جستجوی استاد راهنمای دانشگاهی

• Cognitive Psychology
• Social Cognition
• Neuroscience
• +۷ مورد دیگر

Professor Heather Ferguson is a distinguished cognitive psychologist at the University of Kent's School of Psychology, where she has built an impressive academic career since her appointment as Lecturer in 2009. Promoted to Professor in 2018, she leads groundbreaking research examining the cognitive basis of social communication across the lifespan. Her work bridges cognitive psychology, neuroscience, and social cognition, with particular expertise in perspective-taking, theory of mind, and the interface between cognitive processes and social interaction. Her research primarily investigates how we access and represent other people's perspectives during communication, using methodologies including eye-tracking, EEG, and reaction time measurements. Key questions driving her work include: How do people understand and predict events based on others' mental states? What happens when these conflict with our own knowledge? How do social abilities relate to cognitive skills like memory and inhibitory control? How does aging affect social cognition? Her work has significant implications for understanding autism spectrum disorder, social development, and cognitive aging. Professor Ferguson's recent publications reveal a strong focus on perspective-taking across the lifespan, social cognition in autism, the cognitive effects of fiction reading, and the neural mechanisms underlying empathy. Her research demonstrates consistent methodological rigor through pre-registered studies and meta-analyses, with particular attention to developmental trajectories from adolescence through older adulthood. Psychonomic Society Early Career Award (2019) Open Science Framework Pre-registration Challenge award (2018) Cognitive Neuroscience Society Postdoctoral Fellow Award (2018) University of Kent Prize for Research (2016) Kent Union Teaching Award for 'Best Teacher' (2012) Professor Ferguson actively supervises multiple PhD students and has secured substantial research funding, including a €1.5 million ERC Starting Grant and multiple Leverhulme Trust grants. Her work with the Cognitive basis of Social Communication and Ageing (COGSOCOAGE) research group has produced influential findings on social cognition across the lifespan. She serves as Associate Editor for the Journal of Experimental Psychology: Learning, Memory & Cognition and on the editorial board of Cognition, while also mentoring early-career researchers through the Eastern Arc Mentoring Scheme.

Ali Mousaviمشاهده پروفایل

استادیار

• Archaeology of Iran
• Achaemenid architecture and epigraphy
• Sasanian empire
• +۳ مورد دیگر

Ali Mousavi is Assistant Professor of Iranian Archaeology in UCLA’s Department of Near Eastern Languages and Cultures and a core faculty member of the Cotsen Institute of Archaeology. A Berkeley PhD and former fellow of the Smithsonian, Maison de l’Orient and Global Heritage Fund, he has directed excavations and UNESCO World-Heritage projects at Pasargadae, Bam, Susa, Sultaniyeh and Turang Tepe and authored prize-winning volumes Ancient Iran from the Air and Persepolis: Discovery and Afterlife of a World Wonder . Education PhD, Near Eastern Studies (Archaeology), University of California, Berkeley (2005) MA, Archaeology, History and Languages of Old World Civilizations, Université Lyon II, France (1997) BA, Archaeology and Art History of Europe and the East Mediterranean, Université Lyon II, France (1996) Research interests span the archaeology and art history of Iran from the Neolithic to the early-20th century, with particular focus on Achaemenid and Sasanian monumental architecture, ancient irrigation (qanats), landscape archaeology, digital heritage, and the modern historiography of Iranian archaeology. His field projects integrate remote sensing, epigraphy, GIS and conservation science to investigate imperial capitals, rock-cut monuments and water-management systems across the Iranian plateau. Across more than 30 peer-reviewed articles and book chapters, Mousavi has re-examined dating criteria for Achaemenid stone monuments, analysed royal inscriptions as visual displays, traced medieval Persian pilgrims’ graffiti at ancient sites, and produced synthetic archaeological surveys of the Sasanian empire and the Central Alborz Iron-Age cultures. The corpus reflects a sustained engagement with primary field data, archival research and critical historiography of 19th- and 20th-century excavations. Selected honours Ehsan Yarshater Book Award (2014) Iranian Ministry of Culture World Book Award (2014) Leon Levy – Shelby White publication grant (2008) UNESCO award for World-Heritage nomination files (2003) Iran Heritage Foundation field-work award (2003) Guitty Azarpay Fellowship, UC Berkeley (2000-2003) IFRI Fellowship, Paris (1998) At UCLA he offers undergraduate courses “Archaeology of Iran” and “Ancient Cities of Iran (4000 BC-AD 1900)” and mentors graduate researchers in the Cotsen Institute. His grants and fellowships from NSF-equivalent European and American agencies underwrite both field seasons and publication of critical archaeological corpora, while his service on Iranian, UNESCO and international heritage boards continues to link scholarly output with heritage-management policy.

Ian Miersمشاهده پروفایل

استادیار

• Computer Security
• Applied Cryptography
• Blockchain
• +۴ مورد دیگر

Ian Miers serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, holding a joint appointment with the University of Maryland Institute for Advanced Computer Studies (UMIACS) and serving as a core faculty member of the Maryland Cybersecurity Center (MC2). His academic home resides within the Department of Computer Science, though the overarching college/school structure is not explicitly stated in available materials. His research program centers on applied cryptography with a context-driven methodology: starting from real-world security challenges to develop deployable cryptographic protocols. Key focus areas include blockchain privacy (notably Zerocoin/Zerocash), zero-knowledge proofs, anonymous credentials, and secure messaging systems. Miers emphasizes practical implementations that address subtle security requirements in production environments, bridging theoretical cryptography with tangible system security. Analysis of his 15 most recent publications reveals dominant trends in zero-knowledge proof scalability (zkSNARKs), privacy-preserving infrastructure for blockchains, and cryptographic solutions for content moderation in encrypted messaging. His work consistently targets deployable systems, with increasing focus on balancing privacy guarantees with accountability requirements in real-world applications. Miers actively recruits PhD students for hands-on research in his small lab, emphasizing direct collaboration on applied security and blockchain problems. As a founding scientist of Aleo, Bolt Labs, and Zcash, he translates academic research into commercial products, with his work receiving coverage from major media outlets including The Washington Post, The New York Times, and Wired.

David Yarowskyمشاهده پروفایل

استاد

• Natural Language Processing
• Spoken Language Systems
• Machine Translation
• +۳ مورد دیگر

David Yarowsky is a Professor in the Department of Computer Science at Johns Hopkins University. He leads the Low-Resource Languages Lab and is a member of the Center for Language and Speech Processing. Harvard University - Bachelor of Arts in Computer Science (1987) University of Pennsylvania - Master of Science in Engineering (1993) and PhD in Computer and Information Science (1996) Research Interests : Natural Language Processing, particularly focusing on word sense disambiguation, minimally supervised induction algorithms, multilingual NLP, and machine translation for low-resource languages. His work bridges theoretical linguistics with practical applications in information retrieval, spoken language systems, and very large text databases. Article Trends : His publications emphasize cross-lingual transfer learning, universal morphology, and low-resource language technologies. Key themes include morphological analysis, computational etymology, and adversarial speech recognition. Scientific Awards : ACL Fellow (2013-present) Professional Service : Served as Treasurer and Executive Committee Member of the Association for Computational Linguistics, Secretary-Treasurer of SIGDAT, and chair/co-chair of major conferences including EMNLP 2013, IJCNLP 2011, and ACL 2014. Labs & Teams : Director of the Low-Resource Languages Lab at JHU and active member of the Center for Language and Speech Processing.

Assia Mahboubiمشاهده پروفایل

پژوهشگر

• Type Theory
• Formal Verification
• Computer-Aided Mathematics
• +۳ مورد دیگر

Assia Mahboubi is a tenured researcher ( directrice de recherche ) at INRIA in the Gallinette team, Nantes, France, and an endowed professor in the Algebra and Number Theory section of the Vrije Universiteit Amsterdam, Netherlands. Her work bridges theoretical computer science and formal mathematics, with significant contributions to proof assistants and formal verification. Her research focuses on the foundations and formalization of mathematics in type theory, particularly on the automated verification of mathematical proofs. She explores the interplay between computer algebra and formal proofs, and is a key contributor to the Rocq prover (formerly Coq) and the Mathematical Components libraries. Her work often examines how familiar mathematical objects can be optimally represented for computer-aided proof checking. Recent publications show a strong trend toward categorical reasoning, diagram chasing, and continuity properties in constructive type theory, with increasing focus on practical applications of formal methods in computational mathematics. Her work demonstrates the maturation of formal verification techniques from theoretical foundations to practical tools for mathematical research. ERC Consolidator grant for the FRESCO (Fast and Reliable Symbolic Computation) project Mahboubi actively supervises doctoral students including Vojtěch Štěpančík, Tomás Vallejos Parada, and Alain Chavarri Villarello. She has received significant research funding through her ERC Consolidator grant for the FRESCO project, which aims to develop fast and reliable symbolic computation techniques. She is deeply involved in the international research community, serving on program committees for major conferences including POPL, CPP, and ICFP. She leads research in the Gallinette team at INRIA, which focuses on the intersection of proof assistants, programming languages, and formal mathematics. Her work has helped establish formal verification as a practical tool for mathematical research, moving beyond theoretical foundations to real applications in computational mathematics.

Matthias Feurerمشاهده پروفایل

استاد

• Automated Machine Learning
• Hyperparameter Optimization
• Bayesian Optimization
• +۵ مورد دیگر

Matthias Feurer is a Thomas Bayes Fellow and interim professor at the Chair of Statistical Learning and Data Science, funded by the Munich Center for Machine Learning (MCML) at Ludwig Maximilian University of Munich. He is a member of the Department of Statistics at LMU Munich, working under Prof. Dr. Bernd Bischl. His academic background includes: PhD in Computer Science from Albert-Ludwigs-Universität Freiburg, supervised by Prof. Dr. Frank Hutter M.Sc. in Computer Science from the University of Freiburg B.Sc. in Computer Science and Media from the Media University Stuttgart Feurer's research focuses on simplifying machine learning usage through Automated Machine Learning (AutoML). His work encompasses hyperparameter optimization, meta-learning, and model selection, with increasing emphasis on multi-objective AutoML that considers factors beyond predictive performance such as interpretability, deployability, and fairness. He actively develops open-source tools to advance the field. His recent publications demonstrate a strong trajectory in practical AutoML systems, with growing attention to tabular machine learning, foundation models integration, and addressing real-world constraints in optimization. His work consistently bridges theoretical advances with practical implementations through several widely-used open-source projects. Notable achievements include: 1st place in the warmstarting-friendly leaderboard of the BBO NeurIPS challenge Winner of the 2nd AutoML challenge Winner of the kdnuggets blog contest on AutoML Feurer is actively mentoring and teaching, having advertised PhD positions focused on AutoML, optimization, and benchmarking. He co-founded the Open Machine Learning Foundation supporting OpenML.org. His upcoming move to TU Dortmund as an assistant professor in AutoML and Optimization signals continued growth in his academic career while maintaining his research focus on making machine learning more accessible and rigorous.

Ilker Yildirimمشاهده پروفایل

استادیار

• Computational Modeling
• Visual Perception
• Cognitive Neuroscience
• +۵ مورد دیگر

Ilker Yildirim is an Assistant Professor of Psychology at Yale University, where he leads the Cognitive and Neural Computation Lab (CNCL). He received his Ph.D. from the University of Rochester in 2014. His research focuses on understanding how perception transforms raw sensory signals into meaningful representations of objects and scenes through computational modeling approaches. His research interests include: Computational modeling of visual perception and cognition Intuitive physics and physical reasoning Bayesian inference and probabilistic models in cognition Integration of graphics and physics engines in cognitive modeling Neural mechanisms of object representation Attention and resource allocation in dynamic scenes Yildirim's lab develops computational frameworks that bridge cognitive processes with neural mechanisms, using tools including probabilistic models, simulation engines, and deep learning. His work often involves testing these models through behavioral and neural experiments to create unified accounts of perception and cognition. His recent publications reveal a strong focus on how humans perceive physical properties of objects, particularly soft materials and liquids, and how attention dynamically allocates resources during scene perception. Among his notable achievements is receiving an NSF CAREER award for his project "CAREER: CompCog: Reverse-engineering neural mechanisms of object cognition with multilevel computational modeling," which will run from 2025 to 2030. His Nature Human Behaviour paper by Qi Lin was featured on CBS News, Germany's NZZ, and Wired Italy. Yildirim mentors a diverse group of graduate students and postdocs working on various aspects of perception, cognition, and computational modeling. His students have received prestigious awards including the Jane Olejarczyk Award and the Leonard J. Savage Prize.

• Affective Computing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dr A. I. Shihab is a Senior Lecturer at Kingston University's Faculty of Engineering, Computing and the Environment, Department of Networks and Digital Media. He teaches programming languages (C++/Java), data structures, web development, and AI/machine learning. His research focuses on affective computing and machine learning applications including: Acoustic event detection in sports environments Audio signal analysis for tennis match modeling Multi-camera visual surveillance systems Medical imaging analysis using fuzzy clustering techniques Publications demonstrate expertise in combining audio/video modalities for sports analytics (tennis rallies, court-shots) and developing Markov models for sound event sequence analysis. Contact: a.shihab@kingston.ac.uk

Patricio Antonio Velaمشاهده پروفایل

استاد

• Geometric Estimation and Control
• Computer Vision
• Robotics
• +۴ مورد دیگر

Patricio Vela is a Professor at the School of Electrical and Computer Engineering , Georgia Institute of Technology , specializing in geometric perspectives for control theory and computer vision. His research focuses on computer vision integration for semi-autonomous systems, nonlinear control of robotic systems, and biologically inspired mechanics. Education: B.S. (1998) and Ph.D. (2003) from Caltech Research Areas: Autonomy, Robotics, Computer Vision, Control Theory Key Contributions: Geometry-based control systems, visual navigation frameworks, SLAM benchmarking Recent publications highlight advances in vision-based motion planning , 6D pose tracking , and safe navigation policies for autonomous robots. His work bridges geometric mechanics with deep learning for robust perception and control in dynamic environments. Awards: HENAAC Most Promising Engineer (2005) Contact: pvela@gatech.edu | Office: TSRB 441 | Phone: 404.894.8749

Gail E. Josephمشاهده پروفایل

استاد

• Early Childhood Education
• Child Development
• Social-Emotional Learning
• +۳ مورد دیگر

Gail E. Joseph is a Professor in the College of Education at the University of Washington, with affiliations in Early Childhood & Family Studies and Learning Sciences & Human Development. She teaches courses, advises students, and conducts research on early care and education, focusing on child care quality, social-emotional learning, teacher education, and technology integration. Ph.D., University of Washington Her research projects include statewide surveys on early childhood workforce conditions, studies on digital professional learning tools like Circle Time Magazine, and evaluations of coaching interventions (e.g., FIND in Childcare) to improve teacher-child interactions. She co-created resources such as Teacher Time and the EarlyEdU Alliance, which aims to enhance early childhood education through accessible bachelor’s degrees. Her publications span topics like social-emotional curricula, behavioral interventions, and inclusive education frameworks. She has held leadership roles as Principal Investigator (PI) of the Head Start Center for Inclusion and Co-PI of the National Center for Quality Teaching and Learning (NCQTL). 2018 David R. Thorud Leadership Award (University of Washington) She currently serves as Executive Director of Cultivate Learning at the University of Washington, advancing professional development and quality improvement initiatives nationwide.

Yan Liankeمشاهده پروفایل

استاد

• Chinese Literature
• Creative Writing
• Literary Theory
• +۸ مورد دیگر

Prof. Yan Lianke (born 1958) is a renowned contemporary Chinese writer and academic. He currently holds the IAS Sin Wai Kin Professor of Chinese Culture at Hong Kong University of Science and Technology and serves as Professor at the School of Liberal Arts of Renmin University of China. His work spans novels, short stories, and literary theory, often exploring political, historical, and social themes through a critical lens. Education: BA in Political Education (Henan University, 1985), MA in Literature (PLA Academy of Art, 1991) Awards: Lu Xun Literature Prizes, Franz Kafka Prize, Newman Prize, and international recognition for his humanistic and socially conscious writing Yan’s research and writing focus on the intersection of literature, memory, and truth-telling in authoritarian contexts. His theoretical work, such as the 2020 lecture On Memory , critiques the erasure of personal and collective recollection in modern China. His novels, including Four Books and Dreams of Ding Village , are celebrated for their allegorical depth and spiritual realism. Scientific awards and honors include: 2014 Franz Kafka Prize (first Chinese recipient) 2017 Dream of the Red Chamber Award 2021 Newman Prize for Chinese Literature 2022 Lee Hochul Prize for Peace 2024 Nebula Award for Contribution to Global Chinese Literature Yan’s teaching and creative writing programs at HKUST and Renmin University emphasize the ethical role of literature in documenting human experiences and challenging historical amnesia. His work has been translated into over 30 languages, with more than 150 foreign publications.

Beth M. Carterمشاهده پروفایل

استادیار

• Premodern Japanese Literature
• Mourning Rituals in Literature
• The Tale of Genji
• +۱ مورد دیگر

Beth M. Carter is an Assistant Professor of Japanese at Case Western Reserve University, specializing in premodern Japanese literature. Her research focuses on mourning rituals and practices in The Tale of Genji and related texts. Education: B.A., Sarah Lawrence College; M.A., Johns Hopkins University; M.A. and Ph.D., University of Pennsylvania Her work introduces the concept of "mourning poetics," analyzing the interplay between post-death rituals and lament poetry in Japanese literary traditions. Secondary research explores women's voices in historical Japanese texts. Recent publications (2016–2025) examine corporeal expressions of grief, regional symbolism in mourning scenes, and the evolution of ritual practices in classical Japanese narratives. Scientific Awards Fulbright Graduate Research Fellowship (Kyoto, Japan 2013, 2015) Blakemore Freeman Fellowship for Advanced Asian Language Study (Yokohama, Japan 2014) Current affiliations include Department of Japanese, Guilford House 313, and Phone: 216.368.2102.

Jeffrey Rossmanمشاهده پروفایل

دانشیار

• Russia/USSR
• Modern Europe
• Communism
• +۶ مورد دیگر

Jeffrey Rossman is an Associate Professor at the University of Virginia , affiliated with the Department of History and serving as Director of the Center for Russian, East European, and Eurasian Studies . His work bridges historical analysis with cultural and literary studies, focusing on Russia/USSR, Modern Europe, Communism, Genocide, Espionage, and Jewish Cultural Studies. Education: Ph.D., University of California, Berkeley, 1997 A.B., Harvard University, 1989 His research explores worker resistance under Stalin, the intersection of Jewish identity and German literature, and the role of translation in cultural exchange. He has authored key works on Soviet labor movements and Holocaust memory, blending historical narratives with literary theory. Jeffrey’s recent publications and Google Scholar contributions highlight trends in 20th-century European history , Yiddish-German literary dynamics , and translation as a tool for identity formation . His work spans comparative literature, cultural memory, and diaspora studies, emphasizing interdisciplinary approaches. Scientific Awards: ACLS Collaborative Research Fellowship (2013-15) Harry Frank Guggenheim Foundation Research Grant (2013-15) Multiple grants from the University of Virginia’s College of Arts & Sciences and Faculty Summer Research Grant program Fulbright-Hays and IREX fellowships for international research As an educator, Rossman has taught courses such as Genocide: A Global History and Stalinism , mentoring students in historical and literary analysis. His lab, the Center for Russian, East European, and Eurasian Studies, fosters research on Soviet history, Jewish cultural studies, and transnational literary exchange.

• Civil Engineering
• Construction Management
• Computer Vision
• +۶ مورد دیگر

Mani Golparvar Fard is a Professor at the University of Illinois at Urbana-Champaign, holding joint appointments in the Siebel School of Computing and Data Science and the Department of Civil and Environmental Engineering. He also contributes to the Technology Entrepreneur Center. His research focuses on integrating artificial intelligence, computer vision, and data analytics to advance construction management, infrastructure monitoring, and automation. Key areas include BIM integration, reality capture systems, and deep learning-based progress tracking. His work emphasizes automated construction progress monitoring through semantic segmentation, vision-language models, and UAV-based data collection. He has pioneered methods like Scan2BIM-NET for converting point clouds into BIM models and developed frameworks for worker safety analysis using machine learning. Awards: Walter L. Huber Civil Engineering Research Prize (2018) Daniel W. Halpin Award for Scholarship (2016) Advising & Grants: While no specific grant details are provided, his research is supported by collaborations with industry and government initiatives, such as the Japanese national bridge inspection project. He advises a team focused on AI-driven construction solutions and maintains active partnerships with engineering firms. Labs & Teams: Leads research groups in vision-based construction analytics, automated scheduling systems, and BIM integration. His work is disseminated through platforms like the VisualSiteDiary system and the InstaDam open-source platform for structural damage analysis.

• Machine Learning
• Artificial Intelligence
• Data Science
• +۶ مورد دیگر

Chris J. Maddison is an Assistant Professor at the University of Toronto, holding joint appointments in the Department of Computer Science and the Department of Statistical Sciences. He is also a CIFAR AI Chair at the Vector Institute and a member of the ELLIS Society. Maddison earned his DPhil from the University of Oxford and previously worked as a Senior Research Scientist at Google DeepMind and a member at the Institute for Advanced Study. His research focuses on advancing machine learning methodologies, particularly in leveraging data’s natural structure for efficient learning, with applications in drug discovery, causal inference, and AI safety. Education: DPhil in Computer Science, University of Oxford His research interests span machine learning, AI safety, reinforcement learning, and the integration of logical reasoning into large language models. Maddison has contributed to foundational work on gradient estimation techniques and was a key member of the AlphaGo project. He actively explores how statistical structures in real-world data influence AI capabilities. Recent publications emphasize evaluating conversational agents, mitigating AI safety risks, and enhancing logical reasoning in LLMs. His work bridges theoretical advancements with practical applications, such as code generation and multi-agent systems. Awards: NeurIPS Best Paper Award (2014), Open Philanthropy AI Fellowship Maddison advises multiple PhD students and postdoctoral researchers, fostering collaborations across academia and industry. His former advisees now hold roles at institutions like OpenAI, Stanford, and Magic AI. He teaches advanced courses in machine learning and statistical methods, including CSC 2541 (Large Models) and STA 314 (Machine Learning). Maddison is affiliated with the Schwartz Reisman Institute for Technology and Society, extending his impact to societal implications of AI. His lab’s interdisciplinary approach combines algorithmic innovation with real-world problem-solving.