-reviewed work on hierarchical VAEs, mixture-of-experts models, and low-shot learning techniques. Notable contributions include a patent on graph-based priors for image classification and a drone delivery system optimized via hybrid behavior planning. His work on Bayesian deep learning for optimization and emotion recognition using EEG data further highlights his interdisciplinary expertise.

• Systems Engineering
• Requirements Analysis
• Action Research
• +۳ مورد دیگر

Daune West is a Senior Lecturer in the School of Computing, Engineering and Physical Sciences. Her research focuses on systems inquiry, requirements engineering, and action research, with emphasis on human-technology interaction. She leads the Educational Research Group, exploring teaching methodologies in computing and requirements analysis. Current projects involve analyzing human-horse interactions using physiological signals to study equine-assisted therapy's psychological benefits. She has collaborated with signal processing colleagues to explore emotion detection through brain signals in equine contexts. Her work contributes to UN Sustainable Development Goals related to mental health and well-being. Major awards include the Sir Geoffrey Vickers Memorial Award (1990). She has organized CPD courses on systems thinking and agile methodologies, and reviewed for journals like the International Journal of Systems and Society. Research activities span over three decades with publications in action research, systems theory, and interdisciplinary applications.

Chuan Luمشاهده پروفایل

مدرس ارشد

• Bioinformatics
• Medical Imaging
• Artificial Intelligence
• +۴ مورد دیگر

Chuan Lu is a Senior Lecturer in Bioinformatics at the Department of Computer Science, Aberystwyth University. He holds a BEng from Tianjin University (China), an MSc from KU Leuven (Belgium), and a PhD from KU Leuven. His research focuses on applying artificial intelligence and computational methods to address challenges in medical imaging, reproductive health, and plant science. He has led multiple projects funded by organizations such as the Engineering and Physical Sciences Research Council and the Welsh European Funding Office. Research interests include AI-driven phenotyping in plants (e.g., Arabidopsis), diagnostic modeling for endometriosis and ectopic pregnancies, and healthcare data integration through knowledge graphs. His work bridges disciplines like bioinformatics, computer science, and medicine, with contributions to clinical decision support systems and open-source biobank management frameworks. Recent publications highlight advancements in EEG signal analysis, AI applications in agricultural phenotyping, and ultrasound-based predictive models for surgical planning. Projects include the 'Miscanthus AI' initiative for sustainable plant breeding and the 'LImBuS' open-source biobank system.

Francisco Garcia Sanchezمشاهده پروفایل

استاد

• Natural Language Processing
• Semantic Web
• Ontology Engineering
• +۴ مورد دیگر

Francisco Garcia-Sanchez is a Professor in the Department of Informatics and Systems at the University of Murcia, Spain, since 2007. He previously served as Vicedean of External Relations at the Faculty of Informatics from 2012 to 2017 and was an Assistant Professor at the University of Valencia. His research focuses on Natural Language Processing (NLP), Semantic Web technologies, ontology engineering, and AI applications in domains like cloud computing and data integration. He has published over 55 JCR-indexed papers, achieving an h-index of 20 (Scopus) and 27 (Google Scholar) with 2,789 citations. He has co-advised 7 doctoral theses and led 10 research projects in semantic web and NLP. Active in academic service, he serves on conference committees and is an editorial board member for two JCR journals. His work includes developing semantic systems for recommendation systems, financial data analysis, and bioinformatics. Francisco has conducted research stays at institutions like DERI, CITR, and SRI. Research interests span social semantic web, AI agents, semantic service-oriented architectures, and sentiment analysis. His recent work emphasizes social media-based political analysis, financial sentiment detection, and multimodal emotion recognition. He has pioneered ontology-driven frameworks for cloud service management and e-government applications. Teaching includes courses on distributed systems, enterprise informatics, and bioinformatics.

Angela Almela Sanchez-Lafuenteمشاهده پروفایل

دانشیار

• Forensic Linguistics
• Computational Linguistics
• Corpus Linguistics
• +۴ مورد دیگر

Angela Almela Sanchez-Lafuente is an Associate Professor in the Department of English Philology at the University of Murcia's Faculty of Arts and Humanities. She is affiliated with the LACELL research group (Linguistics Applied to Computing, Language Teaching and Lexicography). She earned her PhD from the University of Murcia in 2012 with a thesis on linguistic deception analysis in English and Spanish. Her research focuses on computational linguistics, forensic linguistics, and corpus-based studies of deception detection, political discourse, and medical text analysis. She has developed tools like Umutextstats for linguistic feature extraction and contributed to projects like AIInFunds for financial sector NLP applications. Her academic background includes extensive work in forensic linguistics, including studies on corpus applications in legal contexts and error analysis in specialized texts. She has published widely on NLP applications for sentiment analysis, political ideology detection, and cross-lingual machine learning. Her research often bridges computational methods with sociocultural issues, such as analyzing migrant representation in judicial decisions. Key areas of expertise include: forensic text analysis, transformer model applications, multilingual NLP, and developing linguistic tools for financial/economic monitoring. She has supervised research projects involving AI-driven platforms for financial information analysis and participated in international NLP competitions like IberLEF and SemEval.

• Natural Language Processing
• Sentiment Analysis
• Machine Learning
• +۶ مورد دیگر

Nikolai Rusnachenko is a Post-Doctoral Research Fellow at Bournemouth University's CfACTs PLUS and NLP-MMI research groups, affiliated with the Talbot Campus. His work focuses on advancing natural language processing through interdisciplinary collaborations, particularly in targeted sentiment analysis, multi-document summarization, and biomedical search interfaces. His research spans multiple domains, including: Developing deep learning models for sentiment attitude extraction in Russian and Vietnamese Creating context sampling frameworks for relation extraction in large texts Enhancing dialogue systems with literary personality traits Designing biomedical search interfaces He has published extensively in venues like SemEval, IEEE WIC, and ACM conferences, working with collaborators across Russia, Vietnam, and the UK. Recent publications highlight his expertise in: Applying LongT5 for Vietnamese media summarization Implementing chain-of-thought reasoning in emotion detection Advancing attention-based models for legal document analysis Optimizing biomedical information retrieval

Janusz A. Starzykمشاهده پروفایل

استاد

• Machine Learning
• Neural Networks
• Robotics
• +۷ مورد دیگر

Janusz A. Starzyk is a Professor of Electrical Engineering and Computer Science at Ohio University's Russ College of Engineering and Technology, and holds a concurrent professorship at the University of Information Technology and Management in Rzeszów, Poland. He earned his M.Sc. and Ph.D. in Electrical Engineering from Warsaw University of Technology and a habilitation from Silesian University of Technology. His research focuses on embodied intelligence, machine learning, neural networks, and VLSI design, with notable contributions to self-organizing systems and reinforcement learning. Starzyk has supervised 47 M.Sc. and 16 Ph.D. students, and his work spans over 190 peer-reviewed publications. He leads the Embodied Intelligence Lab at Ohio University and collaborates with institutions worldwide, including Nanyang Technological University and the Institute for Artificial Intelligence in Switzerland. His awards include the Best Research Paper Award from Ohio University and nominations for IEEE Fellow. He has secured $3.8 million in research grants, with projects in GPS signal processing, radar target recognition, and machine learning applications. His patents include innovations in object identification systems and self-organizing learning hardware. Starzyk's expertise bridges academia and industry, with roles as a consultant for companies like Magnolia Broadband and Sarnoff Research.

Adrian Horzykمشاهده پروفایل

استاد

• Artificial Intelligence
• Neural Networks
• Associative Systems
• +۴ مورد دیگر

Prof. Adrian Horzyk is a distinguished academic at AGH University of Science and Technology, where he leads research in Artificial Intelligence , Associative Systems , and Biocybernetics within the Department of Biocybernetics and Biomedical Engineering . His work bridges Neural Networks , Knowledge Graphs , and Biomedical Applications , with a focus on associative computing and computational intelligence . Key Roles: Professor, AGH University of Science and Technology Labs: Biocybernetics, Cognitive Science, and Artificial Intelligence Laboratory Horzyk's research explores associative knowledge graphs (ANAKG/LANAKG), self-optimizing neural networks (ASONN), and graph-based data structures (AGDS). He investigates how neural plasticity , synaptic delays , and semantic memory can enhance AI systems, including applications in medical diagnostics (e.g., Fetal Alcohol Syndrome classification) and emotional state analysis via chatbots. His recent publications span topics like ECG signal compression , stock market forecasting , and associative reasoning in neural networks . He has developed AVB+ trees for data structure optimization and DASNG (Deep Associative-Semantic Neural Graphs) for efficient data representation. Scientific Collaborations: Collaborated with leaders in AI, including Prof. Leszek Rutkowski and Prof. Ryszard Tadeusiewicz Contributed to international competitions and publications, including monographs like Artificial Associative Systems and Associative Artificial Intelligence (EXIT Publishing, 2013)

• Sleep and Cognition
• Affective Neuroscience
• Neurobiology of Memory
• +۵ مورد دیگر

Péter Simor is an Habil. Associate Professor at the Department of Affective Psychology of Eötvös Loránd University. He leads the Budapest Laboratory of Sleep and Cognition, focusing on sleep neurophysiology, cognitive processes during sleep, and affective neuroscience. His research integrates EEG neuroimaging with behavioral paradigms to study REM sleep microstructure, memory consolidation mechanisms, and interoceptive processing during sleep states. Key affiliations include roles as Head of Research Group at the Budapest Sleep Lab and Alternate Member of institutional ethics & international committees. His work addresses sleep disorders (e.g., REM behavior disorder, nightmares) and their neural correlates, with emphasis on thalamic activity, autonomic nervous system interactions, and cognitive-emotional interplay. He has pioneered studies on mind-wandering's role in implicit learning and developed novel methodologies for sleep EEG analysis. Research Themes: REM sleep physiology, sleep-memory interactions, neurobiology of dreams, chronotype effects, and stress-related mental disorders Techniques: High-density EEG, functional neuroimaging (MRI), polysomnography, ambulatory sleep monitoring Recent studies investigate daytime consequences of sleep fragmentation, circadian rhythm impacts on cognition, and the utility of wearable neurotechnologies. He collaborates internationally on longitudinal aging studies (e.g., HuBA project) linking sleep architecture to brain health metrics.

Moawia Eldowمشاهده پروفایل

دانشیار بالینی

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۲ مورد دیگر

Dr. Moawia Eldow is a Clinical Associate Professor in the Department of Computer Science and Engineering at the University of North Texas. His research spans artificial intelligence, machine learning, and computer vision, with applications in healthcare, security, and education. His recent work includes COVID-19 detection algorithms and facial recognition systems. His publications demonstrate a consistent focus on neural networks, pattern recognition, and human-computer interaction. Recent articles explore AI diagnostics, educational technology, and cybersecurity, reflecting interdisciplinary collaboration with healthcare and linguistics domains. Dr. Eldow maintains an extensive publication record with contributions to IEEE, Springer, and ACM venues. His lab investigates adaptive algorithms for real-world challenges including medical diagnostics and network optimization.

Asif Babaمشاهده پروفایل

دانشیار بالینی

• Computer Science
• Cybersecurity
• Internet of Things (IoT)
• +۷ مورد دیگر

Asif Baba is a Clinical Associate Professor in the Department of Computer Science and Engineering at the University of North Texas. His research focuses on cybersecurity, Internet of Things (IoT), and blockchain technology, with a particular emphasis on secure data transmission, phishing detection, and industrial networking. Research Keywords: Computer Science, Cybersecurity, IoT, Blockchain, Wireless Sensor Networks Email: Asif.Baba@unt.edu Dr. Baba’s recent publications highlight advancements in IoT security, including secure medical data transmission frameworks and fuzzy logic-based phishing detection systems. He has also contributed to blockchain applications in access control, accounting, and education records verification, alongside innovations in industrial IoT networking and RFID data cleansing. His work spans fog computing, drone simulation, and sensor localization, reflecting a multidisciplinary approach to solving real-world challenges through technology.

• Human-Robot Interaction
• Affective Computing
• E-commerce Search Algorithms
• +۴ مورد دیگر

Mingming Li is an active professor at the Chinese Academy of Sciences with extensive research contributions across multiple domains including human-robot interaction, e-commerce systems, and wireless communications. With over 110 publications spanning from 2007 to 2025, Dr. Li demonstrates consistent scholarly productivity and leadership in interdisciplinary research. Dr. Li's research interests span Human-Robot Interaction , Affective Computing , E-commerce Search Algorithms , Machine Learning , and Wireless Communications . Recent work focuses on understanding how humanoid robots' multimodal characteristics (appearance, voice, touch) affect users' emotional responses and cognitive processing, employing physiological measures like ECG and fNIRS. Simultaneously, Dr. Li leads research in e-commerce search optimization, developing novel deep learning architectures for improved recommendation systems. The publication record reveals significant trends toward increasingly sophisticated multimodal analysis in HRI and more efficient neural architectures for practical applications. Dr. Li's work bridges theoretical advancements in machine learning with practical implementations in human-centered systems. Dr. Li has advised numerous graduate students including Jiahao Chen, Aung Naing Win, and Songlin Wang, with whom collaborative publications demonstrate strong mentorship. Research has been supported by substantial funding reflected in the volume and quality of publications across top venues. Current research activities include leading projects on digital twin-based thermal error compensation, multimodal affective robot design, and advanced search algorithms for e-commerce platforms, indicating an active laboratory environment with multiple ongoing research threads.

• Developmental Psychology
• Infant-Parent Interaction
• Social Communication
• +۲ مورد دیگر

Amy Ahn is Lecturer in Psychology at the University of Miami College of Arts and Sciences. Her research examines social and emotional development through computer vision analysis of parent-child interactions. Primary research areas include: Affective responsivity in infant-parent dyads Attachment pattern development Social communication in autism spectrum disorders School-based mental health interventions Recent publications utilize innovative methods like computer vision and audio signal processing to objectively measure social behaviors during diagnostic assessments and natural interactions. Her work on the still-face paradigm demonstrates novel connections between micro-level interaction patterns and later attachment classifications.

• Machine Learning
• Physiological Signal Processing
• Emotion Recognition
• +۳ مورد دیگر

Mary Pidgeon is a Lecturer in the Department of Computer and Software Engineering at the Faculty of Engineering and Informatics. Her research focuses on emotion recognition through peripheral physiological signals and the integration of machine learning techniques with wearable technologies. She explores areas such as galvanic skin response, pulse volume, and skin temperature analysis to advance human-computer interaction and biomedical applications. Her recent work includes developing end-to-end models for emotion recognition and proposing federated learning frameworks for emotion understanding via smart clothing. These projects highlight her interest in ethical data usage and practical healthcare applications. No awards or grants are explicitly mentioned in the provided text.

Hao Xiongمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Health Informatics
• Medical Imaging
• +۳ مورد دیگر

Hao Xiong is a Research Fellow at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University. He specializes in applying machine learning and artificial intelligence to healthcare challenges, including medical imaging, signal processing, and clinical diagnostics. His work bridges computer science and health informatics, focusing on applications like cough classification, medical prognosis modeling, and automated analysis of clinical interactions. Key research areas include neural networks, acoustic signal analysis, and deep learning for healthcare applications. His systematic reviews and models address issues such as wet/dry cough differentiation, esophageal fistula prognosis, and delirium-dementia correlations. He has contributed to advancements in brain extraction algorithms, logo detection frameworks, and multimodal clinical data analysis. Dr. Xiong has been recognized with prestigious awards, including the IBM Rational Prize in Software Engineering (2010) and Best Student Paper Award (2016). His work emphasizes interdisciplinary collaboration, evidenced by projects involving robotics, epidemiology, and wearable technology for health monitoring. Awards: IBM Rational Prize (2010), Best Student Paper (2016), First Place in Algorithms (2012), Mentoring in Visual Computing (2017/2018) Grants/Projects: Visual Computing and Big Data Analytics (2017-2018), multiple collaborations in healthcare AI His research portfolio includes over 40 peer-reviewed publications, showcasing his impact in health informatics, medical imaging, and machine learning applications.