جستجوی استاد راهنمای دانشگاهی

Dr. Edward Johns is an Associate Professor in the Department of Computing at Imperial College London and Director of the Robot Learning Lab. He specializes in robot learning, focusing on enabling robots to learn tasks through imitation and language-based reasoning. His expertise spans robotics, machine learning, and computer vision, with a particular emphasis on manipulation tasks requiring physical interaction with objects. He holds a BA and MEng from the University of Cambridge and a PhD from Imperial College London. Prior to his current role, he was a postdoc at UCL, a founding member of the Dyson Robotics Lab, and led the robot manipulation team there. He also served as Head of Robot Learning at Dyson (part-time, 2021–2022). His research has produced state-of-the-art capabilities such as one-shot imitation learning and language-driven task execution. Key areas of interest include sim-to-real transfer, self-supervised learning, and adaptive robotic systems. His work bridges foundational AI research with practical robotics applications, emphasizing real-world deployment and human-robot collaboration. Dr. Johns has published over 60 peer-reviewed papers, with over 4,000 citations, and has received prestigious awards including the UK-RAS Early Career Award (2023) and the Best Conference Paper Award at ICRA (2024). He is also actively involved in industry through advisory roles for robotics and AI startups. His teaching includes graduate courses on reinforcement learning and robot learning, and he collaborates extensively with labs such as the Robotics Forum and the Artificial Intelligence Network at Imperial College.

• Robot Learning
• Robot Manipulation
• Artificial Intelligence
• +۴ مورد دیگر

Joseph Alejandro Gallego Mejia is an Assistant Teaching Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. He holds a PhD with meritorious distinction in Systems and Computing Engineering from the National University of Colombia, along with a Master’s and dual Bachelor’s degrees in Systems and Computing Engineering and Industrial Engineering. PhD in Systems and Computing Engineering, National University of Colombia (Meritorious Distinction) Master of Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Industrial Engineering, National University of Colombia His research focuses on artificial intelligence, machine learning, computer vision, quantum machine learning, natural language processing, and cybersecurity. He explores robustness estimation, anomaly detection, incremental learning, and scalable software architectures for AI systems. His work bridges theoretical foundations and practical applications in health, remote sensing, and edge computing. The recent publications reflect a strong trend in interdisciplinary AI research, combining machine learning with quantum computing, cybersecurity, and natural language understanding. His work spans domains such as satellite imagery analysis, medical diagnostics, IoT security, and conversational AI, demonstrating a commitment to scalable and robust intelligent systems. Keywords across publications include Computer Science, Machine Learning, Quantum Computing, and Cybersecurity, with subfields ranging from adversarial robustness to hybrid quantum-classical models. Scientific distinctions include: PhD with meritorious distinction, National University of Colombia Postdoctoral fellow, Frontier Development Lab (Trillium), supported by NASA and ESA He has served as a reviewer for top-tier journals and conferences including Neurocomputing, IEEE Access, Radioscience, NeurIPS, and NLDL. Though no formal grants are listed, his postdoc was funded by NASA and ESA, indicating significant external support. He teaches courses in programming, data science, machine learning, deep learning, NLP, and software engineering. He founded the tech company Sammu and mentors students through instruction and research supervision. He is actively involved in research and teaching, contributing to innovative programs in AI and computing education. His lab and team affiliations are not explicitly stated, but his work suggests collaboration with AI, quantum computing, and cybersecurity research groups.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۱۲ مورد دیگر

Dr. Rani Moran is a Lecturer in Psychology at Queen Mary University of London's School of Biological and Behavioural Sciences. She is affiliated with the Centre for Brain and Behaviour. Her research focuses on decision-making, memory, and learning mechanisms, employing methods like computational modeling, neuroimaging, and pharmacological interventions. Key interests include reinforcement learning, cognitive maps, and exploration-exploitation dilemmas. Her work integrates experimental designs with advanced statistical analysis to understand flexible behavioral control. Recent studies explore model-based vs. model-free learning, credit assignment mechanisms, and disinformation's impact on learning biases. She has published in top journals such as Psychological Review and Nature Communications . Dr. Moran collaborates on projects involving neurocomputational models of confidence, meta-cognition, and social learning. Her research aims to develop interventions for optimizing cognitive processes, with applications in mental health and decision-making contexts.

• Decision Making
• Reinforcement Learning
• Cognitive Maps
• +۵ مورد دیگر

Zhen Yi Wu is a Visiting Assistant Professor at the University of Texas at Dallas (UT Dallas), affiliated with the School of Economic, Political and Policy Sciences. They currently serve as the program leader for the Huayu BEST Scholarship Program, a partnership between UT Dallas and Taiwan’s Ministry of Education aiming to promote Mandarin language learning in Taiwan among international students. In this role, Wu oversees scholarship promotion, application guidance, pre-departure preparation, and student support during their immersive experiences in Taiwan. They collaborate with stakeholders to secure resources, organize cultural exchange activities, and evaluate program effectiveness to enhance its impact on students' Mandarin proficiency and cultural understanding. Teaching focuses include specialized courses such as State and Society in Taiwan , Business Chinese , and Advanced Chinese I , reflecting expertise in both regional studies and language education. Their work bridges academic rigor with practical cultural immersion, emphasizing Taiwan’s sociopolitical context and linguistic heritage.

• Taiwanese Studies
• Political Science
• Language Education
• +۳ مورد دیگر

Giuseppe Bruno Averta is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is affiliated with the College of Computer, Film and Mechatronics Engineering and contributes to national and international research in artificial intelligence and robotics. Averta has held a Visiting Researcher position at the Massachusetts Institute of Technology (MIT) from January to June 2019. His research interests include Computer Vision, Deep Learning, Robotics, Neural Architecture Search, Egocentric Vision, Embodied Intelligence (Edge/Tiny ML), and Human-Robot Collaboration . His work is aligned with ERC sectors in Artificial Intelligence, Machine Learning, and Robotics, and contributes to UN SDGs such as Good Health and Well-being, Industry Innovation and Infrastructure, and Responsible Consumption and Production. The recent publication trends highlight his focus on vision-language models (e.g., CLIP), egocentric action recognition, efficient neural architectures (e.g., BiSeNet, MaskFormer), and robust deep learning. His research bridges theoretical advances with practical robotics applications, including grasping and manipulation. Scientific Awards and Recognitions: Georges Giralt PhD Award (euRobotics AISBL, 2021) Wiley Best Reviewer (Wiley, Italy, 2021) Best Paper Award, ICUMT 2015 (2017) Fellow, ELLIS Network of Excellence (2022–) Fellow, DAAD AInet (2022–) DAAD AInet Fellowship Advising and Grants : Averta supervises multiple PhD students in the Artificial Intelligence and Computer and Systems Engineering doctoral programs at Politecnico di Torino. He is involved in teaching at both the master’s and doctoral levels, including courses on Robot Learning and Machine Learning and Deep Learning. He is also a co-inventor on a national and international patent for a method and algorithm for the automatic design of neural networks through machine learning, indicating active research funding and innovation. Labs and Research Groups : He is a member of the SmartData@PoliTO center and contributes to research in the VANDAL PoliTO lab (as indicated by his student Davide Buoso). His work is deeply integrated with teams working on egocentric vision, embodied AI, and neural architecture search.

• Computer Vision
• Deep Learning
• Robotics
• +۹ مورد دیگر

Katrin Erk is a Professor in both the Linguistics Department and Computer Science Department at the University of Texas at Austin. She is part of the UT Austin NLP and computational linguistics research groups. Her work focuses on computational semantics, particularly exploring word embeddings and contextualized word embeddings to study polysemous words and their meanings in context. She also investigates narrative schemas and their integration with sentence-level meaning representations, often employing logic-based frameworks. Research interests include understanding the nuanced and graded nature of word meanings, how these interact with sentence structures, and the theoretical implications of using distributional models in semantics. She has contributed to advancing methods that bridge formal semantic theories with data-driven approaches derived from large text corpora. Office hours for Fall 2024 are listed, and her contact includes an address at Patton Hall (RLP) and an email. No specific grants or awards are mentioned in the provided text.

• Computational Linguistics
• Computational Semantics
• Natural Language Processing
• +۴ مورد دیگر

Raju Vatsavai is an Associate Professor in the Department of Computer Science at North Carolina State University, affiliated with the Center for Geospatial Analytics. He joined NC State in 2014 as part of the Chancellor’s Faculty Excellence Program cluster hire in Geospatial Analytics. Education: PhD and MS in Computer Science from University of Minnesota Prior Roles: Lead Data Scientist at Oak Ridge National Lab, roles at University of Minnesota, IBM Research, AT&T Labs, and C-DAC (India) His research in geospatial analytics spans big data management , spatiotemporal data mining , deep learning for remote sensing , and high-performance computing , with applications in national security, climate change, and crop monitoring. Recent work includes deep learning frameworks for cloud imputation , multi-sensor satellite data harmonization , and transfer learning applications in crop classification . He has been a leading investigator on grants from the National Geospatial-Intelligence Agency, Department of Energy, and Department of Homeland Security. Labs: Associate Director of the Center for Geospatial Analytics Expertise: Spatial computing, Earth observation, nuclear proliferation detection via remote sensing

• Geospatial Analytics
• Big Data Management
• Data Mining
• +۵ مورد دیگر

Svante Lindberg is a Senior Lecturer and Associate Professor in the Department of Languages at Åbo Akademi University’s Faculty of Humanities, Psychology and Theology. He holds a Doctor of Philosophy and Licentiate of Philosophy from Stockholm University, a Master of Philosophy from Uppsala University, and a Diplôme d'études approfondies from Université de Nice. His academic work spans multiple institutions, including substitute roles at Stockholm University and guest lectures at the University of Groningen. Doctor of Philosophy, Stockholm University Licentiate of Philosophy, Stockholm University Master of Philosophy (Linguistics), Uppsala University Bachelor of Philosophy, Stockholm University Diplôme d'études approfondies, Université de Nice His research focuses on contemporary French-language literature, particularly from Quebec, migration literature, world literature, and the works of Michel del Castillo. He also investigates 18th-century French cosmopolitan networks and literary didactics. His doctoral thesis analyzed narrative identity in Quebecois novels, and he edited a significant anthology on migrant literature in Quebec and Scandinavia. He publishes regularly in French, Swedish, and English, contributing to journals and academic volumes on literary theory, translingualism, and cultural identity. The trend in his recent publications shows a strong engagement with narrative identity, translingualism, and the cultural representation of the 'South' in literature. His work bridges French, Scandinavian, and global literary contexts, with a methodological focus on comparative and transcultural analysis. He frequently explores themes of migration, trauma, and religious identity across historical and contemporary texts. His scientific awards include: Guldkanten (2018) Harry Elvings legat (2018, twice) Åbo Akademi Jubileumsfond 1968 (2012) Åbo Akademis mobilitetsstipendium (2010) Lindberg supervises bachelor's, master's, and doctoral theses and has served as an examiner and academic advisor. He is actively involved in academic service, including organizing conferences, peer reviewing, and participating in recruitment committees. He has contributed to the cultural impact of his research through studies on French imagery in Scandinavian literature and has engaged in international academic collaboration, particularly with institutions in the Netherlands and Norway. His work aligns with UN Sustainable Development Goals related to education and cultural understanding. He is a member of academic networks and has hosted visiting scholars, participated in numerous conferences, and contributed to editorial boards. His recent activities include presentations on Michel del Castillo and participation in the NIC Conference 2023 on intercultural communication.

• Contemporary French-language Novel
• Migration Literature
• World Literature
• +۱۲ مورد دیگر

Irina Rish is a Full Professor at the Université de Montréal and a core academic member of Mila – Quebec Artificial Intelligence Institute, where she leads the Autonomous AI Lab. She holds a Canada Excellence Research Chair (CERC) and a CIFAR AI Chair, reflecting her leadership in foundational AI research. Her work is supported by major initiatives, including the U.S. Department of Energy’s INCITE project on Summit and Frontier supercomputers. PhD in AI, University of California, Irvine MSc in AI, University of California, Irvine MSc in Applied Mathematics, Moscow Gubkin Institute Her research focuses on machine learning, neural scaling laws, emergent behaviors in foundation models, continual learning, robustness, and neuroscience-inspired AI . She explores how AI systems can become more general, flexible, and aligned with human cognition. Her recent work investigates training dynamics in large language models, efficient pruning techniques, and the development of time-series foundation models. The analysis of her recent publications reveals a strong focus on scaling behaviors, continual adaptation, and robustness in AI systems . Her work spans theoretical understanding of training dynamics (e.g., zero-sum learning), practical optimization methods, and applications in climate modeling and mental health. She emphasizes open science, leading open-source projects and co-founding Nolano.ai to build efficient, compressed foundation models. Canada Excellence Research Chair (CERC) CIFAR AI Chair IBM Eminence & Excellence Award (2018) IBM Outstanding Innovation Award (2018) IBM Outstanding Technical Achievement Award (2017) IBM Research Accomplishment Award (2009) Irina Rish advises a large group of PhD and Master’s students across Université de Montréal, McGill, and Concordia. She leads major research grants and collaborates internationally on HPC-based AI research. She is also the co-founder and CSO of Nolano.ai, driving innovation in efficient AI systems. She leads the Autonomous AI Lab, which focuses on building large-scale foundation models, understanding neural scaling laws, and developing bio-inspired learning systems. She actively organizes reading groups on scaling, continual learning, and out-of-distribution generalization, fostering a collaborative research environment.

• Machine Learning
• Neural Scaling Laws
• Emergent Behaviors in AI
• +۱۳ مورد دیگر

Zubin Punthakee is an Associate Professor in the Department of Endocrinology & Metabolism within the Faculty of Medicine at McMaster University. His scholarly activity spans over 30 years with 97 publications in the last 10 years, demonstrating sustained research productivity in diabetes, endocrine disorders, and metabolic health. Dr. Punthakee's research interests focus on several key areas in endocrinology and diabetes care. He has made significant contributions to understanding type 2 diabetes remission through metabolic interventions, transition care for adolescents with type 1 diabetes moving to adult care systems, hypoparathyroidism management and skeletal health outcomes, and health disparities among South Asian populations. His work often involves large-scale clinical trials, registry-based research (particularly the Canadian National Hypoparathyroidism Registry), and implementation science approaches to improve diabetes care delivery. Analysis of his recent publications reveals a strong focus on diabetes remission strategies, transition care quality improvement, and skeletal complications of endocrine disorders. His work bridges clinical endocrinology with health services research, often examining how to translate evidence into practice through audit and feedback mechanisms and structured transition programs. Dr. Punthakee has been actively involved in numerous clinical trials including the REMIT-iGlarLixi trial examining diabetes remission, and has contributed to major clinical practice guidelines for diabetes management across the lifespan. His work with the Canadian National Hypoparathyroidism Registry has produced multiple publications characterizing the etiology, clinical manifestations, and management strategies for hypoparathyroidism. His research frequently addresses health disparities, particularly among South Asian populations in Canada, examining factors like vaccine effectiveness, dietary patterns, and cardiovascular risk. This work demonstrates his commitment to addressing health equity through rigorous clinical research.

• Endocrinology
• Diabetes Research
• Metabolism
• +۵ مورد دیگر

Michael J. Spivey is a Professor of Cognitive Science at the University of California, Merced, affiliated with the School of Social Sciences, Humanities and Arts. His research focuses on understanding human cognition through embodied and dynamic systems approaches, with particular expertise in eye-tracking methodologies and real-time language processing. As a faculty member in the Cognitive and Information Sciences department, he contributes to interdisciplinary research that bridges psychology, linguistics, and neuroscience. Dr. Spivey's educational background includes: Ph.D. in Brain and Cognitive Sciences from the University of Rochester (1996) M.A. in Brain and Cognitive Sciences from the University of Rochester (1995) B.A. from the University of California, Santa Cruz (1991) His research interests span psycholinguistics, visual perception, sensorimotor processing, embodied cognition, and dynamical systems theory. Dr. Spivey investigates how cognitive processes unfold in real-time through eye movements and other behavioral measures, challenging traditional modular views of cognition. His work emphasizes the continuous interaction between perception, action, and cognition, demonstrating how language processing is deeply embedded in our sensorimotor experiences. He has made significant contributions to understanding the time course of language comprehension, the role of visual context in linguistic processing, and the dynamic nature of cognitive representations. Analysis of Dr. Spivey's recent publications reveals a strong focus on embodied and dynamic approaches to cognition. His work spans diverse areas including eye-tracking and mouse-tracking methodologies, team cognition, creativity research, bilingual language processing, and the application of foraging theory to cognitive processes. A recurring theme across these publications is the investigation of real-time cognitive dynamics using continuous behavioral measures. His research increasingly incorporates ecological approaches, examining cognition in more naturalistic contexts while maintaining experimental rigor. The interdisciplinary nature of his work is evident in collaborations across psychology, linguistics, neuroscience, and even music cognition. Dr. Spivey is affiliated with the Center for Human Adaptive Systems and Environments and collaborates with researchers at Western University, Northwestern University, Brown University, and UCLA. His work with students likely focuses on training in advanced methodologies for measuring real-time cognitive processes.

• Psycholinguistics
• Visual Perception
• Sensorimotor Processing
• +۵ مورد دیگر

Mor Naaman is a Professor at Cornell University specializing in Human-Computer Interaction, Social Media Analysis, and AI-Mediated Communication. With a prolific publication record spanning over two decades, his research focuses on how people interact with social computing systems, particularly examining trust, information exposure, and community dynamics in online environments. His research interests span several interconnected domains: Human-Computer Interaction with emphasis on social media platforms, AI-Mediated Communication examining how AI systems influence human communication patterns, Misinformation Detection and analysis of information ecosystems, Location-Based Social Networks and community awareness systems, and Trust in Online Systems. His work often bridges technical and social aspects of computing, with publications appearing in top venues like CHI, CSCW, and ICWSM. Analysis of his recent publications (2022-2025) reveals a strong focus on the emerging challenges of AI in social contexts, particularly examining AI-generated content, trustworthiness evaluations of AI systems, and the social implications of generative AI. His research shows consistent interest in understanding community dynamics across platforms like Reddit, Facebook, and Twitter, with recent work examining hyperlocal communities, news consumption patterns, and cross-cultural aspects of AI-mediated communication. Mor Naaman has mentored numerous students and collaborators, including Xiao Ma, Yiqing Hua, and Marianne Aubin Le Quéré, who frequently appear as co-authors on his publications. His work demonstrates strong interdisciplinary connections between computer science, social science, and communication studies. His research methodology typically combines large-scale data analysis of social media platforms with user studies and system design, contributing both theoretical insights and practical applications for designing more effective social computing systems. Recent projects have examined AI writing assistants, community governance of AI content, and the cultural implications of AI-mediated communication.

• Human-Computer Interaction
• Social Media Analysis
• AI-Mediated Communication
• +۵ مورد دیگر

Brian Uzzi holds the Richard L. Thomas Professorship of Leadership and Organizational Change at Northwestern University's Kellogg School of Management. He serves as Co-Director of the Northwestern Institute on Complex Systems (NICO) and The Ryan Institute on Complexity (RIC), with additional appointments in Sociology at Weinberg College of Arts and Sciences and Industrial Engineering and Management Sciences at McCormick School of Engineering. His educational background includes a PhD in Sociology (1994) from State University of New York, Stony Brook, an MS in Organizational Psychology (1989) from Carnegie Mellon University, and a BA in Business Economics (1982) from Hofstra University. Prior to academia, he worked as a carpenter and musician. Research Focus: Dr. Uzzi's work centers on social networks, complexity theory, and the concept of embeddedness—the idea that individuals and organizations operate within social networks that significantly influence their achievements, economic activity, and creative output. His research examines how AI facilitates mind-machine partnerships and how network structures affect scientific collaboration, innovation, and leadership. His work spans sociology, management science, computer science, and ecology, with practical applications in business and government. His recent publications reveal a strong focus on the science of science, exploring topics like innovation abandonment, social media's role in political violence, promotional language in scientific grants, and gender diversity's impact on scientific creativity. The research consistently applies network science to understand patterns of human achievement and organizational performance. Euler Award recipient (2022) from the Network Science Society Member of the American Academy of Arts and Sciences Network Science Society Fellow Multiple 'Professor of the Year' awards at Kellogg World Wide Web Best Paper Prize (2016-2017) As an educator, Dr. Uzzi has developed innovative courses on network science for managers and executives. His consulting work extends to companies and governments worldwide, applying network science principles to real-world challenges in leadership, organizational design, and AI strategy. His research has been funded by DARPA, NSF, and other foundations, demonstrating its significance across multiple disciplines.

• Social Networks
• Complexity Theory
• Embeddedness
• +۵ مورد دیگر

Liadh Kelly is an Assistant Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. She supervises PhD students in applied artificial intelligence, focusing on intelligent search, ubiquitous computing, and multimodal information access. She is affiliated with the ADAPT SFI Research Centre, SFI Centre for Research Training in Foundations of Data Science, and Human Health Institute. BSc in Computer Science MSc (Research) in Computer Science PhD in Computer Science Her research explores context-sensitive retrieval and evaluation methodology in AI-driven systems. Key areas include ubiquitous computing for personal data analysis, deep learning classification for mental wellness indicators, and multimodal lifelogging integration. Recent publications focus on urban mental wellbeing classification , contextual cue analysis , and AI-driven health search systems . Articles address smart city applications , consumer health search , and cross-lingual medical retrieval . Professional roles include Doctoral Consortium Chair at ECIR 2023 and Programme Committee member for SIGIR and ICWSM conferences. She leads grants for 4-year PhD studentships with stipend and fee coverage.

• Applied Artificial Intelligence
• Intelligent Search
• Ubiquitous Computing
• +۳ مورد دیگر

Anja Kraus is a Professor in Arts and Culture Education at Stockholm University, Department of Teaching and Learning. She has held academic positions at the University of Education Ludwigsburg (2003-2013), Linnaeus University Växjö (2013-2019), and joined Stockholm University in 2018. Her academic journey began with studies in Philosophy and Educational Sciences at Free University Berlin and Arts Education at the University of the Arts Berlin, Germany. Her research focuses on Pedagogical Anthropology, with special emphasis on tacit knowledge, corporeality, aesthetic education, and multimodal learning. She has developed systematic approaches to understanding tacit knowing in educational contexts, particularly examining how corporeality, aesthetic learning, and inclusivity function in schools. Her work bridges phenomenological, ethnographical, and body-phenomenological approaches with practical educational applications. She has made significant contributions to understanding how materiality, performativity, and imaginaries shape educational practices. Her recent publications reveal strong trends in embodiment studies, with particular attention to kinesthetic learning, spatial pedagogy, and the relationship between aesthetics and sustainability. Her work increasingly explores educational practices within the Anthropocene context, examining how arts education can address environmental concerns through embodied approaches. The recurring theme across her publications is the exploration of how tacit knowledge manifests in educational settings and how this understanding can transform teaching practices. As head convenor of the international scientific network 'Tacit Dimensions of Pedagogy,' she has organized numerous workshops and conferences addressing pedagogical terminologies across languages. Her collaborative projects span Scandinavia, Europe, Asia, and North and South America, demonstrating her commitment to transcultural approaches in educational research. Her teaching spans multiple languages (German, English, Swedish, Spanish) and covers diverse areas including Classroom Education, Cultural and Media Education, Sciences of Bildung, Elementary Education, and Vocational Training. Her pedagogical approach emphasizes practice-oriented competence, inclusive school development, and aesthetic learning environments with a comparative perspective.

• Pedagogical Anthropology
• Tacit Knowledge
• Corporeality in Education
• +۷ مورد دیگر