جست‌وجوی استاد و پژوهشگر

• Cardiovascular Medicine
• Cardiomyopathy
• Inherited Cardiovascular Disease
• +۷ مورد دیگر

John Stendahl, MD, PhD, is an Assistant Professor of Medicine in the Department of Internal Medicine at Yale School of Medicine, specializing in Cardiovascular Medicine. He is a key member of the Cardiomyopathy & Inherited Cardiovascular Disease Program and affiliated with the Yale Biomedical Imaging Institute and the Yale Translational Research Imaging Center (Y-TRIC). His work integrates clinical cardiology with advanced imaging and translational research. Assistant Professor of Medicine (Cardiovascular Medicine), Yale School of Medicine Member, Cardiomyopathy & Inherited Cardiovascular Disease Program Affiliated Faculty, Yale Biomedical Imaging Institute Member, Yale Translational Research Imaging Center (Y-TRIC) Dr. Stendahl holds an MD from the University of Minnesota (2011) and a PhD in Materials Science and Engineering from Northwestern University (2005), with undergraduate training also from the University of Minnesota. His interdisciplinary background enables a unique approach to cardiovascular diagnostics and therapeutics. MD, University of Minnesota, 2011 PhD, Materials Science and Engineering, Northwestern University, 2005 BS, Materials Science and Engineering, University of Minnesota, 1999 His research focuses on hypertrophic cardiomyopathy (HCM), cardiovascular imaging, and inherited heart diseases. He employs advanced techniques such as SPECT, PET, CT, and molecular imaging to improve diagnosis and management. His work includes genetic analysis, risk stratification, and clinical trials for novel therapies. He is particularly interested in sex-specific outcomes, genotype-phenotype correlations, and the long-term impact of interventions like septal reduction. The analysis of his recent publications reveals a strong emphasis on clinical and translational research in HCM. His work leverages large registries such as the Sarcomeric Human Cardiomyopathy Registry (SHARE) to investigate risk factors, disease progression, and treatment outcomes. There is a clear trend toward integrating genetic data with imaging and clinical phenotypes to enable precision medicine approaches in cardiomyopathy. Dr. Stendahl has been recognized for his research with a Career Development Award from the National Heart, Lung, and Blood Institute (NHLBI) in 2022. Career Development Award, NHLBI, 2022 He actively contributes to academic service, having served as a reviewer for journals including the Journal of Nuclear Medicine , American Heart Journal , Nanomedicine , and Journal of Applied Physiology . His collaborative research network includes prominent Yale investigators such as Albert Sinusas, James Duncan, and Lawrence Staib, reflecting a strong interdisciplinary approach. He is also a member of the Janeway Society, highlighting his role as a physician-scientist at Yale. Dr. Stendahl is affiliated with multiple research teams and centers focused on cardiovascular innovation, including the Yale Biomedical Imaging Institute and Y-TRIC, where he contributes to the development and application of cutting-edge imaging technologies for heart disease.

Soon Haeng KANGمشاهده پروفایل

دانشیار

• Korean Linguistics
• Italian Linguistics
• Comparative Syntax
• +۹ مورد دیگر

Soon Haeng KANG is an Associate Professor in the Department of Asian and North African Studies at Ca' Foscari University of Venice, where he has held a permanent position since 2018. His academic work centers on Korean and Italian linguistics, with a focus on syntax, morphology, and comparative analysis between the two languages. He is actively involved in teaching, research, and expanding Korean language education in Italy. PhD in General Linguistics, Ca' Foscari University of Venice (2007–2007) Master's Degree in Italian Linguistics, Hankuk University of Foreign Studies (2000–2003) Bachelor's Degree in Italian Studies, Hankuk University of Foreign Studies (1993–2000) Visiting Student, Ca' Foscari University of Venice (2001–2002) Dr. Kang's research focuses on the structural aspects of Korean and Italian languages, particularly in adjective syntax, genitive constructions, plural markers, and noun phrase organization. He employs comparative and contrastive methodologies to analyze grammatical phenomena across Korean and Italian, contributing to both theoretical linguistics and applied language teaching. His work bridges East Asian and European linguistic traditions. His recent publications show a strong trend in Korean linguistic theory and pedagogy, with major 2024 monographs on Korean morphology and the verbal system. He has also published extensively on the expansion of Korean language education in Italy and the adaptation of teaching methods during the pandemic. His articles span topics from syntactic movement in Italian to the educational implications of Korean grammar, reflecting a dual expertise in both languages. Dr. Kang has received research funding from the National Research Foundation of Korea for multiple projects related to Italian syntax and Korean-Italian contrastive analysis. These grants supported postdoctoral research and academic development activities in South Korea. Post-doctoral fellow, Hankuk University of Foreign Studies (2009–2010, 2012–2013) Contract Professor of Italian, Hankuk University of Foreign Studies (2007–2018) Contract Professor of Italian, Sejong University (2008–2012) Collaborator and linguistic expert, Ca' Foscari University (2003–2005) He has contributed to the development of Korean studies in Italy through curriculum design, vocabulary textbooks, and institutional leadership. His work helps shape the academic landscape for Korean language education in Europe, particularly in Italy.

• Natural Language Generation
• Vision and Language Models
• Data Pruning
• +۸ مورد دیگر

Albert Gatt is a researcher at the University of Malta , with extensive contributions to Natural Language Generation (NLG) , Vision-and-Language (V&L) models , and evaluation practices in NLP . His work spans multimodal reasoning, data pruning efficiency, and reproducibility challenges in human evaluations. Key collaborations include studies on temporal grounding in image sequences (TempVS benchmark) and automated legal violation detection in cookie banners. Research highlights include bridging linguistic theory with computational models (e.g., VALSE benchmark for multimodal grounding) and improving generation quality through contrastive learning frameworks. Scientific awards are not explicitly mentioned in the provided texts. His work emphasizes rigor in automatic metric validation and cross-modal interpretability , particularly in multimodal model attention mechanisms and logical formula minimization for text generation.

• Machine Learning
• Computer Vision
• Natural Language Processing
• +۲ مورد دیگر

Chun-Liang Li is a Research Scientist at Apple MLR and an Affiliate Assistant Professor at the Allen School of Computer Science, University of Washington. He holds a Ph.D. in Machine Learning from Carnegie Mellon University (2014-2019) and a B.S./M.S. in Computer Science and Information Engineering from National Taiwan University (2008-2013). His research spans machine learning, computer vision, and natural language processing, with emphasis on representation learning, efficient model training, and multimodal understanding. Key focus areas include large language model optimization, contrastive learning techniques, document understanding systems, and domain adaptation methods. Recent publications demonstrate strong focus on LLM efficiency (dataset decomposition, distillation techniques), document AI (table reasoning, form extraction), and multimodal alignment (image-text retrieval, prefix conditioning). His work consistently appears in premier venues including NeurIPS, CVPR, ACL, and ICLR. Awards and Honors: IBM Ph.D. Fellowship (2018) Best student paper runner-up, IJCAI (2017) First Place in both tracks of KDD Cup (2011, 2013) He actively mentors students and collaborators, inviting contact for internship opportunities. Current industry-academic position bridges cutting-edge research with practical applications in machine learning systems.

Kate Frenchمشاهده پروفایل

دانشیار

• Educational Equity
• Urban Education
• Teacher Development
• +۵ مورد دیگر

Kate French is an Associate Professor of Education at Hope College , specializing in the intersections of power, privilege, and oppression in teacher development. She teaches courses such as Foundations of Education and Secondary Principles, with a focus on clinical experiences for urban education. Education: Dual Ph.D. in Educational Policy and K–12 Educational Administration, Michigan State University, 2017 M.Ed. in Educational Policy and Leadership, Southern Methodist University, 2011 B.S. in Biomedical Sciences, Lee Honors College of Western Michigan University, 2009 Research Interests: Dr. French investigates educational equity for marginalized groups, contrasts early-career and seasoned educators, and challenges systemic assumptions in teacher education. Her work emphasizes inclusive learning environments and sociocultural contexts. Publication Trends: Her recent work focuses on teacher evaluation instruments, social justice in urban education, and the sociocultural influences on early-career educators. She employs humanistic inquiry and critical theory frameworks. Advising & Leadership: Dr. French previously chaired Madonna University's teacher education program and served as a postdoctoral fellow at Wayne State University. She mentors preservice teachers but no student names are listed in the provided text.

Jiyoung Kimمشاهده پروفایل

مدرس ارشد

• Korean language and linguistics
• Korean language pedagogy
• Second language acquisition
• +۱ مورد دیگر

Jiyoung Kim serves as a Senior Lecturer in the Department of East Asian Languages and Cultures at Indiana University Bloomington's Hamilton Lugar School of Global and International Studies. She teaches elementary and third-year Korean courses (EALC KOR 101/301) and holds a PhD in Linguistics from the University of Hawaii at Manoa (2014), specializing in Korean language structures and pedagogy. Her academic background includes: PhD, University of Hawaii at Manoa, 2014 Dr. Kim's research centers on Korean grammatical phenomena—including imperfective aspect markers and modal verbs—and their acquisition by second language learners. She develops project-based curriculum frameworks for college-level Korean while integrating visual culture into pedagogical approaches, bridging theoretical linguistics with classroom practice to address learner challenges in morphosyntax and discourse. Publication analysis reveals consistent focus on Korean linguistic structures within acquisition and discourse contexts, with evolving emphasis from grammatical analysis (2009-2013) toward curriculum innovation through project-based learning (2015), demonstrating applied scholarship for Korean language education. No scientific awards are documented in the source material. Details regarding student advising, research grants, laboratory facilities, or collaborative research teams are unavailable in the provided documentation.

Musa KAYAمشاهده پروفایل

دانشیار

• Turkish Language Teaching
• Foreign Language Acquisition
• Educational Sciences
• +۴ مورد دیگر

Musa KAYA is an Associate Professor at the Department of Turkish Education within the Faculty of Education at Bayburt University. His academic work focuses on Turkish language teaching, foreign language acquisition, and multicultural education. He actively contributes to curriculum development and analysis, particularly in alignment with European language standards. Research Interests : Turkish as a foreign language, language transfer phenomena, text simplification, cultural integration, value education, and reading comprehension. Article Trends : Recent publications examine Tunisian students' attitudes toward learning Turkish, comparative analyses of language programs, text complexity in Turkish instruction, and integration of cultural values through literature. Contact : Email - musakaya@bayburt.edu.tr | Phone - (458) 333-2033

Craig Chambersمشاهده پروفایل

استاد

• Human Communication
• Cognitive Science
• Psycholinguistics
• +۲ مورد دیگر

Craig Chambers is a Professor and Department Chair in the University of Toronto Department of Psychology. His research focuses on human communication , cognitive science , and psycholinguistics , particularly language processing across the lifespan and communication with social robots . Education: B.A. in Linguistics, York University M.A. in Linguistics, University of Toronto M.A. in Brain & Cognitive Sciences, University of Rochester Ph.D. in Brain & Cognitive Sciences and Linguistics, University of Rochester His lab investigates how speakers balance verbal and non-verbal information (gestures, intonation, environmental context) to convey meaning, and how listeners integrate these cues during comprehension. Recent studies explore pragmatic inferences , lexical competition , age-related differences in language processing, and social robotics applications . Key article trends include child language acquisition , speech perception in aging populations, multimodal communication , and language prediction mechanisms . Lab activities blend rigorous scientific inquiry with playful experimentation, including initiatives like "The PAL LAB PLAYS!"

Francesco Leofanteمشاهده پروفایل

پژوهشگر ارشد

• Explainable AI
• Counterfactual Explanations
• Robustness
• +۳ مورد دیگر

Francesco Leofante is a Research Fellow at Imperial College London , affiliated with the Centre for Explainable AI . His work focuses on Explainable AI (XAI) , particularly counterfactual explanations with formal robustness guarantees against perturbations. Imperial College Research Fellowship DAAD AINet Fellowship (Safety and Security in AI) Imperial PFDC Supporting Research Staff and Students Award 2023 Research Interests center on Explainable AI , emphasizing counterfactual explanations , robustness , model multiplicity , and formal verification in critical systems like energy and aviation. His work bridges AI , formal methods , and human-AI collaboration . Publications include studies on robust counterfactual explanations , parametric ReLUs for verification, and multi-agent systems with formal guarantees. These appear in top venues like AAAI , KR , IJCAI , and AAMAS , often addressing AI safety and trustworthy systems . Scientific Awards include the Imperial PFDC Supporting Research Staff and Students Award 2023 , DAAD AINet Fellowship , and Imperial College Research Fellowship . He also contributes to workshops and program committees at conferences like AAAI, KR, and IJCAI. Future Work includes expanding robust XAI into critical infrastructure systems (energy, aviation) and developing tools like OMTPlan for AI planning and verification .

Jeffrey Steeleمشاهده پروفایل

استاد

• Second Language Acquisition
• Laboratory Phonology
• Language Assessment
• +۳ مورد دیگر

Jeffrey Steele is a Professor in French Studies at the University of Toronto. His research focuses on second language acquisition, laboratory phonology, and bilingual literacy. He explores how phonological and phonetic factors influence language learning, particularly the acquisition of French and Spanish segmental and prosodic features by Mandarin, Japanese, and English speakers. Steele also investigates the role of phonological awareness in bilingual children's literacy development. PhD in Linguistics, McGill University MA in French Linguistics, Queen’s University BA Hons in French, University of Manitoba Steele’s work employs electropalatography (EPG) to analyze articulatory timing, assimilation, and cluster simplification in native and non-native speech. His publications address topics like cross-linguistic influence on coda voicing, syllable position effects, and the impact of phonetic input variability on L2 learning. Recent studies highlight gradient and categorical effects in bilingual phonology, phonological licensing asymmetries, and prosodic prominence acquisition. He co-developed the University of Toronto Test of French and maintains the Romance Phonetics Database (2004–Present). SSHRC Insight Development Grant (2022–2027) on Reading Comprehension in French Immersion Learners Steele teaches courses in French language skills, linguistic analysis, and individual differences in language acquisition. His collaborations with researchers like Colantoni and Kochetov bridge theoretical linguistics and applied pedagogy.

Jeff Lichtmanمشاهده پروفایل

استاد

• Connectomics
• Neural Circuit Mapping
• Developmental Neuroscience
• +۲ مورد دیگر

Jeff Lichtman serves as the Jeremy R. Knowles Professor of Molecular and Cellular Biology and Santiago Ramón y Cajal Professor of Arts and Sciences at Harvard University, where he leads research within the Department of Molecular and Cellular Biology in the Faculty of Arts and Sciences. His laboratory focuses on the physical basis of long-lasting memory and experience-driven neural circuit restructuring through advanced connectomic approaches. Dr. Lichtman's research program centers on connectomics and neural circuit development , utilizing transgenic Brainbow models for in vivo visualization and automated serial electron microscopy for nanometer-resolution mapping. His lab investigates synaptic competition during mammalian development, circuit rearrangement in peripheral nervous systems, and the structural underpinnings of memory formation. Key research areas include cellular and molecular neuroscience with emphasis on developmental processes, synaptic connectivity dynamics, and experience-dependent circuit refinement. Analysis of his 2021-2025 publications reveals dominant methodological innovation in machine learning-guided microscopy (e.g., SmartEM) and correlative imaging techniques , with expanding applications across model systems including zebrafish, octopus, and human tissue. Recent work increasingly addresses Alzheimer's disease pathology within connectomic frameworks while maintaining core focus on developmental circuit formation. The Lichtman Lab maintains active development of high-throughput tools for neural circuit mapping, including Fishexplorer for zebrafish circuit dissection and large-scale human cerebral cortex reconstructions, with ongoing projects examining both peripheral and central nervous system connectivity.

• Pharmacokinetics
• Transplantation
• Immunosuppressive Drugs
• +۶ مورد دیگر

Anders Åsberg is a Professor at the Department of Pharmacy, University of Oslo, with a focus on pharmacokinetics and its application in organ transplant recipients. He leads the Section of Pharmacology and Pharmaceutical Biosciences and is actively involved in clinical studies related to immunosuppressive drug therapy. Current affiliation: Professor II, University of Oslo Previous roles: Managing Director, Renal Physiology Laboratory (2013–present); Medical Director, Roche Norge AS (2000–2003) Research Interests : Pharmacokinetics of immunosuppressive drugs Drug interactions in transplantation Role of transporters in drug disposition Population modeling for therapeutic drug monitoring Clinical trials in transplant recipients Effects of metabolic changes (e.g., gastric bypass) on drug metabolism Scientific Awards : Best Young Investigator, European Renal Association (2001) Collaborations span institutions such as the Clinical Pharmacokinetic Research Laboratory at the University of Rhode Island and the Laboratory of Applied Pharmacokinetics at the University of Southern California. His work frequently addresses the interplay between drug therapy, patient physiology, and long-term outcomes in kidney transplantation.

Antonio Calà Lesinaمشاهده پروفایل

استاد

• Computational Electromagnetics
• Nanophotonics
• Metamaterials
• +۷ مورد دیگر

Antonio Calà Lesina is a Full Professor in Computational Photonics at the Leibniz University Hannover , leading research at the Hannover Centre for Optical Technologies . His academic journey includes a PhD in Information and Communication Technology from the University of Trento (2013), followed by postdoctoral and associate professor roles at the University of Ottawa (2013–2020). His research spans Nanophotonics , Metamaterials , and Plasmonics , focusing on inverse design, topology optimization, and dynamic control of optical systems via multiphysics simulations. Education : PhD (University of Trento, 2013); MSc in Telecommunications Engineering (University of Catania); BSc in Electronics Engineering (University of Catania) Current Position : Full Professor (Leibniz University Hannover, 2020–2025) His work explores Light-Matter Interactions and Nanostructures , with recent publications on anapole states , multiresonant metasurfaces , and hyperbolic metamaterials . He employs Finite-Difference Time-Domain (FDTD) simulations and deep learning for inverse design in nanophotonics. Collaborations include institutions like the University of Ottawa and research centers in Europe, aligning with the EULiST alliance . Despite no explicit awards mentioned, his contributions to optical beam steering , nonlinear metasurfaces , and machine learning integration highlight his impact in the field.

Sukalpa Chandaمشاهده پروفایل

دانشیار

• Machine Learning
• Zero-Shot Learning
• One-Shot Learning
• +۷ مورد دیگر

Sukalpa Chanda is an Associate Professor at the Department of Computer Science and Communication, Halden University College. His research focuses on Machine Learning with applications to Document Image Analysis, Computer Vision, and Video Image Analysis, including advanced methods like Zero-Shot Learning, Deep Learning, and Transformer Networks. PhD in Computer Science from NTNU Appointments: Postdoctoral Researcher at Uppsala University (2018-2019) and Groningen University (2016-2018) Research Interests: Chanda specializes in Zero-Shot and One-Shot Learning for document and image analysis, with applications in handwriting recognition, face generation, and biomedical imaging. His work bridges theoretical machine learning with practical implementations in cultural heritage preservation and healthcare diagnostics. Scientific Collaboration: He collaborates with institutions like Indian Institute of Technology (Pallakad/Patna) and leads the Hugin Munin Project under The Digital Society research priority area. His team includes Master’s students and research assistants working on Transformer Networks and generative models. Key Publications: Recent works include frameworks for zero-shot action recognition (T2L, 2025), Nordic manuscript writer identification (2023), and advanced medical image segmentation networks (PAANet, 2021). His research spans document analysis, deep metric learning, and biomedical applications.

• Interactive AI
• Human-Centered AI
• Fairness in AI
• +۳ مورد دیگر

Elizabeth M. Daly is a Research Scientist at IBM Research Laboratory, Dublin, and an Adjunct Assistant Professor at Trinity College Dublin's School of Computer Science and Statistics. Her work focuses on interactive AI , human-centered design , and fairness in algorithmic systems . She contributes to AI governance and LLM safeguarding through projects like AutoFair and Granite Guardian. Ph.D. in Computer Science (2007), Trinity College Dublin Thesis: Social Network Analysis for Routing in Disconnected Delay-Tolerant MANETs Her research interests span: Interactive AI : Facilitating AI-human negotiation for common objectives Trustworthy AI : Addressing fairness, accountability, and transparency in industrial applications Explainable AI : Developing tools like AIMEE for model exploration and editing She serves on the program committees of top conferences (RecSys, IUI, WWW, UMAP, ICWSM) and the Royal Irish Academy’s committee on Engineering and Computer Science. Notable scientific award: ACM Distinguished Member . Projects: AutoFair : Human-compatible automation of fairness in AI AIMEE : AI model explorer and editor tool Usage Governance Advisor : Translating AI intent into governance frameworks She leads the Interactive AI Group at IBM Research Europe - Ireland.