جست‌وجوی استاد و پژوهشگر

Zhaozheng Yinمشاهده پروفایل

دانشیار

• Biomedical Image Analysis
• Computer Vision
• Machine Learning
• +۲ مورد دیگر

Zhaozheng Yin is an Associate Professor in the Department of Biomedical Informatics and Department of Computer Science at Stony Brook University, affiliated with the College of Engineering and Applied Sciences. His research focuses on biomedical image analysis, computer vision, machine learning, and human-robot collaboration in smart manufacturing contexts. Ph.D. in Computer Science and Engineering from Pennsylvania State University (2009) M.S. in Electrical and Computer Engineering from University of Wisconsin-Madison B.S. in Automation from Tsinghua University Active in advancing microscopy image analysis through novel algorithmic approaches, Dr. Yin's work bridges theoretical computer science with practical applications in healthcare and industrial automation. His research emphasizes: Intelligent human-robot collaboration systems Cyber-physical sensing and augmented reality for manufacturing Medical image segmentation and classification techniques Temporal action localization and counting algorithms His publications demonstrate expertise in domain adaptation, vision-language integration, and graph-based modeling. Grant-funded projects include NSF CAREER support for microscopy analysis and NRI/CPS grants for collaborative robotics research. Best Doctoral Spotlight Award, CVPR 2009 Young Scientist Awards at MICCAI (2010-2015) NSF CAREER Award recipient (2014) Best Paper Awards at CVPR workshop (2015) and IISE (2018)

Arkadiev Peterمشاهده پروفایل

پژوهشگر

• Linguistic typology
• Case and agreement systems
• Baltic languages
• +۷ مورد دیگر

Peter Arkadiev is a Senior Researcher at the Department of Slavic Studies, Universität Potsdam (since December 2024). His academic career includes positions such as Professor at the Russian State University for the Humanities (2020–2022), Research Professor at Vilnius University’s Philological Faculty (2018–2022), and extensive research roles across institutions in Russia, Germany, Lithuania, and Switzerland. He holds a PhD from the Institute of Slavic Studies of the Russian Academy of Sciences (2006) and a habilitation from the same institute (2019). His research focuses on linguistic typology, case systems, Baltic and Slavic languages, morphology, and areal linguistics. Notable contributions include studies on prefixal perfectivisation and typological analysis of grammatical relations. Education: 1999–2004: Specialist in theoretical/applied linguistics (summa cum laude), Russian State University for the Humanities 2004–2006: PhD student at Institute of Slavic Studies, Russian Academy of Sciences 2019: Habilitation on areal typology of prefixal perfectivisation Arkadiev’s work emphasizes cross-linguistic comparisons and historical perspectives. His recent projects explore morphological typology and syntax-morphology interfaces in Caucasian and Baltic languages. He has received the prestigious title of Professor of the Russian Academy of Sciences (2022). Awards: Professor of the Russian Academy of Sciences (2022) Grants/Funding: Marie Curie Senior Fellowship (Freiburg Institute for Advanced Studies, 2023–2024) ANR-DFG and DFG-funded research (Germany) EU Social Fund grants (Lithuania) Active in academic communities, he participates in the Association of Linguistic Typology, Societas Linguistica Europaea, and Academia Salensis.

Xuan Zhangمشاهده پروفایل

دانشیار

• Artificial Intelligence Hardware
• Machine Vision Sensors
• Electronic Design Automation
• +۳ مورد دیگر

Xuan Zhang serves as Associate Professor in Electrical and Computer Engineering at Northeastern University, leading the Sensory AI Lab since joining in January 2024. Her research bridges computer architecture, integrated circuits, and artificial intelligence to develop miniaturized AI systems for autonomous physical platforms. She earned her PhD in Electrical and Computer Engineering from Cornell University in 2012. Her educational background forms the foundation for her interdisciplinary work spanning hardware and software co-design. Dr. Zhang's research focuses on artificial intelligence hardware, machine vision sensors, and security for autonomous systems. She pioneers techniques for efficient in-sensor computing, analog circuit optimization via machine learning, and hardware-level privacy preservation. Her work addresses critical challenges in energy efficiency, robustness, and security for edge AI deployment, particularly in resource-constrained environments like medical devices and autonomous vehicles. Analysis of her 2023-2025 publications reveals three dominant trends: (1) hardware-accelerated privacy mechanisms for sensors, (2) machine learning-driven analog circuit design automation, and (3) energy-efficient architectures for neural network inference. These works consistently target real-world applications in healthcare, autonomous systems, and semiconductor design. Her accolades include the prestigious NSF CAREER Award (2020) and leadership in a $10 million federal semiconductor initiative. She contributes to national efforts in AI-powered chip design through the National Center for the Advancement of Semiconductor Technology. Dr. Zhang advises graduate researchers in the Sensory AI Lab, securing significant funding for projects spanning hardware security, in-sensor computing, and autonomous system assurance. Her lab collaborates with federal agencies and industry partners on cutting-edge semiconductor research. The Sensory AI Lab operates at the hardware-software interface, developing novel architectures for intelligent edge devices. Current projects include optical privacy preservation, robust analog design tools, and energy modeling frameworks for in-sensor visual computing systems.

• Human-Computer Interaction
• User Experience Design
• Cognitive Psychology
• +۳ مورد دیگر

Demetrios Karis serves as an Adjunct Lecturer in Experience Design at Bentley University while operating his independent consultancy Karis User Experience Evaluation. His academic foundation includes a BA from Swarthmore College, PhD from Cornell University, and Post Doctoral Fellowship at the University of Illinois, Urbana-Champaign, with current office location in Smith Technology Center (Room 121). Education background: BA, Swarthmore College PhD, Cornell University Post Doctoral Fellowship, University of Illinois, Urbana-Champaign Dr. Karis's research spans four decades with two distinct phases: early foundational work in Human-Computer Interaction focusing on speech recognition interfaces and cognitive psychology (1980s-2000s), followed by a radical pivot toward existential climate collapse analysis (2018-2025). His current scholarship integrates biophysical, political, economic, military, health, and psychological perspectives to model civilizational risks, while earlier contributions established key principles in usability testing, remote collaboration systems, and speech interface design. This evolution reflects both technical expertise in user experience methodologies and growing urgency regarding planetary-scale crises. Analysis of his 15 most recent publications reveals a clear methodological continuity—applying rigorous human factors frameworks from his HCI work to complex societal systems in his climate research—while demonstrating extraordinary disciplinary range from psychophysiology to geopolitical forecasting. Regarding academic service, no specific awards or honors are documented in available sources. His position as Adjunct Lecturer suggests primary industry engagement through his consultancy, though he maintains active teaching responsibilities in Bentley's Experience Design program. The absence of listed advisees or grants indicates his academic role may be primarily instructional rather than research-mentorship focused. Dr. Karis's independent research practice through Karis User Experience Evaluation represents his primary operational base for advancing both technical UX work and macro-scale collapse modeling.

Thomas Rainsfordمشاهده پروفایل

مدرس

• Historical Romance Linguistics
• Phonology
• Corpus Linguistics
• +۲ مورد دیگر

Thomas Rainsford is a Lecturer at the University of Stuttgart's Institute of Linguistics, Division of Romance Linguistics. His research focuses on historical Romance linguistics, particularly phonological change, morpho-syntax, and corpus development. He holds a PhD from the University of Cambridge and has held positions at ENS de Lyon and as a British Academy Post-Doctoral Fellow at the University of Oxford. Research interests center on: Diachronic evolution of French, Occitan, and Italian Prosodic changes and phonological annotation Lexical and morpho-syntactic aspects of motion events Historical corpus development with multi-layer annotation Publications demonstrate consistent focus on: Historical phonology and orthographic systems Syntactic change in medieval Gallo-Romance languages Corpus linguistics methodologies Computational approaches to historical texts Awards include the British Academy Post-Doctoral Fellowship. Current research involves leading a DFG-funded project examining motion events in French and Italian through lexical and syntactic change analysis. Developed the Old Gallo-Romance Corpus (OGR) with specialized phonological and metrical annotation layers.

Zihao Fuمشاهده پروفایل

عضو هیئت علمی

• Large Language Models
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Zihao Fu is a Research Assistant Professor at The Chinese University of Hong Kong (CUHK), specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) . His work bridges computational methods with social sciences, focusing on model instability, repetition, hallucination, and algorithmic fairness. He has held research positions at the Oxford Internet Institute and the Language Technology Lab at the University of Cambridge. Education Ph.D. in Systems Engineering and Engineering Management (2017–2021), CUHK M.Eng. in Aeronautics and Astronautics (2012–2015), Beihang University B.Eng. in Automation Science (2008–2012), Beihang University His research explores the theoretical foundations of LLMs, addressing challenges like repetition , instability , and hallucination . He integrates linguistics , cognitive science , and fairness frameworks to enhance both foundational understanding and real-world applications of language technologies. Recent work includes biomedical NLP applications ( BAND dataset ), parameter-efficient model adaptation, and fairness toolkits ( OxonFair ). Zihao leads projects like BioCaster (disease outbreak monitoring) and CAM-Tool (cloud task distribution). He is actively mentoring postdoctoral researchers at CUHK and CUHK (Shenzhen), with expertise in machine learning , knowledge base integration , and parallel computing systems . His industry experience includes developing distributed algorithms at Alibaba Cloud’s PAI platform.

Elizabeth Raceمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Memory Systems
• Learning Mechanisms
• +۳ مورد دیگر

Elizabeth Race is an Associate Professor in the Department of Psychology at Tufts University's School of Arts and Sciences. She holds a PhD in Neuroscience from Stanford University (2009) and completed postdoctoral training at Boston University's Memory Disorders Research Center. Her Integrative Cognitive Neuroscience Lab investigates the neural mechanisms of learning, memory, and cognitive control using fMRI and EEG techniques. Research focuses on how memory adaptively guides behavior and enables future simulations, examining both healthy adults and clinical populations with amnesia. Recent publications explore temporal dynamics of memory formation, misinformation susceptibility, and neural mechanisms of memory protection. Her work demonstrates consistent innovation in experimental paradigms linking cognitive psychology with neuroscience. She teaches courses including Brain & Behavior, Cognitive Neuroscience, and Statistics at undergraduate and graduate levels. Current research projects examine rhythmic neural synchronization during encoding and ventromedial prefrontal contributions to memory integration. Lab activities include collaborations with the Center for Applied Brain and Cognitive Sciences and research funded by the Grammy Museum Foundation.

Morwaread Farboodمشاهده پروفایل

دانشیار

• Music Perception and Cognition
• Computational Modeling of Music
• Algorithmic Composition
• +۳ مورد دیگر

Morwaread Farbood is an Associate Professor and Associate Director of Music Technology at New York University's Steinhardt School of Culture, Education, and Human Development. She holds dual affiliations with the NYU Music and Audio Research Lab (MARL) and the Max Planck/NYU Center for Language, Music, and Emotion (CLaME). Her research bridges music cognition, computational modeling, and algorithmic composition, with a focus on real-time auditory perception phenomena like tonality and musical tension. She co-founded the Northeast Music Cognition Group and was a 2017-2018 Radcliffe Fellow in Computer Science at Harvard University. Her professional achievements include the Pro Musicis International Award and First Prize at the Prague International Harpsichord Competition. Farbood actively contributes to music accessibility through innovations in audio description systems for live theater, using reference recordings and real-time synchronization techniques. She also maintains an active performing career as a harpsichordist, with performances at venues like Carnegie Hall and major international festivals. Research interests span computational models of musical structure, cross-cultural melodic learning, and neurocognitive underpinnings of musical perception. Her work integrates methods from music theory, cognitive psychology, and computer science to advance understanding of auditory perception's temporal dynamics. Recent projects include developing automated audio description systems for theatrical performances and exploring asymmetrical scale properties' impact on musical learning. She has authored over 50 peer-reviewed articles, patents, and creative works, reflecting her dual expertise in academic research and artistic practice.

Uri Hassonمشاهده پروفایل

استاد

• Neuroscience
• Natural Language Processing
• Cognitive Science
• +۷ مورد دیگر

Uri Hasson is a Professor at the Princeton Neuroscience Institute, Princeton University, focusing on the neural basis of brain-to-brain human communication, natural language processing, and language acquisition in real-world contexts. His lab challenges traditional experimental models by using deep learning to decode cognition during natural stimuli. Research Highlights: Investigates neural alignment in speaker-listener interactions. Develops computational tools to model language processing in everyday conversations. Explores shared principles between biological and artificial neural networks. Recent Article Trends: 2025–2023 publications emphasize deep language models matching neural responses, event segmentation via Bayesian surprise, and multibrain convergence during storytelling. Key keywords: Neuroscience, Natural Language Processing, Deep Learning, Cognitive Modeling . Awards: NIH Pioneer Award Lab & Collaborations: The Hasson Lab integrates neuroimaging (ECoG, fMRI) with large-scale datasets and AI to study real-life cognition. Collaborations span psychology, computational neuroscience, and machine learning.

Ruben Martinsمشاهده پروفایل

استاد پژوهشی

• Constraint Programming
• Program Synthesis
• Software Analysis
• +۳ مورد دیگر

Ruben Martins is an Assistant Research Professor and Master’s Program Director at the School of Computer Science, Carnegie Mellon University. He holds a Ph.D. from the Technical University of Lisbon, followed by postdoctoral research at the University of Oxford and UT Austin. His work focuses on constraint programming, program synthesis, and formal verification, with applications in improving programmer productivity and automating data science tasks. Education: Ph.D. in Computer Science, Technical University of Lisbon (2013) Postdoctoral Researcher, University of Oxford (2014-2015) Postdoctoral Researcher, UT Austin (2015-2017) Ruben's research bridges constraint programming with program synthesis, aiming to automate tasks such as vulnerability detection, code repair, and SQL synthesis. He developed Open-WBO , a MaxSAT solver that won multiple gold medals and is used in real-world optimization scenarios like seating arrangements for events. His work integrates large language models (LLMs) with traditional methods to enhance software analysis and debugging. Awards: Distinguished Paper Award at PLDI 2018 Gold Medal in MaxSAT Competitions for Open-WBO Advising & Grants: Ruben advises Master’s students and directs courses such as 15639, 15604, and others. His research has been supported by grants focusing on program synthesis and cybersecurity. Labs/Teams: Leads development of Open-WBO and contributes to projects like Crabtree (Rust API testing) and Pryde (evasion attack analysis).

• Natural Language Processing
• Text Generation
• Machine Learning
• +۱ مورد دیگر

Zihao Fu is a Researcher at the Oxford Internet Institute (OII), University of Oxford, where he served as a Postdoctoral Researcher from March 2024 to April 2025, focusing on the Trustworthiness Auditing for AI project. Previously, he was a Research Associate (PostDoc) at the University of Cambridge's Language Technology Lab under Prof. Nigel Collier. His research emphasizes Natural Language Processing, Text Generation, Machine Learning, and Biomedical Applications. Education includes a Ph.D. from The Chinese University of Hong Kong (supervised by Prof. Wai Lam) and a visiting student period at Tsinghua University's NLP Lab. He has substantial experience with large-scale distributed algorithms in Alibaba Cloud's PAI platform. Research interests span NLP, biomedical applications, and AI ethics, with notable contributions to datasets like BAND and frameworks like OxonFair. His work addresses challenges in text generation repetition, parameter-efficient fine-tuning, and algorithmic fairness.

Els Lefeverمشاهده پروفایل

دانشیار

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۵ مورد دیگر

Els Lefever is an Associate Professor at Ghent University, where she works with the LT3 (Language and Translation Technology) research team. Her position focuses on computational linguistics and natural language processing research, with strong ties to both theoretical and applied aspects of language technology. Dr. Lefever earned her PhD in Computer Science from Ghent University in 2012 with her dissertation titled "ParaSense: Parallel Corpora for Word Sense Disambiguation." Her academic journey began as a computational linguist at the R&D department of Lernout & Hauspie Speech Products before transitioning to academia. Els Lefever's research spans multiple areas within computational linguistics with particular expertise in multilingual natural language processing. Her work focuses on computational semantics, cross-lingual word sense disambiguation, and multilingual terminology extraction. Recent research directions include automatic detection of irony in online text, argumentation mining in social media, sentiment analysis of financial news, language modeling for low-resourced languages, and computational approaches to Byzantine Greek epigrams. Her research demonstrates a consistent pattern of bridging theoretical computational linguistics with practical applications across diverse language domains and historical periods. Professor Lefever actively supervises PhD research on several cutting-edge topics including terminology extraction from comparable corpora, event extraction and sentiment mining of financial news, language modeling for low-resourced languages, argumentation mining in social media, and the automatic detection of links between Byzantine Greek epigrams. Her supervision portfolio demonstrates her commitment to advancing multiple frontiers of computational linguistics simultaneously. As an educator, Professor Lefever teaches courses in Terminology and Translation Technology, Language Technology, Localisation, Digital Text Analysis, and Digital Humanities. Her teaching reflects her research interests, providing students with both theoretical foundations and practical skills in language technology applications. The LT3 research group, where Professor Lefever is a key member, maintains strong connections with both academic and industry partners. The group has participated in numerous international conferences and shared tasks including SemEval competitions across multiple years, demonstrating consistent contributions to benchmark datasets and evaluation methodologies in natural language processing.

William Idsardiمشاهده پروفایل

استاد

• Neurolinguistics
• Phonology
• Psycholinguistics
• +۳ مورد دیگر

William Idsardi is a Professor of Linguistics at the University of Maryland, affiliated with the Program in Neuroscience and Cognitive Science and the Maryland Language Science Center. His research focuses on neurolinguistics, phonology, and psycholinguistics, combining experimental, computational, and theoretical approaches. Key areas include phonological abstraction mechanisms, the neural basis of speech perception, and the computational foundations of phonological patterning. His work bridges disciplines, investigating how phonological categories are represented in the brain using neuroimaging techniques like MEG. Notable contributions address the role of categorical perception in fricative sounds, the phoneme hypothesis, and computational complexity differences between phonology and syntax. Collaborative projects explore dialect perception, infant lexical learning, and cross-linguistic vowel systems. Publications span phonological theory, neuroimaging studies, and computational linguistics, emphasizing interdisciplinary methods. His research has implications for understanding language acquisition, speech disorders, and the evolution of linguistic structure. Labs associated with his work include the EEG/ERP Lab and Maryland Neuroimaging Center.

Gerry Altmannمشاهده پروفایل

استاد

• Psycholinguistics
• Sentence Processing
• Event Cognition
• +۳ مورد دیگر

Gerry Altmann is a Professor and Director of Perception, Action, and Cognition in the Department of Psychological Sciences at the University of Connecticut. He earned his Ph.D. from the University of Edinburgh in 1986. His research employs behavioral and neuroscientific methods to investigate real-time language processing, event cognition, and object representation dynamics. His research focuses on: Sentence processing and language comprehension mechanisms Event cognition and mental representation of object histories Real-time mapping between language and visual environments Neural correlates of language processing using EEG and fMRI Recent publications (2019-2025) demonstrate methodological diversity including eye-tracking, EEG, computational modeling, and behavioral paradigms. Predominant themes include event representation, neural dynamics of language processing, and cognitive architectures supporting abstract concept formation. Honors include: Founding Director of the CT Institute for the Brain and Cognitive Sciences (2015-2021) Editor-in-Chief of Cognition (2006-2015) Honorary Secretary of the UK's Experimental Psychology Society (2004-2007) He has supervised numerous graduate students including doctoral candidate Emily Yearling and master's student Wesley Leong. Recent graduates include Julia Mocciola, Katrina Turick, and Yanina Prystauka. Dr. Altmann directs the Altmann Lab at UConn, which uses eye-tracking, EEG, and fMRI to study language processing. The lab is affiliated with the CT Institute for the Brain and Cognitive Sciences and includes postdoctoral, graduate, and undergraduate researchers.

• Artificial Intelligence
• Data Science
• Machine Learning
• +۷ مورد دیگر

Hady W. LAUW is an Associate Professor in the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU), serving as Director of the BSc (Computer Science) Programme and a Lee Kong Chian Fellow. He holds a PhD from Nanyang Technological University (2008). His research focuses on artificial intelligence, data science, machine learning, and recommender systems, with notable contributions to multimodal recommendation frameworks like Cornac and collaborative filtering techniques. He teaches advanced courses including IS712 Machine Learning for postgraduate students and CS608 Recommender Systems for MITB programme participants. His work emphasizes practical applications, such as designing explainable recommendation systems and integrating A/B testing into frameworks. Key research interests include web mining, preference learning, representation learning, and decision support systems. He has advised multiple students on topics like neural networks, collaborative filtering, and comparative analysis of reviews. Scientific achievements include the Lee Kong Chian Fellowship and over 100 publications in top venues like ACM WWW and IEEE TKDE. He actively contributes to conferences as a PC member and chairs events like PAKDD. His Cornac framework supports reproducible research in multimodal recommendations. He leads the Preferred.AI research group, fostering undergraduate and postgraduate research in computing. His work bridges theoretical advancements with industry applications, particularly in data-driven decision making and automated evaluation metrics.