جست‌وجوی استاد و پژوهشگر

Bing Liuمشاهده پروفایل

استاد مدعو

• Natural Language Processing
• Large Language Models
• Dialogue Systems
• +۴ مورد دیگر

Bing Liu serves as Director of Applied Research at Scale AI and Adjunct Professor in the Computer Science and Engineering department at the University of California, Santa Cruz. Previously, he held leadership roles at Meta (GenAI and Reality Labs), Google Research, and Capio.ai (acquired by Twilio), with expertise spanning generative AI, NLP, and spoken dialogue systems. His educational background includes: Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University B.Eng in Electrical and Electronic Engineering (First Class Honors) from Nanyang Technological University, Singapore Exchange studies at KTH Royal Institute of Technology, Sweden Liu's research focuses on advancing large language models, dialogue systems, and reinforcement learning for conversational AI. His work bridges theoretical innovation with industrial-scale applications, particularly in zero-shot learning, multilingual capabilities, and evaluation frameworks for generative AI. He has pioneered techniques in dialogue state tracking, knowledge-enriched task-oriented systems, and continual learning to address catastrophic forgetting in neural dialogue models. Analysis of his 15 most recent publications reveals a clear trajectory toward industrial-scale generative AI: early work (2018-2021) established foundational methods in task-oriented dialogue systems, while recent publications (2022-2024) focus on LLM post-training, multimodal integration, and evaluation benchmarks like Humanity's Last Exam. Key thematic clusters include cross-lingual transfer, knowledge grounding in dialogue, and robust evaluation frameworks for frontier models. As an educator, Liu guides graduate research at UC Santa Cruz in LLM and multimodal AI while serving in critical conference roles including Publication Chair for ACL 2024 and Area Chair for ACL 2023's Large Language Models track. His industry leadership includes building Scale AI's 40+ member research team and driving Meta's Llama3 development, managing multimillion-dollar data roadmaps that scaled the Meta AI Assistant to 700M MAU. Liu directs Scale AI's applied research lab focused on GenAI data and evaluation, having previously built Meta's NLU team for AR/VR voice assistants deployed across Portal, Oculus, and Ray-Ban Smart Glasses. His current work centers on creating evaluation leaderboards adopted by top AI labs and developing the data engine for next-generation generative models.

Joseph B. Zwischenbergerمشاهده پروفایل

استاد

• Cardiothoracic Surgery
• Extracorporeal Membrane Oxygenation (ECMO)
• Cardiovascular Research
• +۳ مورد دیگر

Joseph B. Zwischenberger, MD, is a Professor of Surgery and Pediatrics at the University of Kentucky College of Medicine , with affiliations to the Saha Cardiovascular Research Center , CVRC - Affiliated Faculty , and the Surgery/Cardiac MD/PhD Program Mentor . His clinical and research focus spans cardiothoracic surgery , ECMO technology , and critical care innovations , particularly in artificial organ development and postoperative pain management . Education: MD from University of Kentucky Residency: University of Michigan, Ann Arbor Fellowships: Cardiac Division (NIH), Cardiothoracic Surgery, and Critical Care (University of Michigan) Certifications: American Board of General Surgery (Vascular and Thoracic Surgery) His research explores ECMO program development , respiratory failure mechanisms , and congenital heart defect support systems , emphasizing multidisciplinary collaboration in medical device innovation and pediatric cardiovascular care . Key trends include postoperative critical care protocols , tracheal replacement technologies , and surgical education reform to enhance resident autonomy. Notable scientific contributions include leadership in JACC Scientific Expert Panel on ECMO and foundational work on transhiatal esophagectomy for esophageal carcinoma. His 2023 Annals of Thoracic Surgery article addresses ICU governance models, while his 2024 Ann Thorac Surg Short Rep case study highlights device complication analysis. As an MD/PhD program mentor , he trains future physician-scientists and collaborates with the Saha Cardiovascular Research Center on translational studies. His work has shaped thoracic surgical protocols, including epidural placement guidelines and Fontan procedure optimization .

• Data Mining
• Social Network Analysis
• Machine Learning
• +۳ مورد دیگر

Jaideep Srivastava is a Professor affiliated with Qatar Foundation (Doha, Qatar), University of Minnesota (Minneapolis, USA), and holds a PhD from University of California Berkeley. His research spans data mining, social network analysis, time series modeling, and health informatics. Recent work focuses on clinical deterioration prediction, sleep research, and computational analysis of pandemic behaviors. Key contributions in clustering algorithms and graph neural networks Active in multimodal learning and misinformation detection His publications from 2024-2022 demonstrate expertise in hierarchical clustering , large language model applications , and health data analytics . Articles often integrate machine learning , social network dynamics , and clinical monitoring systems . Current projects involve Covid-19 in-hospital mortality prediction , virtual influencer analysis , and low-light imaging techniques . Collaborations span institutions in Qatar, USA, and India with applications in urban mobility and precision medicine.

• Computational Neuroscience
• Robotics
• Machine Learning
• +۳ مورد دیگر

Florentin Wörgötter is a faculty member at the Department for Computational Neuroscience , Georg August University of Göttingen, Germany. His research bridges robotics , computational neuroscience , and machine learning , focusing on action prediction, neural networks, and human-robot interaction. Key Research Areas : Action segmentation, semantic decomposition of manipulation sequences, 3D object reconstruction, and sensor fusion for infant movement classification. Recent Trends : Combining task-dependent learning with optimal path search, using foundation models for graph-based action recognition, and improving CNN interpretability through influence functions. He collaborates extensively with researchers like Minija Tamosiunaite , Tomas Kulvicius , and Poramate Manoonpong , contributing to journals such as NeuroImage , Robotics and Autonomous Systems , and IEEE Transactions on Neural Networks . His work often integrates deep learning , semantic reasoning , and biologically inspired models for robotic applications.

Judith Laisterمشاهده پروفایل

دانشیار

• Urban Anthropology
• Aesthetic/Visual Anthropology
• Multimodal Anthropology
• +۵ مورد دیگر

Associate Professor Judith Laister at the University of Graz's Institute for Cultural Anthropology and European Ethnology explores urban anthropology through aesthetic and multimodal frameworks. Her work interrogates intersections between art and science, focusing on participatory art in public spaces, gender justice, and anthropology in the Anthropocene. She leads the ELF - Elisabeth List Fellowship Program and co-founded the nice* network for gender-responsive urban interventions. Key research themes: Urban place-making, representational critique, relational art, and translational concepts Affiliated with initiatives like Green Belt Graz and We Earthlings! study projects Her teaching includes foundational courses in European Ethnology and urban anthropology, alongside roles in curriculum development and equal opportunities advocacy. Publications often bridge art theory and ethnographic practice, emphasizing experimental methodologies and public engagement.

Martin Cunneenمشاهده پروفایل

دانشیار

• AI Governance
• Philosophy of AI
• Language and AI
• +۱۰ مورد دیگر

Dr. Martin Cunneen is an Associate Professor at the University of Limerick's Kemmy Business School, affiliated with the Data-Driven Computer Engineering Research Centre and Lero – the Irish Software Research Centre. He leads the AI-ERA (Ethics, Regulation, Accountability) Research Group and serves as Principal Investigator for the Horizon Europe-funded XTREME project (2024–2027), focusing on mixed reality technologies for art and culture. Active in AI governance, ethics, and interdisciplinary research Supervises 14 postgraduate students across 7 thematic areas Led €1.2 million in research funding in the past year His research spans AI/data governance , climate risk mitigation , extended reality , health technology , autonomous vehicles , and philosophy of AI , integrating technical and social science perspectives under the UN SDG framework. Scientific awards include: KBS Faculty Teaching Excellence Award (2022) Teaching interests include AI governance, explainable AI, data ethics, and sustainable AI practices. He actively participates in EU Horizon projects and collaborates with Science Foundation Ireland (SFI) and international research consortia. Labs: XTREME Mixed Reality Research Living Lab at Kemmy Business School (2024)

Nicholas D Schiffمشاهده پروفایل

استاد

• Disorders of Consciousness
• Traumatic Brain Injury
• Deep Brain Stimulation
• +۵ مورد دیگر

Nicholas D Schiff is a Professor of Medical Ethics in Medicine, Professor of Neuroscience at the Brain and Mind Research Institute, and Professor of Neurology at Weill Cornell Medical College, holding the Jerold B. Katz Professorship in Neurology and Neuroscience. His academic appointments span multiple departments reflecting his interdisciplinary work at the intersection of neurology, neuroscience, and medical ethics. Dr. Schiff completed his M.D. at Cornell University Medical College in 1992 and earned his B.A. from Stanford University in 1987. His educational background established the foundation for his career bridging clinical neurology with neuroscience research. His research focuses on disorders of consciousness, traumatic brain injury mechanisms and treatments, deep brain stimulation techniques, thalamocortical function, and neuroethical considerations in severe brain injury. Schiff pioneered work on cognitive motor dissociation and developed the anterior forebrain mesocircuit model to explain disorders of consciousness. His laboratory investigates neural mechanisms of recovery using multimodal approaches including EEG, fMRI, and direct neural recordings. Analysis of his recent publications reveals a strong emphasis on developing objective biomarkers for consciousness assessment, refining deep brain stimulation protocols for traumatic brain injury, and translating basic neuroscience discoveries into clinical applications. His work increasingly incorporates multimodal assessment techniques and focuses on both mechanistic understanding and practical clinical interventions. Principal Investigator for JSMF Covid-19 Consortium for Recovery of Consciousness (2020-2025) Principal Investigator Subaward for Thalamic stimulation to prevent impaired consciousness in epilepsy (2019-2025) Co-Investigator for Central thalamic deep brain stimulation to regulate arousal and cognition (2020-2025) Key Personnel for NIH 7T MRI System grant (2021-2025) Dr. Schiff maintains active collaborations through the Central Thalamic Deep Brain Stimulation Trial and serves on scientific advisory boards including QuantalX Neuroscience Ltd. His laboratory at the Brain and Mind Research Institute integrates basic neuroscience with clinical applications, focusing particularly on thalamic function and consciousness regulation.

Yajie (Kevin) Liangمشاهده پروفایل

استادیار

• Neural stem cell therapy
• Two-photon imaging
• Neurogenesis
• +۵ مورد دیگر

Yajie (Kevin) Liang, MB, PhD, is an Assistant Professor in the Department of Diagnostic Radiology and Nuclear Medicine at the University of Maryland School of Medicine. He is a Principal Investigator at the Center for Advanced Imaging Research (CAIR) and a member of the Marlene and Stewart Greenebaum Comprehensive Cancer Center. His interdisciplinary research bridges neuroscience, imaging technology, and regenerative medicine. Education and Training: 1998–2003: Baccalaureate in Medicine, 3rd Military Medical University, Chongqing, China 2003–2009: PhD in Neurobiology, 3rd Military Medical University, Chongqing, China 2010–2012: Postdoc, Department of Radiology, Johns Hopkins University 2012–2015: Postdoc, Institute of Physiology, Tübingen University, Germany Research Focus: Dr. Liang’s laboratory develops and applies advanced in vivo imaging techniques, particularly two-photon and three-photon microscopy, to study neural stem cell therapy, stroke recovery, and neurodegeneration. His team investigates how transplanted neural cells integrate into host brain circuits and how toxic protein aggregates, such as α-synuclein, propagate in dementia models. Current Projects: Long-term tracking of single neural stem cells in stroke models Nanobody-based chemogenetic probes for α-synuclein strain imaging Smart multiphoton imaging systems for real-time cellular interrogation 3D-printed microinjection needle arrays for precise brain delivery Grants & Funding: NIA: “Shedding Light on Functional Heterogeneity of Dementia-related Alpha-synuclein Strains” ($463,124, 2022–2025) Maryland Stem Cell Research Fund: “Smart Intravital Multiphoton Imaging iPSC-derived Cells” ($345,000, 2024–2026) NIMH subcontract: “3D Microprinting-Enabled Microinjection Needle Arrays” ($88,295, 2023–2025) Total active funding: $896,419 Scientific Awards: Young Investigator Award, National Natural Science Foundation of China (2009) Outstanding Doctoral Thesis, Chongqing City (2010) Fortune Award for Junior Investigators, Tübingen University (2013) Dr. Liang is an active member of the Society for Neuroscience, Society for Image Guided Neurointerventions, and BioImaging North America. His work has been featured in high-impact journals including Nature Methods , Cell Research , and Biomaterials .

Vytautas Čyrasمشاهده پروفایل

دانشیار

• Legal informatics
• Artificial intelligence and law
• Conceptualisation
• +۷ مورد دیگر

Dr. Vytautas Čyras serves as an Associate Professor at Vilnius University's Faculty of Mathematics and Informatics, specifically within the Institute of Computer Science and Department of Software Engineering. With over three decades of academic experience since 1984, he bridges computer science and legal theory through groundbreaking interdisciplinary research. Education: Master's in Applied Mathematics (Computer Science) from Vilnius University (1979) Doctorate from Moscow State University's Faculty of Computational Mathematics and Cybernetics (1985) Second Master's in Law from Vilnius University and German Law Centre (2007) Dr. Čyras' research spans legal informatics, information systems, and computer science. His primary focus includes artificial intelligence and law, regulatory compliance, legal requirements, and pioneering work in legal visualization. His Structural Blanks approach to programming with recurrences demonstrates deep expertise in both foundational computer science and legal applications. His research explores how visual and multisensory approaches can transform legal reasoning and compliance in digital environments. His publication trajectory reveals an evolution from technical computer science topics toward sophisticated legal informatics applications. Recent work emphasizes multisensory legal machines, legal visualization frameworks, and the integration of AI with legal reasoning systems. He has made significant contributions to understanding how legal norms can be transformed into operational rules for virtual environments and digital governance systems. Professional Activities: Active participant and organizer of major legal informatics conferences including IRIS, Baltic DB&IS, and EGOVIS Contributor to European Framework Programme projects including VirtualLife and SKY-Scanner Longstanding member of the Lithuanian Computer Society and its Intellectics Section Dr. Čyras teaches courses including Artificial Intelligence, Knowledge Representation, and Human-Computer Interaction. His interdisciplinary background enables him to bridge theoretical legal concepts with practical applications in regulatory compliance systems and legal technology development.

Rohit Singhمشاهده پروفایل

استادیار

• Computational Biology
• Machine Learning
• Single-Cell Genomics
• +۴ مورد دیگر

Rohit Singh is an Assistant Professor at Duke University with appointments in the Departments of Biostatistics & Bioinformatics, Cell Biology, Computer Science, and Electrical and Computer Engineering. He is a member of the Duke Cancer Institute and the Division of Integrative Genomics. Academic Rank : Assistant Professor Departments : Biostatistics & Bioinformatics, Cell Biology, Computer Science, Electrical and Computer Engineering University Affiliations : Duke Cancer Institute, Division of Integrative Genomics His research focuses on computational biology, machine learning for drug discovery, and decoding disease mechanisms through single-cell genomics and protein language models. Current projects include SAME, Velorama, Raygun, and Allo-Allo. Recent publications span single-cell analysis, protein language models, and causal inference. He develops tools like Schema , D-SCRIPT , and Sceodesic . Grants : NIAID, Chan Zuckerberg Initiative, Foundation for Prader-Willi Research Awards : MIT Sprowls Award, Stanford Stephenson Award, RECOMB Test of Time Award He advises students in computational biology and has contributed to patents in protein interaction modeling and viral detection. The lab welcomes postdocs, rotation students, and collaborators.

Sasan Matinfarمشاهده پروفایل

پژوهشگر

• Medical Sonification
• Sonic Interaction Design
• Extended Reality (XR)
• +۴ مورد دیگر

Sasan Matinfar is a research scientist at the Technical University of Munich (TUM), affiliated with the Chair of Computer Aided Medical Procedures (Prof. Navab) and the Munich Center for Machine Learning (MCML). He serves as scientific staff at Rechts der Isar Hospital, developing XR and sonification systems for surgical environments since 2020. His educational background includes: Master’s and Bachelor’s in Computer Science, Ludwig Maximilian University of Munich (LMU) Musicology, Franz Liszt University of Music, Weimar Piano Interpretation, Art University of Tehran Matinfar pioneers medical sonification and multisensory XR, creating auditory interfaces that convert tissue properties into sound for surgical guidance. His work in user-centered design produces clinically viable tools like the Ocular Stethoscope for retinal procedures and physics-based BioSonix frameworks, merging computer vision with perceptual audio engineering to enhance intraoperative precision without visual overload. Analysis of his 12 recent publications (2017-2025) reveals an evolving research arc from foundational surgical soundtracks to sophisticated context-aware sonification. Current work integrates generative AI with real-time tissue deformation modeling, focusing on multimodal frameworks where auditory feedback complements visual navigation in complex surgeries like cardiac interventions and retinal peeling. Key recognitions include: The Data Sonification Award (2025) MICCAI 2023 Best Paper Nominee (top 3% of submissions) MICCAI Young Scientist Award (2017, top 2% of papers) As an educator, Matinfar mentors students through TUM courses including Medical Augmented Reality (WS 2025/26) and Surgical Robotics, while co-organizing the Medical Augmented Reality Summer School and IEEE ISMAR 2025’s MIX Workshop. His patented technologies emerge from collaborations with Politecnico di Milano, TU Dresden’s CeTI, and Balgrist Hospital Zurich, securing interdisciplinary grants in surgical data science. Matinfar operates within TUM’s NARVIS Lab for medical image analysis and RobUSt for robotics-ultrasound integration, leveraging the German Heart Center Munich (DHM) infrastructure to validate XR systems in live surgical workflows and advance vision-language models for intraoperative decision support.

Matthias Springsteinمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• Multimedia Information Retrieval
• +۵ مورد دیگر

Matthias Springstein is a researcher at the Technical Information Library (TIB), which is affiliated with Leibniz University Hannover. He is part of the Visual Analytics research group within TIB's Research & Development department, focusing on advanced computer vision and multimedia information retrieval techniques. His research interests span multiple areas of artificial intelligence with emphasis on computer vision applications. Springstein specializes in web-supervised learning for visual concepts, incremental learning approaches, and methods to minimize manual labeling efforts for training data. His work bridges theoretical machine learning with practical applications in digital humanities, particularly in art-historical image analysis and film/video studies. His publication record shows a consistent focus on multimodal analysis, with recent work exploring knowledge graphs for image classification, large-scale hierarchical classification of art-historical images, and computational tools for film analysis. The research demonstrates progression from foundational work in image-text relations and depth estimation toward increasingly sophisticated applications in cultural heritage and scholarly media analysis. Notable achievements include receiving the Best Paper Award at the International Conference on Multimedia Retrieval (ICMR) in 2019 for his work on semantic image-text relations. Springstein has developed TIB AV-Analytics, a computational platform for scholarly video analysis that has been presented at multiple major conferences (SIGIR 2023, SCSMI 2024), indicating significant impact in both the information retrieval and film studies communities.

• Age-Related Macular Degeneration
• Diabetic Retinopathy
• Retinal Imaging
• +۴ مورد دیگر

Dimitra Skondra, MD, PhD, is a Professor at the University of Chicago's Department of Ophthalmology and Visual Science, specializing in vitreoretinal diseases. A board-certified retina specialist, she focuses on surgical and medical treatments for conditions including diabetic retinopathy, retinal detachment, and age-related macular degeneration (AMD). Her clinical expertise is complemented by active research in retinal imaging, gut microbiome interactions with ocular health, and therapeutic innovations. Education: Fellowship in Vitreoretinal Surgery, Harvard Medical School (2013) Residency in Ophthalmology, Weill Cornell Medical College (2011) PhD/Postdoctoral Research, University of Crete Medical School (2007) MD, University of Crete Medical School (2001) Research Focus: Dr. Skondra leads translational studies investigating the gut-retina axis in AMD pathogenesis, metformin's protective effects against retinal degeneration, and advanced imaging for early disease detection. Her work integrates microbiology, pharmacology, and epidemiology to develop targeted interventions. Publication Trends: Recent articles emphasize metformin's role in AMD prevention, racial disparities in retinal vascular health, and non-surgical treatments for macular holes. Her research consistently bridges clinical practice with molecular mechanisms, particularly in microbiome-related therapies. Awards: Retina Society Raymond Margherio Award (2013) Harvard/Alcon Clinical Research Scholar Award (2013) ARVO/Alcon Early Career Clinician Scientist Award (2006) Knights Templar Eye Foundation Award (2006) Dr. Skondra collaborates with multidisciplinary teams to advance retinal disease management, though specific lab/student details are undisclosed in the source text.

Haohan Wangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Computational Biology
• Healthcare Applications
• +۵ مورد دیگر

Haohan Wang is an Assistant Professor at the University of Illinois Urbana-Champaign's School of Information Sciences, with affiliations to the Carl R. Woese Institute for Genomic Biology and the National Center for Supercomputing Applications. His research focuses on developing trustworthy machine learning methods for computational biology and healthcare applications , emphasizing robustness , causality , and interpretability in vision-based models. Recent research trends in his work include: Large Language Model interactions with biomedical challenges (GenoAgent, GenoTex) Adversarial security in language and vision models (Guard, Jailbreakzoo) Genomic data analysis through robust machine learning frameworks (Precision Lasso, Kernel Mixed Models) Interactive toolkits like Robustar for data annotation and model training Scientific awards include recognition as Baidu's Top 50 AI+X Rising Young Scholars (2022), Best Paper Honorable Mention at WSDM 2023, and Broad Institute's Next Generation status (2019). Current projects explore AI-made scientists for biomedical discovery and Robustar development for GUI-based robust vision learning.

• Language Assessment
• L2 Writing Assessment
• Assessment Literacy
• +۴ مورد دیگر

Anthony Green is a Professor of Language Assessment and Director of the Centre for Research in English Language Learning and Assessment (CRELLA) at the University of Bedfordshire. He has over 15 years of leadership in CRELLA and extensive experience in test development, validation, and educational research. Research Interests: Assessment of written language, washback effects, CEFR alignment, and relationships between assessment, learning, and teaching Professional Roles: Fellow of the Academy of Social Sciences (2023), former ILTA President (2015-16), ALTE Quality Management Working Group co-chair Editorial Service: Language Testing, Assessing Writing, Language Assessment Quarterly, and other journals Contact: tony.green@beds.ac.uk | +44 (0)1582 489086 His research focuses on how language assessment influences pedagogy, with particular emphasis on writing evaluation and the ecological impacts of testing frameworks. Current supervision areas include washback effects, CEFR-aligned assessments, and reading/writing test development. Recent publications examine test design trends, washback theories, and practical applications in language assessment. He has supervised 13 PhD students to completion and currently mentors three active researchers.