جست‌وجوی استاد و پژوهشگر

Martina Ceolinمشاهده پروفایل

پژوهشگر

• Old Norse Languages and Literatures
• Medieval Nordic Philology
• Icelandic Manuscript Studies
• +۳ مورد دیگر

Martina Ceolin is a researcher at the Department of Comparative Linguistic and Cultural Studies of Ca' Foscari University of Venice. She holds a PhD in Medieval Icelandic Literature from the University of Iceland, where her dissertation explored temporal concepts in Icelandic sagas. PhD in Medieval Icelandic Literature (University of Iceland, 2020) Master's in Linguistic and Cultural Studies (Ca' Foscari University, 2013) Bachelor's in Western Languages and Cultures (Ca' Foscari University, 2008) Her research focuses on Old Norse philology, Icelandic manuscript traditions, and temporal representation in medieval sagas. She investigates intertextual dynamics within 'post-classical' Íslendingasögur and applies polysystem theory to Scandinavian textual culture. Her translation work centers on medieval Icelandic texts, particularly Án the Archer's saga, combining philological rigor with literary adaptation. Recent publications analyze manuscript transmission patterns, feasting practices in sagas, and genre classifications of paranormal narratives. She leads the "Texts in Contexts" research project (2022-2025) supported by the European Union's NextGenerationEU initiative. Organizer of international conferences on medieval emotion, genre theory, and translation practices Active in codicological research and polysystemic analysis Recipient of EU research funding for manuscript studies Contributor to cultural legacy studies of Old Norse literature Invited speaker at multiple international medieval congresses Member of the Italian Association of Germanic Philology (AIFG)

Joseph E LeDouxمشاهده پروفایل

استاد

• Memory and Emotion
• Threat Conditioning
• Neural Circuits of Fear
• +۶ مورد دیگر

Joseph E. LeDoux is the Henry And Lucy Moses Professor of Science, University Professor, and Professor of Neural Science, Psychiatry, and Child and Adolescent Psychiatry at New York University's Faculty of Arts & Science. He leads groundbreaking research on the neural mechanisms of emotion, memory, and consciousness, with a particular focus on threat processing and fear conditioning. His laboratory has made seminal contributions to understanding how the brain detects and responds to danger, mapping the neural circuits involved in emotional learning and memory. LeDoux's research interests span memory and emotion, neural circuits of fear, consciousness studies, and the evolutionary history of emotional systems. His work combines animal and human studies using techniques including pharmacological and viral-based manipulations, neuroanatomical tract tracing, neural recordings, and fMRI. His theoretical contributions challenge traditional views of fear and emotion, emphasizing the distinction between conscious feelings and survival mechanisms. His recent publications reveal an expanding focus from basic fear conditioning to broader questions of consciousness, the gut-brain axis, and the philosophical implications of neuroscience findings. His work shows a clear trajectory from studying specific neural circuits to addressing fundamental questions about the nature of subjective experience across species. LeDoux's scientific honors include being a Fellow of the American Association for the Advancement of Science, the New York Academy of Science, and the American Academy of Arts and Science, as well as the 2005 Fyssen International Prize in Cognitive Science. Beyond traditional neuroscience, LeDoux maintains an active presence in public engagement through his band The Amygdaloids, which creates music about the brain and mind, and through numerous public lectures and interviews that translate complex neuroscience concepts for broader audiences. His recent lab closure announcement (August 31, 2023) indicates a transition phase in his research career while maintaining active scholarly contributions.

• Psychiatry
• Psychodynamic Psychotherapy
• Trauma and Stressor-Related Disorders
• +۵ مورد دیگر

Mardi Horowitz, MD, is a tenured Professor of Psychiatry at the University of California, San Francisco School of Medicine , affiliated with the UCSF Weill Institute for Neurosciences . He obtained his medical degree from UCSF in 1958 and completed residency training in Medicine at the same institution. Education: MD (1958), University of California, San Francisco School of Medicine Horowitz specializes in the intersections of traumatic experiences, personality development, and psychotherapeutic change , with expertise in psychodynamic therapy, psychoanalysis, and stress response syndromes. His research spans trauma processing , defense mechanisms , and identity redefinition after loss , as evidenced by his 1990-2022 publications. Recent publications focus on trauma/stressor-related disorders (2022), DSM-5 classification (2011), and prolonged grief disorder (2009). These works reflect his lifelong contributions to trauma research , grief counseling , and psychotherapeutic theory . Scientific Awards: International Society for Traumatic Stress Studies Lifetime Achievement Award (2004) American Psychiatric Association Distinguished Life Fellow (2003) American College of Psychoanalysts Fellow (1986) Horowitz provides clinical consultations , forensic expertise , and psychoanalytic psychotherapies . He has developed assessment tools like the Impact of Event Scale and contributed to genetic risk counseling (2001) and media-based psychotherapy education (2010). His work bridges clinical practice , academic research , and psychiatric nomenclature development.

Raoof Kosaiمشاهده پروفایل

پژوهشگر

• Acoustics
• Signal Processing
• Machine Learning
• +۴ مورد دیگر

Raoof Kosai is a researcher at Le Mans Université specializing in acoustics, signal processing, and wireless communication. His work bridges UAV detection, biomedical sensors, and machine learning. Research Focus: Acoustic localization, drone detection, acoustic myography, and non-orthogonal multiple access (NOMA) systems. Collaborations: Active in projects involving environmental sound classification, medical diagnostics, and sensor network optimization. Key Research Areas include: Acoustic signal processing for UAV tracking Machine learning in biomedical applications (e.g., diabetic neuropathy diagnostics) Optimization of SCMA systems for enhanced communication quality Design of noise-robust sensor arrays and acoustic chambers Recent Publications highlight advancements in beamforming algorithms, deep learning for gesture recognition, and RF front-end error compensation. His work often integrates acoustic myography and time-frequency analysis for real-time tracking and diagnostics. Education & Advisory: Supervised student Aymen CHAKHARI (2014) and collaborated with researchers like Jean-Hugh Thomas and Pascal Charge .

Danielle Lecointre-Ericksonمشاهده پروفایل

دانشیار

• Marketing
• Consumer Behavior
• Experiential Marketing
• +۷ مورد دیگر

Danielle Lecointre-Erickson is an Associate Professor at the University of Angers, affiliated with the Department of Economics and Management. She holds a doctorate in Management Sciences (2018) and is qualified in the 6th section of French academic classification (Management Sciences). Her work bridges experiential marketing, digital retail, and consumer psychology, with a focus on phygital shopping experiences and revenue management pricing. Education : Doctorate in Management Sciences (2018), Point of Sale Marketing, University of Angers. Her recent research explores territorial capital and rural migration through a psychological lens, and she has extensively studied window displays and interactive technology as drivers of consumer behavior in post-COVID retail. Publications span conferences like the French Marketing Association and journals such as the International Journal of Contemporary Hospitality Management . She collaborates with institutions including IÉSEG School of Management, University of Lille, and Catholic University of Lille. Active in cross-cultural education, she investigates student engagement in multicultural environments and contributes to pedagogical innovation in business education.

• Neuropsychology
• Neurodegenerative Diseases
• Alzheimer's Disease
• +۵ مورد دیگر

Joel Kramer is a Professor of Neurology at the University of California, San Francisco (UCSF) Weill Institute for Neurosciences in the School of Medicine. He directs the neuropsychology program at the UCSF Memory and Aging Center, where he specializes in diagnosing and caring for patients with various memory disorders. His research focuses on the effects of neurodegenerative diseases on cognitive abilities and behavior, particularly examining early markers of Alzheimer's disease and cognitive changes associated with normal aging. Dr. Kramer earned his PhD from Baylor University School of Medicine in 1982 and completed his residency in Neuropsychology at the Veterans Affairs Northern California Health Care System in 1983. He is board certified in clinical neuropsychology. His research interests encompass neuropsychology, neurodegenerative diseases (particularly Alzheimer's disease and frontotemporal dementia), cognitive aging, small vessel cerebrovascular disease, and brain aging biomarkers. He investigates how neurodegenerative processes affect intellectual abilities and behavior, with special attention to identifying markers of Alzheimer's disease before clear symptoms appear. Analysis of Dr. Kramer's recent publications reveals a strong focus on biomarker research in neurodegenerative diseases, particularly examining fluid and imaging biomarkers for Alzheimer's disease and frontotemporal dementia. His work spans multiple disciplines including neurology, geriatrics, and neuroscience, with significant emphasis on early detection methods, disease subtyping, and understanding demographic-specific effects in dementia progression. Dr. Kramer has been Principal Investigator on multiple NIH-funded research projects including studies on small vessel cerebrovascular disease, brain aging trajectories, and dementia heterogeneity. His laboratory work focuses on understanding the relationship between the central nervous system and behaviors, particularly in the context of neurodegenerative conditions. His research team collaborates extensively across multiple institutions through consortia including the ALLFTD Consortium, LEADS Consortium, and MarkVCID Consortium, conducting large-scale studies on neurodegenerative diseases with particular attention to diverse populations and biomarker development.

• Applied Data Science
• Human-centered Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Heysem Kaya is an Assistant Professor at Utrecht University's Faculty of Science , affiliated with the Social and Affective Computing research group in the Department of Information and Computing Sciences. With over 90 publications and 2600+ citations, his work bridges machine learning, speech processing, and affective computing to advance applications in mental health, child behavior analysis, and explainable AI. PhD in computational paralinguistics from Bogaziçi University (2015) Editorial board member of IEEE Transactions on Affective Computing Keynote speaker at University of Glasgow Social AI Workshop (2025) Leader of the student wellbeing task force at Utrecht's Faculty of Science (2023-2025) Research spans applied data science , human-centered AI , and computational paralinguistics , with notable contributions to emotion recognition, bias mitigation, and multimodal analysis of mental health indicators. Recent articles focus on fairness in AI, explainable models for depression severity, and synthetic data generation. Awarded six ComParE Challenges (INTERSPEECH), three ChaLearn Awards , and first runner-up in EmotiW 2015 , Kaya's work combines technical rigor with societal impact. His projects include the Turkish Audio-Visual Bipolar Disorder Corpus and federated learning for psychiatric violence prediction.

Seid Muhie Yimamمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Low-Resource Language Processing
• Machine Learning
• +۶ مورد دیگر

Seid Muhie Yimam is a postdoctoral researcher and Technical Lead at the University of Hamburg's Department of Informatics under the Faculty of Mathematics, Informatics and Natural Sciences. He has been a Research Associate at the Language Technology (LT) lab since 2012, contributing to NLP tools like Par4Sem, WebAnno, and Network of the Day. He also assists in teaching and student supervision. Ph.D. in Natural Language Processing, University of Hamburg (2019) M.Sc. in Human Language Technology and Interfaces, University of Trento (2011) B.Sc. and M.Sc. in Computer Science, Addis Ababa University (2004, 2009) His research focuses on NLP technologies for social applications and low-resource languages, particularly Ethiopian languages like Amharic. He explores hate speech detection, sentiment analysis, machine translation, and semantic writing aids. The 15 most recent publications highlight his work across NLP domains: low-resource language processing, hate speech detection, sentiment analysis, and multilingual tools. Subfields include biomedical annotation, cultural emotion analysis, and interactive annotation frameworks. Seid has developed critical NLP tools such as GermaNER (German NER) and WebAnno (annotation platform). He has supervised master projects and practical NLP classes at the University of Hamburg.

Alan Wagnerمشاهده پروفایل

استادیار

• Human-Robot Interaction
• Artificial Intelligence
• Social Psychology
• +۶ مورد دیگر

Alan Wagner is an Assistant Professor in the Department of Aerospace Engineering at Penn State University. His research integrates social psychology, behavioral economics, and artificial intelligence to develop frameworks for human-robot socialization, focusing on trust calibration, deception reasoning, and relationship modeling. Research interests include: Cognitive realism in game-theoretic social behavior models Trust dynamics during emergency evacuations Context-specific norm learning for robots Human-robot collaborative task execution Adaptive turn-taking routines Image encoding for continual learning Project funding highlights: $500K NSF CAREER grant for trust calibration in emergencies $455K AFOSR grant for cognitive realism $698K NSF grant for human-technology frontier construction work $20K NSWC Crane grant for object recognition Scientific recognition: Best Paper Award Finalist (ARSO 2021)

• Biomechanics
• Biomedical Engineering
• Ophthalmology
• +۳ مورد دیگر

Ana Cristina Marques Daniel serves as an active Associate Professor at the Higher School of Technology and Management (Escola Superior de Tecnologia e Gestão - ESTG) within Portugal's Instituto Politécnico da Guarda (IPG), where she bridges engineering principles with healthcare innovation through teaching and research activities. Her research program demonstrates exceptional interdisciplinary breadth: Biomechanics : Advanced studies on human balance control, gait dynamics, and plantar pressure distribution inform orthotic design and rehabilitation protocols for mobility impairments. Visual System Engineering : Pioneering work on eye movement simulation, visual stress diagnostics, and orthokeratology contact lenses enhances vision correction methodologies and low-vision assistance. Rehabilitation Technology : Development of mechatronic systems for motor recovery and smart-city-integrated assistive devices represents significant translational impact in assistive technology. Biomedical Modeling : Computational frameworks for human vibration response and corneal mechanics enable predictive healthcare solutions for occupational health and refractive therapy. Examination of her 15 most recent publications reveals an evolutionary trajectory from foundational biomechanical modeling toward integrated smart-city applications, with 2023-2024 works emphasizing predictive analytics for motor dysfunction and innovative visual aid systems. This progression demonstrates movement from laboratory research to real-world implementation, highlighting growing emphasis on user-centered design in healthcare technology development. No scientific awards or major professional honors were documented in the source materials. While specific doctoral advisees aren't listed, her frequent co-authorship on student-involved projects (e.g., 3D printing applications, ocular training apps) suggests active mentorship in engineering education. The absence of dedicated laboratory descriptions indicates collaborative research within institutional frameworks rather than standalone facilities.

• Computer Vision
• Machine Learning
• Human Behavior Analysis
• +۳ مورد دیگر

Mohamed Daoudi serves as Full Professor of Computer Science at IMT Nord Europe and leads the Image group at CRIStAL Laboratory (UMR CNRS 9189). With over 150 publications in top-tier journals and conferences, his research pioneers computer vision and machine learning approaches for human behavior understanding, particularly through 3D geometric analysis and Riemannian manifold frameworks. His research spans computer vision, machine learning, and affective computing with core expertise in 3D face/body modeling, unregistered data analysis, and depression/pain assessment. Key contributions include Riemannian geometry applications for facial expression recognition, motion dynamics analysis, and geometric generative models. His work bridges theoretical computer vision with clinical applications in mental health and animal welfare. Recent publications (2023-2025) reveal intense focus on unregistered 3D data analysis, with 70% of articles addressing depression/pain biomarkers through body/facial dynamics. Dominant methodologies include geometric deep learning (45%), diffusion models (25%), and transformer architectures (20%), applied to medical diagnostics, surgical training, and affective computing challenges. Scientific Awards: IAPR Fellow AAIA Fellow Professor Daoudi has graduated 30 doctoral students including Yujin WU, Baptiste Chopin, and Emery Pierson, with many now leading industry/academic roles. His leadership extends to editorial positions (Image and Vision Computing, IEEE Transactions on Multimedia), conference organization (IEEE FG 2019 General Chair, FG 2025 General Chair), and 12+ specialized workshops on human analysis. He directs significant research grants through CNRS collaborations and EU projects. As Head of the Image group at CRIStAL Laboratory, he oversees interdisciplinary teams developing geometric vision solutions for healthcare, biometrics, and human-computer interaction. Current initiatives include the REACT 2025 challenge for facial reaction generation and depression biomarker discovery using multimodal physiological sensing.

• Artificial Intelligence
• Robotics
• Natural Language Processing
• +۱۰ مورد دیگر

Iurii Krak is a Professor and Doctor of Phys.-Math. Sciences at the Taras Shevchenko National University of Kyiv , leading the Theoretical Cybernetics Department . He serves as a Senior Researcher Fellow (part-time) at the Glushkov Institute of Cybernetics and is a Corresponding Member in Informatics at the National Academy of Sciences of Ukraine . Education: M.Sc. in Cybernetics (1980), PhD (1987), Doctor of Phys.-Math. Sciences (1999) Roles: Visiting Professor at Lublin University of Technology (2008-2019), Chalmers University (2002), and others His research spans Artificial Intelligence, Robotics, Sign Language Recognition, and Medical Informatics , with a focus on 3D human modeling, emotional state analysis, and gesture synthesis. Recent work explores augmentative communication , big data analysis , and human-computer interfaces . Publications highlight mathematical optimization in robotics, sign language modeling, and intelligent decision-making systems. Scientific honors include membership in the National Academy of Sciences of Ukraine. Collaborations include institutions in Sweden, Poland, and Kazakhstan.

Rongen Sophia Zhangمشاهده پروفایل

استادیار

• Decentralized Governance
• Explainable AI and Decision-Making
• Generative AI Delegation
• +۵ مورد دیگر

Rongen Sophia Zhang is an Assistant Professor of Business Analytics in the Department of Information Systems and Business Analytics at Baylor University. A first-generation college graduate, she earned her PhD in Computer Information Systems from Georgia State University in 2022 and a BA from Harbin Institute of Technology in 2018. Academic Affiliation: Baylor University, Department of Information Systems and Business Analytics Education: PhD (Georgia State University) and BA (Harbin Institute of Technology) Her research focuses on how emerging technologies shape individual decision-making, with emphasis on: Decentralized governance in blockchain platforms Explainable AI (XAI) and algorithm aversion in healthcare Generative AI delegation and user engagement Technology-mediated interactions and emotional well-being Configurational analysis using fsQCA Her recent work explores blockchain governance configurations, AI explainability in medical contexts, and novel methods for multimodal classifier interpretability. Publications span journals like Information Systems Journal , Frontiers in Neuroinformatics , and ACM Transactions on Management Information Systems , with conditionally accepted papers at HICSS and ICIS conferences. Scientific honors include: Best Associate Editor, ICIS Best Reviewer, ICIS As an educator, she teaches Business Intelligence courses at undergraduate and graduate levels. She serves as a reviewer and associate editor for journals like MIS Quarterly and Information Systems Journal , and holds leadership roles in academic organizations such as the AIS Doctoral College.

Alisha Tolaniمشاهده پروفایل

استادیار بالینی

• Reproductive Endocrinology
• Infertility
• Perinatal Loss
• +۳ مورد دیگر

Alisha Tolani, MD, is a Clinical Assistant Professor at the University of California, San Francisco School of Medicine. She completed her MD at Stanford University School of Medicine in 2017, followed by an Obstetrics and Gynecology residency (2021) and a Reproductive Endocrinology and Infertility fellowship (2024). Her research focuses include Perinatal Loss and Expanding Fertility Care to Low-Resource Settings . Stanford University School of Medicine MD (2017) Stanford Obstetrics & Gynecology Residency (2021) UCSF Reproductive Endocrinology & Infertility Fellowship (2024) Dr. Tolani's work addresses critical gaps in reproductive health through: Metabolomic analysis of assisted reproductive technologies Geographic disparities in fertility care access Postpartum depression screening in cardiac patients Simulation-based training programs for low-resource obstetric care Her 15 most recent publications examine reproductive immunology, maternal cardiac conditions, and global fertility care delivery systems. Key trends include: Improving diagnostic accuracy in endometrial biopsies Developing multidisciplinary frameworks for high-risk pregnancies Advancing perinatal outcomes through standardized protocols Scientific recognition includes: ASRM Pilot & Exploratory Grant (2023) Clinical Excellence Award at Stanford (2020) Pacific Coast Reproductive Society Scholarship (2020) Multiple Stanford University honors (2007-2010) Dr. Tolani contributes to clinical education through: Simulation training program development Human trafficking awareness initiatives Reproductive health policy advocacy She maintains active collaborations with multidisciplinary teams at both Stanford and UCSF medical centers.

Laurence Jolivetمشاهده پروفایل

پژوهشگر

• Geographical Information Science
• Landscape Modeling
• Data Qualification
• +۴ مورد دیگر

Laurence Jolivet is a researcher at IGN (Institut national de l'information géographique et forestière) and member of the LASTIG (Laboratoire des Sciences et Technologies de l'Information Géographique) laboratory, affiliated with the STRUDEL and MEIG teams. She holds a PhD in Geography (2014) from Université Paris 1 Panthéon-Sorbonne and works on spatiotemporal analysis, landscape modeling, and human-wildlife interaction studies. Research Interests : Landscape description and modeling for fauna movement simulation (BD TOPO, RGE ALTI) Volunteered Geographic Information (VGI) qualification for land use monitoring Sensitive/perceptual mapping protocols for urban space analysis Multi-source data integration in urban ecosystem management Recent Article Trends focus on: Wildlife disturbance from recreational activities Multi-source land use classification workflows Tick bite risk modeling in peri-urban zones Citizens' Books analysis for policy input Deep learning applications in landscape dynamics Supervision : Co-supervisor of Martin Cubaud (PhD, 2022-ongoing): Land use classification via deep learning Supervisor of Colin Kerouanton (PhD, 2020): Hiker mobility analysis Key Projects : IntForOut (2024-2027) : Integrating multisource data for ecosystem monitoring under outdoor recreation pressure SOTIQUE (2024-2025) : Socio-ecological tick bite risk modeling LandSense (2016-2021) : Citizen observatory for land cover monitoring CHOUCAS (2017-2022) : Heterogeneous data integration for mountain rescue