جست‌وجوی استاد و پژوهشگر

• Urban Policy
• Sustainable Development
• Governance
• +۳ مورد دیگر

Ilari Karppi is a University Lecturer at Tampere University’s Faculty of Management and Business, specializing in Administrative Studies. His research focuses on urban policy, governance, and sustainable development, with particular emphasis on urban safety, event management, and the integration of technology in urban environments. He has been actively contributing to interdisciplinary studies addressing challenges in urban planning, crisis management, and public-private collaboration. Key research interests include smart urban safety frameworks, the role of technology in public spaces, and the complexities of multi-actor governance systems. His work frequently explores how urban design and policy can enhance safety, equity, and sustainability in rapidly evolving cities. Recent studies have examined perceptions of security in mass events, machine learning applications in crisis simulations, and boundary objects for sustainable urban development. Key Themes: Urban security, governance innovation, sustainable urban planning, technology adoption in public spaces, event management, and collaborative governance models. Notable Contributions: Analysis of simulated trust in security exercises, integration of eye-tracking systems in urban planning, and evaluation of transit equity in urban mobility. His publications span over two decades, reflecting a deep engagement with regional development, policy push dynamics, and institutional stability in globalized contexts. Though no formal awards or grants are listed, his extensive academic output underscores his influence in urban studies and administrative sciences.

Yang Huaمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Visual Recognition
• +۳ مورد دیگر

Dr. Yang Hua is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on computer vision, machine learning, and their practical applications, including visual recognition, robust learning with limited data, and hardware-aware systems. He has supervised multiple PhD students in areas like generative adversarial networks and domain adaptation. Affiliations: Institute of Electronics, Communications & Information Technology; Co-Investigator in multiple research projects (e.g., R5159ECS, R2733CPH). Teaching: Courses include 'How to do Research' and 'Database and Programming Fundamentals' for MSc and PhD students. Research Interests: Dr. Hua's work addresses challenges in visual recognition, domain adaptation, and federated learning. He emphasizes real-world applications and has contributed to competitions like PASCAL VOC Challenge and VOT-TIR2015. Awards: Recognized with Queen's University STAR award (2019), VOT-TIR2015 tracker win, and multiple PASCAL VOC Challenge wins. His research has been funded by Microsoft Research and European conferences. Grants & Projects: Includes 'Artificial Intelligence for Vision-Based Navigation' and collaborations on medical imaging (e.g., AMD diagnosis). He leads projects on federated learning and domain adaptation. Labs/Teams: Active in the Institute of Electronics, Communications & Information Technology, contributing to distributed AI and biomedical applications.

May Helen Uppstad Austadمشاهده پروفایل

پژوهشگر

• Vocational Education
• School-to-Work Transition
• Mastery Learning Models
• +۵ مورد دیگر

May Helen Uppstad Austad serves as a Researcher at the University of Agder's Department of Pedagogy within the Faculty of Humanities and Pedagogy. She is currently pursuing a public PhD through a collaborative research project with Lindesnes Municipality focused on working life education in lower secondary schools. Her role integrates academic research with practical municipal implementation, emphasizing co-creation with educators and students. Her research centers on vocational pedagogy and school-to-work transitions, with particular expertise in mastery models ( mestringsmodell ), dropout prevention, and transversal skills development. She investigates how working life subjects can be effectively embedded within standard secondary curricula through action research methodologies, prioritizing inclusive practices for diverse learners and vulnerable youth populations. Analysis of her 15 most recent publications (2023-2025) reveals consistent focus on practical implementation challenges in Norwegian secondary education. Key themes include resource allocation for working life subjects, development of localized curricula through teacher-student collaboration, and frameworks for building workplace relationships to support school-work transitions. Her work demonstrates strong municipal-academic partnership approaches, with recurring emphasis on mastery-oriented assessment and adaptation strategies for at-risk students. Austad actively disseminates findings through conferences like NordYrk and Profes Spring PhD symposium, though no formal scientific awards are documented. Her research is conducted within a project team involving Lindesnes Municipality personnel, teachers, and students, focusing on real-world application rather than theoretical development. While no formal advisees are listed, her collaborative methodology involves significant knowledge exchange with educational practitioners.

• Machine Learning
• Maritime Engineering
• Robotics
• +۴ مورد دیگر

Shengkai Zhang is an active researcher with 26 publications and 444 citations spanning engineering, computer science, and environmental disciplines. His work demonstrates strong interdisciplinary collaboration through co-authorship with researchers like Kezhong Liu and Mozi Chen across multiple high-impact venues including IEEE conferences, arXiv, and specialized journals. His research interests center on Machine Learning applications in maritime systems , with significant contributions to Large Language Model integration for ship navigation, wireless sensing for bridge officer monitoring, and sensor fusion techniques. Additional expertise spans robotics perception (visual-inertial systems, mmWave radar enhancement), environmental modeling (urban energy systems, climate studies), and biomedical applications of traditional medicine. Recent work shows increasing focus on AI foundation models and their security implications. Zhang's publication trajectory reveals consistent output with accelerating impact since 2023, featuring 15+ papers in 2024 alone. His research clusters around three core themes: Maritime AI Systems (LLM navigation, track association, watchkeeping monitoring) Advanced Sensing Technologies (mmWave radar, Wi-Fi sensing, GNSS fusion) Environmental & Biomedical Applications (urban energy modeling, gut microbiome studies) These areas demonstrate both technical depth in signal processing/computer vision and practical focus on real-world engineering challenges.

Xiao Zhangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Statistical Machine Learning
• Convex Optimization
• +۴ مورد دیگر

Xiao Zhang is a tenure-track faculty member at the CISPA Helmholtz Center for Information Security and a member of the European Laboratory for Learning and Intelligent Systems (ELLIS). He obtained his Ph.D. in Computer Science from the University of Virginia in 2022 under Prof. David Evans, following an M.S. in Statistics from the same institution and a B.S. in Mathematics from Tsinghua University. Research Focus Zhang's research spans foundational and applied aspects of trustworthy machine learning, with emphasis on: Security vulnerabilities in ML systems (adversarial attacks, data poisoning) Robustness guarantees for learning algorithms Optimization methods for deep learning Privacy-preserving techniques Multimodal and physical-world applications His recent work focuses on developing theoretically-grounded defenses against emerging threats to AI systems. Publication Trends Zhang's 15 most recent publications (2019-2025) demonstrate consistent focus on adversarial machine learning, with growing emphasis on: 1) Physical-world attacks/defenses, 2) Multimodal model security, and 3) Certified robustness guarantees. The work consistently appears at top-tier venues (NeurIPS, ICLR, CCS). Academic Activities He actively recruits students and collaborators for trustworthy ML research, with open positions for PhD candidates and research assistants. No awards or specific grant information is documented in the provided materials.

• Cognitive Linguistics
• Psycholinguistics
• Construction Grammar
• +۷ مورد دیگر

Mégane Lesuisse is a Lecturer in Linguistics at Université Paris 8, affiliated with the TransCrit research group (UR 1569). Her work focuses on cognitive linguistics, psycholinguistics, and the intersection of language and spatial cognition. She teaches courses including Phonetics 1, Grammar 3 (Complex Sentence), and Linguistics: Meaning at the undergraduate level. Her research explores spatial expression, linguistic relativity, oculometry, and gender stereotypes in language. Key research interests include the cognitive impact of language-specific spatial encoding preferences, cross-linguistic comparisons of French, English, and Dutch spatial descriptions, and the relationship between language structure and conceptualization. She uses experimental methods like eye-tracking to study memory and attention modulation in static and dynamic locative events. Lesuisse has conducted projects such as ReCoLanS (Re-thinking English Modal Constructions) and co-organized workshops on time/space cognition. Her work bridges theoretical linguistics with empirical studies, emphasizing the bidirectional influence between language and thought.

Renjie Liaoمشاهده پروفایل

استادیار

• Deep Learning
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Renjie Liao is an Assistant Professor (tenure-track) in the Department of Electrical and Computer Engineering (ECE) at the University of British Columbia (UBC), with an associated appointment in the Department of Computer Science. He is also a Faculty Member at the Vector Institute and a Canada CIFAR AI Chair. Prior to UBC, Dr. Liao was a Visiting Faculty Researcher at Google Brain and held a Senior Research Scientist position at Uber Advanced Technologies Group during his PhD. He earned his B.Eng. (Automation) from Beihang University, M.Phil. (CS) from the Chinese University of Hong Kong, and PhD (CS) from the University of Toronto. His research focuses on probabilistic and geometric deep learning , with key contributions in deep generative models, geometric deep learning, neural algorithmic reasoning, and generalization bounds. Notable areas include 3D point cloud analysis, self-driving systems, and healthcare applications using graph neural networks. His work bridges theoretical foundations (e.g., PAC-Bayes bounds) with practical applications like motion forecasting and medical imaging. Education: B.Eng. in Automation, Beihang University (2011) M.Phil. in Computer Science, CUHK (2015) PhD in Computer Science, UofT (2021) Dr. Liao has received awards such as the RBC Graduate Fellowship and Connaught International Scholarship. His lab (Deep Structured Learning Lab) emphasizes principled mathematical approaches to solving complex problems. He advises students in machine learning, computer vision, and robotics, encouraging applications from those with strong coding/mathematical backgrounds. Labs/Teams: Deep Structured Learning Lab (UBC) Vector Institute Collaboration

• Astrodynamics
• Space Situational Awareness
• Orbit Propagation
• +۵ مورد دیگر

Davide Amato is an Assistant Professor in Spacecraft Engineering at the Department of Aeronautics, Faculty of Engineering at Imperial College London. He leads the Computational Astrodynamics (COAST) research group focused on developing advanced computational methods to enhance space situational awareness and satellite dynamics analysis. His work emphasizes error correction in orbital data, machine learning applications for space systems, and sustainable space operations. Education: PhD from Technical University of Madrid (2017), MSc and BSc from University of Naples Federico II (2013, 2009). Prior positions include Postdoctoral roles at University of Arizona and University of Colorado Boulder. Research interests include astrodynamics, space debris mitigation, orbit propagation, and computational methods. His group develops algorithms for satellite maneuver reconstruction, error-bounded orbit prediction, and scientific machine learning applications in space systems. Recent work addresses challenges in space catalog accuracy and collision avoidance through advanced mathematical techniques. He actively supports PhD applications for computational astrodynamics research via Imperial's President's PhD scholarships. His research spans applied mathematics, aerospace engineering, and interdisciplinary collaborations with the Space Lab and Artificial Intelligence Network at Imperial.

Pietro Peronaمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Signal Processing
• +۵ مورد دیگر

Pietro Perona is the Allen E. Puckett Professor of Electrical Engineering at the California Institute of Technology (Caltech). He holds a D.Eng. from the University of Padua (1985) and a Ph.D. from UC Berkeley (1990). His academic roles include serving as Director of the Center for Neuromorphic Systems Engineering (1999–2004) and Executive Officer for Electrical Engineering (2006–2010). His research focuses on computational vision, visual recognition, and machine learning. Key projects include the Visipedia initiative (smart apps for species identification like iNaturalist and Merlin Bird ID) and collaborations on neuroethology with Professors Anderson and Dickinson, studying fruit fly and mouse behavior. He also explores human visual perception and crowd-sourced learning. Perona has been recognized as an IEEE Fellow and leads the Caltech Vision Lab, which develops machine vision systems for applications in conservation, robotics, and neuroscience. His lab’s work spans foundational research to real-world tools, including datasets like the Caltech Fish Counting Dataset and MABe22 benchmarks. He teaches courses on computational vision and has advised numerous projects in AI and robotics. Current collaborations include partnerships with Amazon Web Services (AWS) and Disney on AI-driven solutions.

Ye Quanzhiمشاهده پروفایل

پژوهشگر

• Planetary Science
• Astronomy
• Astrophysics
• +۳ مورد دیگر

Ye Quanzhi is a Researcher at the University of Maryland's Department of Astronomy and a long-term visitor at Boston University's Center for Space Physics. He specializes in small Solar System bodies, including asteroids, comets, and meteoroids. His work involves ground- and space-based telescopes, numerical simulations, and data analysis from surveys like the Zwicky Transient Facility. He contributed to the NASA Planetary Data System Small Bodies Node and co-authored studies on the Taurid swarm and Comet C/2019 Y4 (ATLAS). Awards include the Harold C. Urey Prize in Planetary Science (2023). His research spans planetary formation, impact risks, and interstellar connections. He has advised students like Jasmine Li and engages in public outreach through media appearances in both Mandarin and English.

Bruno Adornoمشاهده پروفایل

دانشیار

• Robotics
• Legged Robots
• Mobile Manipulators
• +۴ مورد دیگر

Bruno Adorno is a Reader in Robotics (equivalent to Associate Professor) at the University of Manchester's Department of Electrical and Electronic Engineering. He holds the Sellafield/Royal Academy of Engineering Senior Research Fellowship in Cooperative Legged Robots in Challenging Environments. He is affiliated with the Manchester Centre for Robotics and AI and the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE). Previously, he was an Associate Professor at the Federal University of Minas Gerais (UFMG), Brazil, where he co-founded the MACRO research group. Education : BSc in Mechatronic Engineering, University of Brasilia (2004) MSc in Electrical Engineering, University of Brasilia (2008) PhD in Robotics, University of Montpellier (2011) Research Interests : His work focuses on robot kinematics, dynamics, and control, with applications to mobile manipulators, legged robots, and cooperative systems. He explores practical and theoretical advancements in robotic systems, including surgical robotics, teleoperation, and human-robot interaction. His methods often leverage dual quaternion algebra and vector field inequalities for robust control and motion planning. Awards : Sellafield/Royal Academy of Engineering Senior Research Fellowship Advising & Grants : Adorno has supervised multiple PhD/MSc students, as evidenced by his roles as examiner in recent theses on topics like robotic tail performance, tricopter UAVs, and reinforcement learning in robotics. His research has been supported by initiatives like the Sellafield fellowship and collaborations with industry and academia. Labs & Teams : He leads research within Manchester's robotics groups, emphasizing interdisciplinary projects in autonomous robotics, surgical robotics, and robotic autonomy in extreme environments.

Ruzena Bajcsyمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Computer Vision
• +۵ مورد دیگر

Ruzena Bajcsy is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences at UC Berkeley. She founded the GRASP Lab at the University of Pennsylvania and later became the inaugural director of CITRIS, a UC-wide research center. Her work spans robotics, computer vision, medical imaging, and tele-immersion. She holds dual PhDs from Stanford and Slovak Technical University. Education: Ph.D., Computer Science, Stanford University, 1972 Ph.D., Electrical Engineering, Slovak Technical University, 1968 M.S., Electrical Engineering, Slovak Technical University, 1957 Research Interests: Bajcsy’s research focuses on robotics, computer vision, assistive technologies, and tele-immersion. She pioneered the Digital Humanities program at UC Berkeley and developed medical imaging techniques for anatomical analysis. Current work includes kinematic analysis of human movement and assistive devices for mobility. Awards: Benjamin Franklin Medal in Computer and Cognitive Science (2009) IEEE Robotics & Automation Award (2013) Member of National Academy of Engineering and Medicine Grants & Labs: Directed GRASP Lab (1978–2001) and CITRIS (2001–2005). Current labs include the Tele-immersion Lab and collaborations with the CITRIS Health initiative.

Hyung Jin Changمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۲ مورد دیگر

Dr Hyung Jin Chang is an Associate Professor in the School of Computer Science at the University of Birmingham . He earned a PhD in machine learning and computer vision from Seoul National University in 2013, following a BSc in Electrical and Computer Engineering from the same institution in 2006. Research focuses on artificial intelligence , computer vision , robotics , and human-robot interaction , particularly human-centred visual learning for hand/body pose estimation, gaze tracking, and action/internal state understanding. Key projects include EU FP7 GRANT 612139 , EU H2020 GRANT 643783 , and industry collaborations with Samsung Electronics and Samsung GRO Grant . Recent publications address advancements in unsupervised learning , domain adaptation , 3D hand-object interaction modeling , and multimodal gaze following in conversational scenarios. His work bridges theoretical AI research with practical applications in vision-based robotics and medical image analysis, supported by both academic and industrial grants.

Eric Pearceمشاهده پروفایل

استاد

• Astronomical Instrumentation
• Satellite Tracking
• Space Surveillance Systems
• +۲ مورد دیگر

Eric Pearce is a Professor at Steward Observatory, University of Arizona, specializing in advanced astronomical systems for satellite surveillance. His research bridges instrumentation development and space situational awareness, with a focus on optimizing telescope technology for Earth-orbit monitoring. Research Focus: Design and deployment of robotic telescope systems for space object detection Algorithm development for satellite tracking and characterization Mersenne-Schmidt optical configurations for wide-field synoptic surveys High-sensitivity instrumentation for geosynchronous orbit monitoring Previously, he led the DARPA Space Surveillance Telescope (SST) project at MIT Lincoln Laboratory, creating the world's first large-aperture Mersenne-Schmidt telescope. His early career included supernova detection systems at New Mexico Tech and telescope software development at Yerkes Observatory.

Christopher Palmaمشاهده پروفایل

استاد آموزشی

• Astronomy Education
• Solar System Formation
• Planetary Science
• +۶ مورد دیگر

Christopher Palma is a Teaching Professor and the Associate Department Head for Outreach in the Department of Astronomy & Astrophysics at the Pennsylvania State University Park campus in State College, PA. From 2019-2023, he served as the Associate Dean for Undergraduate Students in the Eberly College of Science at Penn State. His academic career spans teaching, educational research, and extensive outreach activities focused on astronomy education and public engagement. His research interests center on astronomy education, with particular focus on developing learning progressions for understanding Solar System formation. Palma has made significant contributions to teacher professional development through the NSF Earth and Space Science Partnership and has created innovative courses including ASTRO 150 on dark skies/quiet skies (approved in spring 2025) and Astronomy 401: Fundamentals of Planetary Science. His educational research has examined student conceptions about how astronomers study the Solar System and developed frameworks for understanding planetary formation. Palma's publication record shows a strong focus on both educational research and public science communication. His recent work spans solar observation technology, planetary formation theories, cultural astronomy, and science policy related to light pollution. Notably, he has bridged academic research with public engagement through articles in The Conversation and collaborations with media outlets like Weather World. His outreach activities are extensive, including management of the Davey Lab Planetarium (recently upgraded to a full dome video projection system), leadership of telescope observing programs, advising student astronomy clubs, and organizing the annual AstroFest. Palma has been instrumental in developing a vision for a new planetarium and immersive visualization theater at the Penn State Arboretum. As an educator, Palma has developed multiple astronomy courses for diverse audiences, from introductory courses for general education students to specialized content for pre-service teachers. His work with the CAPER team on astronomy lab manuals using backwards faded scaffolding demonstrates his commitment to evidence-based pedagogy. Palma's professional service includes leadership roles with the Pennsylvania Earth Science Teacher's Association and the Penn State In-Service Workshops in Astronomy, which he directed from 2002-2019 and resumed leading in 2024.