جست‌وجوی استاد و پژوهشگر

Alberto Sanfeliu Cortésمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Computer Vision
• +۱۲ مورد دیگر

Alberto Sanfeliu Cortés is a Full Professor of Computational Sciences and Artificial Intelligence at the Universitat Politècnica de Catalunya (UPC), where he has been a faculty member since 1981. He is affiliated with the Institut de Robòtica i Informàtica Industrial (IRI), a joint center of UPC and CSIC, and serves as the Scientific Director of the Unit of Excellence Maria Maeztu at IRI. He leads the Mobile Robotics research line and coordinates the Artificial Vision and Intelligent Systems Group (VIS). He previously served as director of IRI and the UPC Department of Automatic Control. Research interests: His work spans Artificial Intelligence, Robotics, Computer Vision, Pattern Recognition, SLAM, Human-Robot Interaction, Autonomous Systems, and Networked Robotics . He focuses on both theoretical and applied aspects, including urban robotics, autonomous navigation, and the integration of large language models in robotic systems. His research is deeply interdisciplinary, bridging engineering, AI, and societal applications. The recent publications highlight a strong trend toward human-centered robotics , particularly in urban environments, last-mile delivery, and cybernetic avatars. There is growing emphasis on large language models for explainability and personalization, collaborative robotics , and context-aware navigation using vision transformers. His work increasingly addresses societal integration of robots in smart cities and sustainable systems. Scientific Awards: Technology Prize from Generalitat de Catalunya Fellow of the International Association for Pattern Recognition (IAPR) Advising and Grants: He has supervised multiple PhD students, with current advisees working on topics like human intention learning and LLM-enhanced interaction. He has led 45 R&D projects, including 16 EU-funded ones, and was coordinator of the URUS project. Current projects include TORNADO (foundation models for robots handling deformable objects) and SOCIAL PIA (cybernetic avatars). He has also collaborated with Volkswagen Research on autonomous driving initiatives. Labs and Teams: He leads the Artificial Vision and Intelligent Systems (VIS) group and the Mobile Robotics research line at IRI, a premier robotics institute in Spain. His team is actively involved in EU and national projects, focusing on real-world deployment of intelligent robotic systems.

Weihua Zhouمشاهده پروفایل

دانشیار

• Health Informatics
• Medical Image Analysis
• Machine Learning
• +۳ مورد دیگر

Weihua Zhou is a Tenured Associate Professor at Michigan Technological University in the College of Computing, with affiliations in Applied Computing, Biomedical Engineering, Computer Science, Electrical and Computer Engineering, and Mathematical Sciences. He holds a PhD from Southern Illinois University Carbondale, an MS and B.Eng. from Wuhan University, and completed postdoctoral research at Emory University. Academic Positions : Tenured Associate Professor (2025–present), Tenure-Track Assistant Professor (2019–2025) at Michigan Tech; Nina Bell Suggs Endowed Professorship (2015–2019) at the University of Southern Mississippi. Research Interests : Focuses on medical imaging and health informatics , particularly machine learning applications in cardiovascular diagnosis , osteoporosis risk stratification , and senile dementia early detection . Additional work includes radiomics for COVID-19 severity assessment , federated learning in medical segmentation , and deep learning for proximal femur strength prediction . Scientific Awards : USM Nina Bell Suggs Endowed Professorship, USM College of Arts and Sciences Scholarly Research Award, American Heart Association Research Leaders Academy (2017, 2018), USM Butch Oustalet Distinguished Professorship Research Award. Lab & Tools : Leads the Medical Imaging & Informatics Lab (MIILab-MTU) and contributes to the NSF/MRI GPU Cluster. Open-sourced tools include KD4COVID19 for radiomics analysis and ECGTools for ECG classification.

Lisa Adamsمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence in Radiology
• Quantitative Imaging Biomarkers
• Oncological Imaging
• +۵ مورد دیگر

Dr. Lisa Adams is a Research Fellow at the Technical University of Munich (TUM) and an Attending Radiologist at TUM University Hospital Rechts der Isar, affiliated with the Diagnostic and Interventional Radiology department. She holds an Albrecht Struppler Clinician Scientist Fellowship (2024) and leads research in the Quantitative Imaging Biomarkers for Predictive Healthcare focus group. Adams earned her MD from Charité - Universitätsmedizin Berlin (2016), completed board certification in radiology (2021), and conducted postdoctoral research at Stanford University (2022-2023). She transferred her Habilitation in Experimental Radiology to TUM in 2024. Her research integrates AI with radiology diagnostics, specializing in: Developing machine learning methods for early disease detection and risk assessment Advancing quantitative imaging biomarkers across organ systems Body composition analysis and biological age estimation Multimodal analysis for personalized healthcare Ethical implementation of AI in clinical practice Adams' recent publications demonstrate strong focus on AI applications in radiology, spanning large language models for clinical reporting, deep learning for medical image interpretation, nanoparticle tracking in regenerative medicine, and radiomics for cancer diagnosis. Her work consistently bridges technical innovation with clinical translation. Awards & Recognition: Walter-Friedrich-Prize, Deutsche Röntgengesellschaft (2023) Alavi Mandell Award (2021) Invest in the Youth Stipend, ECR Vienna (2017) She actively mentors doctoral candidates, having supervised seven PhD students to completion since 2020 with two more nearing submission. Adams secures substantial research funding from DFG, EU, Wilhelm Sander Foundation, Bayern Innovativ, and Berlin Institute of Health. She serves as Scientific Editor for European Radiology and Trainee Editorial Board Member for Radiology: Artificial Intelligence , while also holding leadership positions in the German Radiological Society.

• Robot Cooperation
• Human-Robot Interaction
• People Motion Behavior
• +۵ مورد دیگر

Anaís Garrell Zulueta is an Associate Professor at the Polytechnic University of Catalonia (UPC) and a Robotics Researcher at the Institut de Robòtica i Informàtica Industrial (CSIC-UPC) . She serves as Vice-Director of the Mobile Robotics and Intelligent Systems subline and supervises the RAIG - Mobile Robotics and Artificial Intelligence Group . PhD (2013): European Doctorate with highest honors from UPC B.S. in Mathematics (2006) from University of Barcelona Diploma d'Estudis Avançats (DEA) in Control, Vision, and Robotics from UPC Her research focuses on Human-Robot Interaction (HRI) and robot cooperation , particularly in urban environments . Key themes include: Explainable AI for robot transparency Human motion behavior prediction Socially aware navigation systems Collaborative transport robotics Autonomous last-mile delivery systems Cybernetic avatars and societal implications Recent projects (2023-2025) include: TORNADO: Foundation models for robots handling deformable objects HandIA: AI-based rehabilitation tools LENA: Lifelong navigation learning TRIFFID: First responder assistance robotics SOCIAL PIA: Cybernetic avatar modeling Scientific recognition includes: Second Prize for Best Spanish Robotics Thesis Best Paper Award Nomination (IEEE/RSJ IROS, 2009) As an advisor, she supervises: PhD students: Ferran Gebelli Guinjoan, Lavinia Hriscu, Edison Bejarano Final year projects: 8 students on topics like LLM-enhanced interaction and LiDAR SLAM systems She operates within the Institut de Robòtica i Informàtica Industrial (IRI) and collaborates with Carnegie Mellon University.

• Semantic Web
• Ontologies
• Knowledge Representation
• +۱۱ مورد دیگر

Dieter A. Fensel is a Full Professor at the Institute of Computer Science, Faculty of Computer Science, University of Innsbruck, Austria . He has held academic positions at the University of Karlsruhe, Vrije Universiteit Amsterdam, and the University of Amsterdam. He founded the Digital Enterprise Research Institute (DERI) in Galway and Innsbruck and co-founded the Semantic Technology Institute International (STI2). His work spans semantic technologies, knowledge engineering, and intelligent systems. PhD in Political Science, University of Karlsruhe (1993) Habilitation in Applied Computer Science, University of Karlsruhe (1998) Masters in Computer Science (TU Berlin) and Social Science (FU Berlin) His research interests focus on the Semantic Web, ontologies, knowledge representation, web services, and intelligent systems. He investigates how semantics can enhance data interoperability, service composition, and knowledge sharing in distributed environments. His work bridges formal methods with practical applications in e-commerce, tourism, and digital enterprises. He emphasizes the role of semantics in enabling machine-understandable content and automated reasoning across domains. The research trends in his publications and projects reveal a consistent focus on semantic technologies, from foundational work on knowledge representation (e.g., KARL language) to large-scale EU projects on data ecosystems (PlanetData, BYTE), travel (EuTravel), and energy (ENTROPY). His work evolved from theoretical AI and knowledge engineering to applied semantic web services, linked data, and digital innovation in societal domains. His scientific awards include: Carl-Adam-Petri-Award of the Faculty of Economic Sciences, University of Karlsruhe (2000) As an academic advisor, Dieter Fensel has supervised over 25 PhD students and served on numerous Master’s and PhD committees. He has led more than 100 national and international research projects with total funding in the hundreds of millions of euros, including major grants from the EU’s 7th Framework Program, Horizon 2020, and Science Foundation Ireland. These projects span domains such as big data, ambient assisted living, transportation, and digital services. He co-founded and led several research labs and teams , including: Digital Enterprise Research Institute (DERI), Galway and Innsbruck Semantic Technology Institute (STI) Innsbruck Semantic Technology Institute International (STI2) Co-founder of the European Semantic Web Conference (ESWC) and International Semantic Web Conference (ISWC) These organizations foster global collaboration in semantic technologies and have become central hubs for research, innovation, and community building in the field.

Jeffrey Girardمشاهده پروفایل

استادیار

• Affective Communication
• Affective Computing
• Clinical Assessment
• +۴ مورد دیگر

Dr. Jeffrey Girard serves as Assistant Professor and M. Erik Wright Scholar in the Psychology Department at the University of Kansas, directing the Brain, Behavior & Quantitative Science Program and co-leading the Kansas Data Science Consortium. His interdisciplinary research bridges psychology, computer science, and statistics to investigate emotional expression through verbal and nonverbal behavior, with emphasis on individual differences and social contexts. Dr. Girard's educational background includes: Ph.D. in Psychology (Clinical) from the University of Pittsburgh M.S. in Psychology (Clinical) from the University of Pittsburgh B.A. in Psychology & Philosophy from the University of Washington His research centers on affective communication and affective computing , examining how emotions manifest in interpersonal interactions across clinical and non-clinical populations. Key focus areas include transdiagnostic psychiatry, multimodal behavior analysis, and the development of computational tools for clinical assessment. This work integrates statistical modeling with machine learning to address questions in interpersonal functioning and mental health diagnostics. Analysis of Dr. Girard's recent publications (2023-2025) reveals strong trends in computational psychiatry, with emphasis on multimodal datasets for emotion recognition, AI-driven clinical assessment tools, and transdiagnostic approaches to psychopathology. His work consistently bridges technical innovation in affective computing with real-world clinical applications, particularly in depression assessment and psychosis research. Scientific recognition includes: M. Erik Wright Scholar Dr. Girard actively contributes to academic service through editorial roles at IEEE Transactions on Affective Computing, Clinical Psychological Science, and other leading journals. He serves on executive boards for the Society for Interpersonal Theory and Research, Society for Affective Science, and Hierarchical Taxonomy of Psychopathology society, demonstrating leadership in advancing interdisciplinary research methodologies. He directs the Affective Communication and Computing Lab, which develops computational frameworks for analyzing emotional expression in clinical contexts, and co-leads the Kansas Data Science Consortium to foster cross-departmental data science initiatives.

Lalit Jainمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Artificial Intelligence
• +۹ مورد دیگر

Lalit Jain is an Assistant Professor at the Foster School of Business , University of Washington. His research bridges theoretical mathematics with practical machine learning systems, focusing on adaptive data collection under budget constraints, applied to marketing, cognitive psychology, and humor detection. Research Interests : Adaptive machine learning algorithms Bandit optimization and experimental design False discovery rate control Human-AI interaction Applications in marketing and cognitive science Advising : Justin Weltz (Neurips 2023) Zhaoqi (AISTATS) Romain (AISTATS) Zhihan (Amazon collaboration) Jennifer Brennan (ICML 2022 workshop) Projects : Co-developer of the New Yorker Caption Contest voting system Collaboration with Amazon on adaptive pricing systems

• Natural Language Processing
• Machine Learning
• Word Sense Disambiguation
• +۵ مورد دیگر

Hiroyuki Niiro is a Professor in the Department of Information Engineering at Ibaraki University's College of Engineering, where he has served since joining as an Assistant in 1993, becoming Lecturer in 1997, Assistant Professor in 2001, and Professor in 2015. Born in Nagasaki in August 1961, he graduated from Tokyo Institute of Technology's Department of Information Science in 1985 and earned his Doctorate in Engineering from the same institution in 1997. His research focuses on Natural Language Processing using machine learning and statistics , with additional interests in image and voice pattern recognition and data mining. His work has evolved from traditional NLP techniques to contemporary transformer-based approaches, particularly specializing in Japanese language processing, word sense disambiguation, and domain adaptation methods. Niiro's recent publications (2021-2025) demonstrate his shift toward large language models, with research spanning BERT adaptations, data augmentation techniques, multimodal learning, and Japanese-specific NLP challenges. His work shows a consistent trajectory from foundational NLP research to current state-of-the-art language modeling approaches. He currently supervises graduate students including Yang Lei (D2) and Yu Onodera (M2) in his laboratory. Niiro has authored numerous books including Fine-tuning of LLM and RAG (2024), Introduction to Natural Language Processing Starting with Document Classification (2022), and multiple deep learning programming guides. His laboratory maintains active research in natural language processing, with members participating in major conferences including the Annual Conference of the Association for Natural Language Processing. Niiro has also contributed to educational resources including statistical examination preparation materials and RSS technology introductions.

Fumihiro Kanoمشاهده پروفایل

پژوهشگر

• Comparative Psychology
• Animal Cognition
• Social Intelligence
• +۴ مورد دیگر

Fumihiro Kano is a comparative psychologist at the Centre for the Advanced Study of Collective Behavior, University of Konstanz, and an Affiliated Scientist at the Max Planck Institute of Animal Behavior. His research focuses on the evolutionary origins of social intelligence, using cutting-edge technologies like eye-tracking, motion-capture, and thermal imaging to study social cognition in great apes, monkeys, and birds. Education: PhD in Biological Sciences (Primate Research Institute, Kyoto University) Key Collaborations: Max-Planck Institute for Evolutionary Anthropology, University of Oxford, Kumamoto Sanctuary (Kyoto University) Kano’s work spans comparative analysis of gaze behavior, emotional processing, and collective decision-making. He has developed wearable sensors for free-flying pigeons and non-invasive methods for studying primates in sanctuaries. His studies on the human eye’s uniformly white sclera have provided experimental support for the gaze signaling hypothesis . Recent research integrates large-scale motion-capture systems with gaze-tracking to analyze interspecies interactions in pigeons, crows, and humans. He specializes in quantifying attention dynamics during collective behavior, including vigilance in birds and social cognition in apes. Scientific Awards: Heidelberg Academy of Sciences Manfred Fuchs Preis (2023) APA Division 6 Early Carrier Investigator Award (2020) Japanese Psychological Association International Award (2018) Kano leads interdisciplinary teams combining computer vision, psychology, and behavioral ecology. His work bridges evolutionary biology and technological innovation, with applications for understanding human uniqueness and animal cognition.

Alessandro Raganoمشاهده پروفایل

پژوهشگر

• Machine Learning
• Audio Processing
• Quality of Experience (QoE)
• +۶ مورد دیگر

Alessandro Ragano is a Postdoctoral Researcher at the Insight Centre for Data Analytics , where he has been investigating Quality of Experience (QoE) aspects of audio archives and developing data-driven approaches for QoE estimation and audio restoration using deep learning since 2018. Education: MSc in Computer Science and Engineering from Politecnico di Milano (Italy) BSc in Computer Engineering from Università Degli Studi di Salerno (Italy) His research integrates machine learning , audio signal processing , and multimedia quality assessment to improve speech enhancement, audio restoration, and perceptual modeling. Recent trends in his publications focus on self-supervised learning , objective quality metrics , and audio dataset generation with applications in speech separation, music representation, and audio inpainting. He actively contributes to open-source tools like Binamix and AQP for audio research and quality evaluation.

Jun Wuمشاهده پروفایل

پژوهشگر

• Vibration and Dynamics
• Medical Image Segmentation
• Surgical Artificial Intelligence
• +۳ مورد دیگر

Dr. Jun Wu is a Postdoctoral Research Assistant at the Department of Biology, University of Oxford, where he conducts research in the Animal Vibration Lab. Previously, he served as a research associate in the Department of Aerospace Engineering at the University of Bristol. His academic credentials include: PhD in Sound and Vibration Research from the University of Southampton Dr. Wu's research bridges vibration dynamics and biomedical engineering, with current work developing engineering technologies inspired by biological dynamic systems. His publication record reveals a significant pivot toward medical artificial intelligence since 2023, with dominant contributions in surgical vision-language models and medical image segmentation. This dual expertise enables unique cross-pollination between biological vibration principles and clinical AI applications. Analysis of his 2023-2025 publications shows concentrated innovation in adapting foundation models like Segment Anything Model (SAM) for medical contexts. Key advances address uncertainty quantification in segmentation, human-in-the-loop refinement systems, multi-modal diagnostic reasoning, and real-time surgical video analysis. These works consistently target clinical deployment challenges including safety verification, computational efficiency, and human-AI collaboration. Professional recognition includes: Associate Fellow of the Higher Education Academy (AFHEA) Member of the Royal Aeronautical Society (MRAeS) As a core member of Oxford's Animal Vibration Lab, Dr. Wu contributes to research investigating biological dynamic systems for engineering innovation while leading medical AI initiatives that translate these principles into surgical and diagnostic technologies.

• Child Psychiatry
• Autism Spectrum Disorder
• Attention-Deficit/Hyperactivity Disorder
• +۴ مورد دیگر

James McCracken is a tenured Professor of Psychiatry and Biobehavioral Sciences at UCLA's David Geffen School of Medicine. As Director of the Division of Child and Adolescent Psychiatry at the Semel Institute for Neuroscience and Human Behavior, he leads the NIMH-funded Research Center 'Translational Research to Enhance Cognitive Control' focusing on novel treatments for cognitive deficits in child psychiatry. His research spans pharmacogenomics, neurodevelopmental disorders (ASD, ADHD, OCD), and autonomic neurophysiology. Key affiliations: Center for Autism Research and Treatment (CART), ADHD Brain Research Institute, Society for Neuroscience Research themes: Pharmacologic interventions for neurodevelopmental disorders, white matter sex differences, EEG biomarkers, and genome-wide association studies Leadership roles: Principal Investigator for multiple NIMH grants, editorial board member for the Journal of Child and Adolescent Psychopharmacology His recent publications (2023-2025) emphasize precision medicine in ASD, OCD genetics, and pupillary response as a neurophysiological marker. Awards include the APA Young Psychiatrist Research Award and listings in Best Doctors and Top Doctors databases. Scientific Awards American Psychiatric Association Young Psychiatrist Research Award Best Doctors in America America's Top Doctors Publications Over 150 peer-reviewed articles across child psychiatry Leading research in pharmacogenomics and neuroimaging

Massimo Mecellaمشاهده پروفایل

استاد

• Service-Oriented Computing
• Business Process Management
• Process Mining
• +۱۲ مورد دیگر

Massimo Mecella serves as Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, where he leads the Processes, Services and Software Management research group and participates in the CINI National Cyber Security Lab. His academic foundation stems from a PhD in Computer Engineering earned at Sapienza in 2002. His research expertise spans service-oriented computing, business process management, and cyber-physical systems with emphasis on service composition, process mining, and adaptive distributed architectures. Key technical domains include IoT integration, digital twin development, and security frameworks for complex software ecosystems. Recent publications (2024-2025) demonstrate a pronounced shift toward Large Language Model (LLM) integration in business processes and smart manufacturing. Dominant themes include LLM-driven process modeling, multimodal quality control systems, and digital twin implementations for energy management and production optimization. Methodological innovations focus on retrieval-augmented generation (RAG) for service discovery and fuzzy cognitive maturity assessments. His distinguished recognition includes: ICSOC 2013 Most Influential Paper Award (2003-2012 decade) 2017 Best Paper Award As research group leader, Mecella directs projects in smart manufacturing, process mining, and cyber-physical security, with funding typically sourced from EU initiatives and industry partnerships in aerospace, healthcare, and energy sectors. His team maintains active collaborations with aerospace manufacturers through the MICS SPOKE8 project and develops frameworks like SAMBA for human-in-the-loop manufacturing systems. The Processes, Services and Software Management group operates within Sapienza's engineering faculty infrastructure, utilizing specialized labs for CPS/IoT testing and digital twin simulation, with strong ties to the CINI Cyber Security Lab for security validation.

Laure Soulierمشاهده پروفایل

مدرس

• Design of language models for Information Retrieval (IR) and Natural Language Processing (NLP)
• Data-to-Text Generation
• Search-Oriented Conversational Systems
• +۳ مورد دیگر

Laure Soulier is a HDR (Habilitation à Diriger des Recherches) Lecturer at Sorbonne University within the MLIA team at the ISIR (Institute for Intelligent Systems and Robotics) laboratory. Her research focuses on the design of language models for Information Retrieval (IR) and Natural Language Processing (NLP) applications, including data-to-text generation , search-oriented conversational systems , language models for robotics , and continual learning with domain adaptation . Recent publications highlight her work on cross-encoders, co-speech gesture generation, and latent space metrics. She supervises an ANR-funded postdoctoral researcher position (SCAI/BnF program) and collaborates on projects involving multimodal techniques, user interaction analysis, and document vectorization. Her scientific contributions include best paper awards at CORIA 2021, SCAI@EMNLP 2019, CORIA 2015, and AIRS 2013. Laure Soulier’s work spans collaborative information retrieval models, entity ranking in heterogeneous networks, and neural approaches for knowledge-based IR. She has contributed to evaluation frameworks for LLMs in IR and co-speech gesture generation, with applications in e-commerce search, medical information retrieval, and social media-based collaboration. Her research integrates user roles, document representations, and reinforcement learning techniques.

Måns Magnussonمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Probabilistic Machine Learning
• Statistical Inference from Textual Data
• +۴ مورد دیگر

Måns Magnusson is an Associate Professor at the Department of Statistics, Uppsala University, with affiliations at the Institute for Analytical Sociology (Linköping University) and the Institute for Future Studies. His work bridges Bayesian statistics, probabilistic machine learning, and textual analysis, focusing on model evaluation, diagnostics, and inference algorithms. He contributes to computational social science and digital humanities through text-as-data methods. Research Themes: Bayesian inference, probabilistic machine learning, statistical inference from textual data Key Applications: Sociology, political science, law, education statistics, public health Current Projects: Improving probabilistic programming generalizability (Swedish Research Council grant), SWERIK research infrastructure (Riksbankens jubileumsfond) His recent publications emphasize text mining, model comparison, and legal data challenges. He has developed tools for national ID number validation, hate crime estimation, and parliamentary corpus construction. Notable awards include the Cramér Prize (2018), Statistician of the Year (2023), and membership in the Swedish Young Academy (2023) and ELLIS (2024). Scientific Contributions: Botten Ada Bayesian election model, 'loo' package for cross-validation Collaborative Work: AI4Research sabbatical (2024), Riksbankens jubileumsfond funding Industry Background: Statistician roles at Swedish Agency for Education, Crime Prevention, and Public Health