جستجوی استاد راهنمای دانشگاهی

Mark Liberman is a Trustee Professor at the University of Pennsylvania , holding appointments in the Department of Linguistics and Department of Computer and Information Science . He serves as Director of the Linguistic Data Consortium and Faculty Director of Ware College House . His career spans linguistics, speech technology, and computational methods. Education: Harvard University (1965-1969), MIT (M.S. 1972, Ph.D. 1975) Professional Experience: AT&T Bell Laboratories (1975-1990), University of Pennsylvania (1990-present) His research interests include: Corpus-based Phonetics : Analyzing speech patterns via large-scale datasets. Clinical Applications : Developing speech biomarkers for neurodegenerative diseases. Tonal Phonology : Studying lexical tone and intonation in languages like Yoruba and Mandarin. Formal Annotation Models : Creating frameworks for linguistic data standardization. Recent publications highlight automated speech analysis, cross-linguistic prosody, and digital biomarkers for conditions like ALS-FTD and Alzheimer’s. His collaborations span computational linguistics , neurology , and cognitive science . Scientific awards include the IEEE James L. Flanagan Award (2017), Antonio Zampolli Prize (2010), and fellowships from the AAAS and Linguistic Society of America . He advises PhD students May Chan and Jonathan Him Nok Lee and contributes to editorial boards for journals like Cognition and Annual Review of Linguistics . His work bridges speech science , language technology , and neurocognitive research .

• Corpus-based Phonetics
• Speech and Language Technology
• Clinical Applications of Linguistics
• +۶ مورد دیگر

Ryan Heuser is an Assistant Professor in Digital Humanities at the University of Cambridge, specializing in computational approaches to literary and intellectual history, prosody, and artificial intelligence's impact on language. His work bridges data science, machine learning, and literary studies through digital methodologies. Doctoral training in Eighteenth-Century British Literature, Stanford University (2019) Founding member & Associate Research Director, Stanford Literary Lab Junior Research Fellow, King’s College Cambridge (2019-2022) Research interests span computational modeling of semantic revolutions, large-scale literary field analysis, and the intersection of digital methods with historical and intellectual studies. His book Explorations in the Digital History of Ideas (2023) co-edited with Peter de Bolla exemplifies this approach. Recent publications focus on historical semantics, metrical analysis, and digital mapping of emotions in literature, reflecting his interdisciplinary expertise in natural language processing, network theory, and literary data visualization. Currently leads teaching initiatives at Cambridge Digital Humanities and contributes to computational projects exploring textual rhythms and large language models.

• Digital Humanities
• Computational Prosody
• Literary and Intellectual History
• +۵ مورد دیگر

Matthew Louis Mauriello is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware , where he directs the Sensify Lab . He holds a PhD in Computer Science from the University of Maryland (2018) and completed postdoctoral work at Stanford University (School of Medicine, 2020; School of Public Policy & Environmental Engineering Department, 2019). Research interests span Human-Computer Interaction (HCI), Ubiquitous Computing, and User-Centered Design with applications in: Sustainability Human-Building Interaction Wearable Technology Personal Informatics Educational Game Design Mental Health Interventions Recent publications highlight trends in stress monitoring (skin-like biosensors, workplace wellbeing), energy auditing (thermography systems), and educational technology (block-based programming tools for teachers). His work appears in ACM CHI, ACM Human-Computer Interaction, and Building and Environment. Scientific awards include: Best Paper Honorable Mention, CHI 2016 Best Paper Honorable Mention, CHI 2015 Best of WebSci'18 Teaching at University of Delaware encompasses courses like Educational Game Design Operating Systems Advanced Web Technologies Computing for Social Good with a focus on project-based learning and systems thinking.

• Human-Computer Interaction
• Ubiquitous Computing
• Sustainability
• +۷ مورد دیگر

Wei Xu is an Associate Professor at Georgia Institute of Technology's College of Computing and School of Interactive Computing, with affiliations to the Machine Learning Center. Their research bridges machine learning, natural language processing, and social media with focus areas in large language models, cultural bias mitigation, multilingual capabilities, and human-AI collaboration in text evaluation. NSF CAREER and Google Academic Research Award recipient Director of NLP X Lab PhD from New York University, BSMS from Tsinghua University Research interests span: Multilingual Multicultural LLMs addressing representational gaps and cultural adaptation in language models (NAACL 2025, ACL 2024); Robustness and Reasoning through dynamic AGI evaluations (ACL 2024, EMNLP 2024); Interdisciplinary NLP applications in security, healthcare, and law (EMNLP 2024, ACL 2024). Recent publications focus on multilingual alignment (NAACL 2025), privacy risk estimation (arXiv 2025), cultural bias analysis (ACL 2024), and medical text simplification (EMNLP 2024). Key themes include bias mitigation, multimodal processing, and practical LLM evaluation. Scientific Awards : NSF CAREER, Google/Sony/Criteo research awards, ACL'24 Best Social Impact Award, COLING'18 Best Paper Advising 15 PhD/MS/BSMS students including Yao Dou (human-centered LLM evaluation), Tarek Naous (multilingual LLMs), and alumni like Chao Jiang (Apple AI/ML) and Yang Chen (NVIDIA research scientist). Teaches graduate courses on NLP and LLMs.

• Large Language Models
• Natural Language Processing
• Machine Learning
• +۶ مورد دیگر

Antoine Bosselut is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he leads the EPFL NLP group. His research focuses on developing AI reasoning agents that can model, represent, and reason about human and world knowledge, with applications in health, education, and global fairness. His research interests span multiple critical areas in modern AI: LLM Representations of Knowledge: Understanding what language models know and how they represent that knowledge internally Reasoning Algorithms: Developing methods to improve LLMs' reasoning capabilities through symbolic systems, neuroscience, and cognitive science Large-scale AI Development: Creating open-source foundation models with multilingual capabilities AI Democratization: Ensuring equitable access to AI technologies across different cultural and regulatory contexts His recent publications reveal a strong focus on the intersection of language models and cognitive science, with multiple studies examining how LLMs align with human cognition. He's also deeply engaged in practical applications of NLP technology, particularly in education and multilingual settings, as evidenced by his work on evaluating AI's impact on higher education and developing culturally-aware language models. His scientific achievements have been recognized with several prestigious awards: Outstanding Paper Award at NAACL 2025 ELLIS Scholar designation in 2024 Outstanding Paper Award at ACL 2023 Inclusion in Forbes 30 Under 30 list for Science & Healthcare in 2021 Bosselut actively mentors numerous PhD students across diverse NLP research areas and has secured significant recognition for his work in both academic and media circles. His lab has been featured in major publications including Communications of the ACM, The Atlantic, and Quanta Magazine, highlighting the societal impact of his research on commonsense reasoning and AI capabilities.

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Kai-Wei Chang is an Associate Professor at the University of California, Los Angeles (UCLA) in the Department of Computer Science, part of the Henry Samueli School of Engineering. He is also an Amazon Scholar at Alexa AI, focusing on advancing trustworthy AI and multimodal foundation models. His research bridges NLP, machine learning, and ethical AI, with a focus on fairness, robustness, and bias mitigation in language and vision-language systems. Education: Ph.D. in Computer Science (UIUC, 2015), M.S. and B.S. in Computer Science and Electrical Engineering from National Taiwan University. Research Interests: Trustworthy NLP (fairness, robustness), Multimodal Foundation Models (e.g., VisualBERT, GLIP), Reasoning in LLMs, and mitigating societal biases in AI systems. Notable contributions include pioneering work on aligning NLP models with human values and developing SOTA multimodal models like DesCo and GLIP. Awards: Sloan Research Fellowship (2021), Okawa Grant (2018), EMNLP Best Paper (2017), KDD Best Paper (2010). His work is funded by NSF, IARPA, ONR, and industry partners like Amazon, Google, and Facebook. Service: VP-Elect of SIGDAT, Ethics Committee Chair (NAACL 2022), Organizer of Trustworthy NLP Workshops, and Senior Area Chair for top conferences (ACL, NeurIPS, AAAI). Labs/Teams: Leads the UCLA Natural Language Processing Group, fostering interdisciplinary research on ethical AI and multimodal systems.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Carl Vondrick is a Professor in the Department of Computer Science at Columbia University. His research focuses on creating robust and versatile perception systems that leverage video and interaction with the natural world, with applications in 3D reconstruction, visual question answering, and robot manipulation. Former research scientist at Google Visiting researcher at Cruise Education: PhD (2017) from MIT, advised by Antonio Torralba BS (2011) from UC Irvine, advised by Deva Ramanan His research explores multimodal approaches for cross-task and cross-modal transfer, scene dynamics, audiovisual perception, interpretable models, and spatial awareness systems. The lab emphasizes zero-shot generalization and neuro-symbolic methods while addressing safety and robustness in AI systems. Key publication trends include: 2025: Video generation for robotics 2024: Differentiable rendering and cross-modal reasoning 2023: Robust perception and 3D modeling Scientific Awards: 2024 PAMI Young Researcher Award 2021 NSF CAREER Award Teaching Roles: Teaching Computer Vision II (2021-2025), Computer Vision I (2018-2019), and Representation Learning (2020-2022). Advising: Advises 8 current PhD students and has mentored 5 graduated students now at institutions like MBZUAI and UMD. The lab recruits 1-2 PhD students annually through Columbia’s PhD program. Grants and Collaborations: Funded by NSF, DARPA, Toyota Research Institute, Amazon Research, and Google.

• Computer Vision
• Machine Learning
• Multimodal Perception
• +۱۱ مورد دیگر

Jessica Straley is an Associate Professor in the Department of English at the University of Utah, where she has served since 2005 (Visiting Assistant Professor 2005-2007, Assistant Professor 2007-2016, Associate Professor 2016-present). She holds a PhD in English from Stanford University, an MA in Literature, Culture, and Modernity from Queen Mary and Westfield College, University of London, and a BA in English from Cornell University. Education: PhD, English - Stanford University MA, Literature, Culture, and Modernity - Queen Mary and Westfield College BA, English - Cornell University Her research focuses on intersections between Victorian literature, children's literature, animal studies, disability studies, and ecocriticism. She explores how literary imagination interacts with scientific and moral discourses, particularly in 19th-century contexts. Recent publications analyze feral child narratives, zoo representations, and evolutionary theory in children's texts. Her work bridges historical literary analysis with contemporary critical frameworks like disability rights and environmental ethics. Scientific Awards: Faculty Fellowship Award (University Research Council, 2017) Ramona W. Cannon Award for Teaching Excellence (2016) Tanner Humanities Center Fellowship (2016) University Research Committee Faculty Fellowship (2011) Newberry Library Short-Term Library Research Fellowship (2008) She teaches courses in 19th-Century British Literature, Intellectual Movements, and Honors Thesis/Project supervision. Her external grant (Animal Testing URC, 2017-2018) demonstrates institutional support for her interdisciplinary work.

• Victorian Literature
• Children's Literature
• Animal Studies
• +۴ مورد دیگر

Matthew Potolsky is Professor of English at the University of Utah, specializing in nineteenth-century literature and literary theory. His career spans from 1998 Lecturer at Harvard University to current University Professorship. He earned a BA in Comparative Literature and Philosophy (1990), followed by MA and PhD in Comparative Literature (1992, 1997) from UC Irvine. Chair of English Department (2013-2016) University Professor (2014-2016) Research focuses on Decadence , Mimesis , Finance-Aesthetics intersections , and Government Secrecy . His work traces connections between financialization and decadent aesthetics, revealing how economic cycles influence artistic production. Key themes include: Decadent anti-realist literary movements Finance capital's cultural impact Decadent counterpublic formations Victorian aesthetic education debates Sublime aesthetics in national security Cosmopolitanism in literary communities Recent publications analyze: Decadent style as financialization rhetoric Reintroduction of verisimilitude theory Decadent responses to financial crises Mimetic labor in artistic production Decadent cosmopolitan counterpublics Historical parallels between financialization and literary decadence

• Decadence
• Mimesis
• 19th-Century European Literature
• +۳ مورد دیگر

Shrikanth (Shri) Narayanan is a University Professor and holder of the Niki and Max Nikias Chair in Engineering at the University of Southern California (USC), serving as the inaugural Vice President for Presidential Initiatives. He leads the Signal Analysis and Interpretation Lab (SAIL) and holds joint appointments in Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology-Head and Neck Surgery. His research focuses on speech and audio processing, behavioral signal processing, and real-time MRI of speech production, with applications in healthcare, education, and technology. Education: B.E. in Electrical Engineering from College of Engineering, Guindy (Chennai, India, 1988); M.S., Engineer, and Ph.D. in Electrical Engineering from UCLA (1990, 1992, 1995). Research interests span computational linguistics, machine learning, and multimodal human behavior analysis. He pioneered technologies for speech biomarkers in mental health, real-time MRI of speech production, and wearable sensor systems for longitudinal health studies. His work in speech emotion recognition, forensic interviews, and clinical applications has been recognized through over 40 awards, including the IEEE Flanagan Award and ISCA Medal. He has published extensively in journals like Proceedings of the IEEE , Journal of the Acoustical Society of America , and PLOS One . Key Grants: NSF CAREER, Okawa Research, IBM Faculty, Google/Amazon awards. Labs/Teams: Signal Analysis & Interpretation Lab (SAIL), USC Information Sciences Institute (ISI), Google Visiting Faculty Researcher.

• Speech and Audio Processing
• Behavioral Signal Processing
• Real-Time MRI of Speech Production
• +۴ مورد دیگر

Dr. Diyi Yang is an Assistant Professor in the Computer Science Department at Stanford University. She leads the Social and Language Technologies (SALT) Lab, affiliated with the Stanford NLP Group, Stanford HCI Group, Stanford AI Lab (SAIL), and Stanford Human-Centered Artificial Intelligence (HAI). Her research focuses on socially aware natural language processing, large language models (LLMs), and human-AI interaction, aiming to improve human-human and human-computer communication through socially grounded AI systems. Education: Ph.D. in Language Technologies Institute, Carnegie Mellon University (2013–2019) B.S. in ACM Honored Class, Shanghai Jiao Tong University (2009–2013) Research Interests: Dr. Yang’s work bridges computational social science and NLP. She explores how AI can understand social contexts in language use and develop systems that respect cultural norms, ethical standards, and human values. Her lab’s projects include AI companions for skill training (e.g., Rehearsal Dialects), norm-aware LLMs (NormBank), and frameworks for human-AI collaboration (Co-Gym). Recent efforts address bias in AI, societal impacts of LLMs, and ethical evaluation of human-AI systems. Awards & Honors: 2024: Sloan Research Fellowship, ONR Young Investigator Award 2023: Adamic-Glance Young Distinguished Award (ICWSM), Kavli Fellow (NAS) 2022: NSF CAREER Award, Microsoft Research Faculty Fellow 2020: IEEE AI’s 10 to Watch Advising & Grants: Dr. Yang advises over 10 PhD students and postdocs, co-leading projects on LLM evaluation (SWE-bench/SWE-smith), human-AI ethics, and culturally aware NLP. Her research is supported by NSF, Amazon, DARPA, Google, and Stanford’s HAI initiative. Labs & Teams: The SALT Lab collaborates across disciplines, with projects spanning computer science, linguistics, and social sciences. Current initiatives include developing AI tools for mental health support (AI Partner & Mentor) and auditing societal impacts of LLMs.

• Computational Social Science
• Natural Language Processing
• Socially Aware NLP
• +۴ مورد دیگر

Jennifer Olsen, PhD, is an Assistant Professor of Computer Science at the University of San Diego since 2020. She holds a PhD, MS, and BS in Human-Computer Interaction and Cognitive Science from Carnegie Mellon University, followed by postdoctoral research at the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. Her research focuses on the intersection of human-computer interaction, cognition, and education, emphasizing collaborative learning and educational technology design from both learner and instructor perspectives. Education: PhD in Human-Computer Interaction, Carnegie Mellon University MS in Human-Computer Interaction, Carnegie Mellon University BS in Cognitive Science, Carnegie Mellon University Research Interests: Dr. Olsen explores how collaboration supports learning, designs technologies to enhance educational practices, and investigates gaze-based metrics for understanding collaborative problem-solving. Her work spans gamified robotics, AI-driven orchestration systems, and virtual reality applications in vocational training. She emphasizes learner-centered design and the integration of social robots and virtual agents in pedagogical settings. Grants/Advising: While no specific grants or advisees are listed, her prolific publication record indicates active involvement in educational technology research and development. Her work addresses challenges in classroom orchestration, multimodal data analysis, and accessibility in educational robotics. Labs/Teams: Collaborates with interdisciplinary teams focused on educational technology, human-robot interaction, and adaptive learning systems. Her research leverages tools like FROG orchestration graphs and eye-tracking technologies to develop practical classroom solutions.

• Human-Computer Interaction
• Learning Sciences
• Educational Technology
• +۲ مورد دیگر

Andrew Mitchell is a Professor at the Faculty of Law, Monash University, and a member of the WTO Dispute Settlement Panelists Indicative List. He has extensive legal practice experience with Allens Arthur Robinson and consults for governments, international organizations, and the private sector. Mitchell has taught law in Australia, Canada, Indonesia, Singapore, and the US. He holds law degrees from the University of Melbourne, Harvard Law School, and a PhD from the University of Cambridge. His research focuses on international economic law, public international law, and digital trade governance, with a particular emphasis on the intersection of trade law and public health. Mitchell has secured six major grants, including an Australian Research Council Future Fellowship, and has authored over 170 books and articles. He serves as an editor for Edward Elgar’s International Economic Law Series and multiple journal editorial boards. Recent projects include 'Safeguarding Health in International Investment Agreements' (2022–2025) 'Maritime Cooperation for a Sustainable Indo-Pacific' (2021–2022) 'Global E-Commerce and Cottage Industries in India' (2020–2021) He has contributed to policy submissions on bilateral investment treaties and delivered lectures on data sovereignty and digital trade. His awards include editorial leadership roles at journals like the Journal of World Investment and Trade and Asia Pacific Law Review .

• International Economic Law
• Public International Law
• International Trade Law
• +۳ مورد دیگر

Walid Magdy is a Professor at the School of Informatics, The University of Edinburgh, where he is a faculty member at the Institute for Language, Cognition and Computation (ILCC). He holds a PhD from Dublin City University's School of Computing and has been a faculty fellow at The Alan Turing Institute. With substantial industry experience, he has worked for Qatar Computing Research Institute (QCRI), Microsoft, and IBM, where he filed nine patents. His research spans computational social science and natural language processing. In computational social science, he focuses on social content analysis, political bias detection, polarization, and users' behavior analysis/prediction, with particular attention to understudied communities. His natural language processing work centers on social applications including sentiment analysis, sarcasm detection, and hate-speech identification, with specialized expertise in Arabic and its dialects as well as Persian. Professor Magdy's recent publications demonstrate a consistent focus on Arabic language processing and social media analysis, with growing attention to cultural factors in NLP systems. His work bridges computational methods with social science questions, particularly regarding misinformation, cultural differences in online behavior, and the impact of platform policies on diverse linguistic communities. He has expanded his research to include Persian language processing and continues to explore social dynamics across different cultural contexts. His significant contributions have been recognized with multiple awards: Best Demo Award for TwiXplorer at CSCW 2024 Outstanding Paper Award at ACL 2024 Best Paper Award Runner-up at SocInfo 2022 Best Paper Award at WANLP-EMNLP 2022 Best Paper Award at AIRS 2015 Best Dataset Award at ICWSM 2013 Professor Magdy serves as an editor for Springer's Social Network Analysis and Mining journal and has held leadership roles in major conferences including ACL 2023, ArabicNLP 2023, ICWSM 2022, and ASONAM 2022. He has co-organized numerous shared tasks focused on Arabic language processing and social media analysis, contributing significantly to community resources and benchmarks. He founded and directs the Social Media Analysis and Support for Humanity (SMASH) research group at the University of Edinburgh, which has organized the Summer School in Computational Social Science (SICSS-Edinburgh) in 2022, 2023, and 2025, training researchers in computational social science methodologies.

• Computational Social Science
• Natural Language Processing
• Social Content Analysis
• +۸ مورد دیگر

Adriana Kovashka is an Associate Professor at the University of Pittsburgh , affiliated with the School of Computing and Information and serving as Department Chair . Her academic journey began with BA degrees in Computer Science and Media Studies from Pomona College (2008) and a PhD in Computer Science from The University of Texas at Austin (2014). Joined Pitt’s faculty in January 2015 NSF CAREER awardee (2021) Google Faculty Research Award recipient Dr. Kovashka’s research spans Computer Vision , Machine Learning , and Natural Language Processing , focusing on visual rhetoric, weak multimodal supervision, and domain adaptation. She pioneered techniques for analyzing political imagery, developing robust object detection frameworks, and exploring the intersection of visual and textual persuasion through large-scale annotated datasets. Her recent work emphasizes geographic diversity in vision-language systems, audio-visual fusion for domain generalization, and shape-texture bias mitigation in CNNs. Key publications include groundbreaking studies on symbolic reasoning, multimodal dialogue systems, and ethical AI applications in education. Scientific honors include: NSF CRII Award (2016) NSF CAREER Award (2021) Pitt CRDF Award (2016, 2018) Best Paper at ECV Workshop (2021) Google Faculty Research Award (2016, 2018) Dr. Kovashka actively mentors students in multimodal learning projects and collaborates with interdisciplinary teams on NSF-funded initiatives. She co-organizes workshops like the first CVPR workshop on advertisement understanding and leads research groups exploring human-AI co-learning systems.

• Computer Vision
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر