جست‌وجوی استاد و پژوهشگر

M. Reza Hosseiniمشاهده پروفایل

مدرس ارشد

• Construction Technology
• Sustainable Engineering
• Circular Economy
• +۴ مورد دیگر

Dr. M. Reza Hosseini is a Senior Lecturer in Construction Technology at the University of Melbourne's Melbourne School of Design. He also serves as a Research Fellow at the Centre for Research in Assessment and Digital Learning (CRADLE) and is affiliated with the Mediated Intelligence in Design research laboratory at Deakin University. With a PhD in Virtual Design and Construction and an MSc in Construction Engineering and Management, his expertise spans digital engineering, sustainable construction, and circular economy practices. Dr. Hosseini has authored over 240 publications, focusing on topics such as BIM integration, AI-driven construction solutions, and emission reduction strategies. His research has been recognized through a top 2% global researcher ranking (2021–2023). His academic journey includes teaching BIM and digital technologies at Australian universities, addressing industry gaps through education reform. He actively collaborates on projects involving smart building technologies, blockchain for supply chains, and predictive analytics for infrastructure maintenance. Current research emphasizes circular economy frameworks, sustainable materials, and AI applications in construction safety and defect detection. Dr. Hosseini's work bridges theory and practice, with contributions to policy development, industry standards, and cross-disciplinary innovation. His recent studies explore digital twin technologies, BIM adoption challenges, and socio-technical dynamics in construction projects. He leads initiatives to enhance collaboration in BIM-enabled environments and advocates for education programs that align with industry demands for 'T-shaped' professionals skilled in both technical and collaborative competencies.

• Machine Learning
• Computer Vision
• Autonomous Robotics
• +۹ مورد دیگر

Yann LeCun is a Silver Professor at New York University (NYU) and Chief AI Scientist at Meta. He holds the Jacob T. Schwartz Chair in Computer Science at NYU's Courant Institute of Mathematical Sciences, and has affiliations with the Center for Data Science, Center for Neural Science, and the Tandon School of Engineering (Electrical and Computer Engineering). LeCun is a leading figure in artificial intelligence, known for pioneering work in deep learning, convolutional neural networks (e.g., LeNet), and self-supervised learning. His research focuses on machine learning, computer vision, autonomous robotics, and computational neuroscience. Education: Ph.D., Computer Science, Université Pierre et Marie Curie, France, 1987. DEA, Artificial Intelligence and Pattern Recognition, Université Pierre et Marie Curie, France, 1984. Diplôme d'Ingénieur, Electrical Engineering, École Supérieure d'Ingénieurs en Électrotechnique et Électronique, France, 1983. Research Interests: Machine learning, computer vision, robotics, computational neuroscience, and foundational AI research. He emphasizes the importance of self-supervised learning, world models for autonomous intelligence, and open-source AI development. His work bridges theoretical advancements with practical applications in healthcare, climate modeling, and robotics. Awards & Honors: ACM Turing Award (2018, shared with Geoffrey Hinton and Yoshua Bengio). Queen Elizabeth Prize for Engineering (2025). Member of the National Academy of Sciences and National Academy of Engineering. Multiple honorary doctorates and fellowships from institutions worldwide. Advising & Grants: LeCun has advised numerous PhD students and postdocs, many of whom have gone on to leadership roles in academia and industry. His research is supported by grants from Meta FAIR, NYU, and collaborations with institutions globally. He emphasizes mentorship and fostering interdisciplinary teams. Labs & Teams: Leads the CILVR Lab (Computational Intelligence, Learning, Vision, Robotics) at NYU and collaborates with Meta's FAIR (Fundamental AI Research). These groups focus on advancing AI through projects like JEPA (Joint Embedding Predictive Architecture) and World Models .

Kayla DesPortesمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Learning Sciences
• Creative Computing
• +۶ مورد دیگر

Kayla DesPortes is an Assistant Professor of Human-Computer Interaction and the Learning Sciences at New York University’s Steinhardt School of Culture, Education, and Human Development, within the Department of Administration Leadership and Technology. She holds a Bachelor’s in Electrical and Computer Engineering from Cornell University and a PhD in Human-Centered Computing from Georgia Institute of Technology. Her research focuses on transforming computing technologies and learning environments to empower marginalized communities through equitable, arts-integrated approaches. She designs participatory systems that merge computational literacy with artistic practices, such as dance and visual arts, to foster critical thinking about social justice issues. Key initiatives include the Creative Computing Cookbook (NSF Grant #2241809) and Critical Data Stories (NSF Grant #2302658), which co-design tools for creative computing education with community organizations. She also collaborates with MIT on an NSF-funded project exploring fabrication literacies through games (Grant #2008028). DesPortes teaches courses such as User Experience Design and Tangible Electronics for Teaching and Learning , emphasizing hands-on, interdisciplinary learning. Her work bridges the learning sciences, human-computer interaction, and community-centered design to address systemic inequities in STEM access and representation. In grants and collaborations, she leads efforts to develop AI literacy platforms, data storytelling tools, and culturally responsive curricula. Her research emphasizes long-term partnerships with organizations like STEM From Dance and Community Word Project, prioritizing community voice and asset-based approaches.

Jun Jinمشاهده پروفایل

استادیار

• Robotics
• Machine Learning
• Reinforcement Learning
• +۴ مورد دیگر

Jun Jin is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Alberta and a Fellow of the Alberta Machine Intelligence Institute (Amii). His research focuses on robotic reinforcement learning, embodied artificial intelligence, and human-centered autonomy. He holds a PhD and has eight years of industry experience in autonomous systems, including autonomous driving and construction automation. He teaches ECE 720 B01 Robot Learning: Principles and Advances and leads the Human-Centered Autonomy (HCA) Lab, which hosts a weekly reading club. His research interests include developing scalable learning architectures for robots to adapt to dynamic environments, ensuring safe human-robot interaction, and advancing open-ended learning agents. Notable achievements include the ICRA 2022 Outstanding Student Paper Award and the KUKA Innovation Award 2018. He emphasizes applying robotics to construction (e.g., infrastructure maintenance robotics) and healthcare. Dr. Jin actively mentors students through competitive research assistant positions and collaborates with Amii for computational and industrial resources. His lab fosters a community-driven approach to advancing robotics through interdisciplinary research and public engagement.

Michael Manganمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Robotics
• Biorobotics
• +۵ مورد دیگر

Dr. Michael Mangan is a Senior Lecturer in Machine Learning and Robotics at the University of Sheffield's School of Computer Science, and Operations Director of Sheffield Robotics. He holds an MEng in Avionics from the University of Glasgow (2004), an MSc in Neuroinformatics from the University of Edinburgh (2006), and a PhD in Biorobotics (2011). His research focuses on understanding insect navigation and applying these insights to robotics, emphasizing bio-inspired systems for autonomous navigation and smart agriculture. Research interests include modeling insect vision, navigation strategies, and neural mechanisms, with applications to robotics and pest control. Mangan leads the ManganLab, exploring how simple nervous systems enable complex behaviors through computational and robotic models. His work integrates biology, computer science, and engineering to develop robust autonomous systems. Key contributions include tools like CompoundRay for simulating compound eyes and I2Bot for multi-modal insect navigation simulations. He has secured grants such as ActiveAI (£953k) and SkyEye (£25k), focusing on AI transparency, neuromorphic control, and vision-based localization. Professional memberships include the Machine Learning research group and involvement in Living Machines conferences. Current projects explore fruit detection in agriculture, neuromorphic sequence learning, and animal tracking in natural environments.

Laurissa Tokarchukمشاهده پروفایل

مدرس ارشد

• Mobile and Location-Based Gaming
• Game AI
• Data-Driven Human-Computer Interaction (HCI)
• +۷ مورد دیگر

Dr. Laurissa Tokarchuk is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science, affiliated with the Game AI and Cognitive Science research groups and the Centre for Intelligent Sensing (CIS). Her research focuses on mobile and location-based gaming, data-driven HCI, mobile sensing, and social computing. She has led projects like the EPSRC ImpactQM KTA on location estimation and the Royal Society-funded virus prevention study with UESTC. Dr. Tokarchuk teaches modules including Digital Media and Social Networks and has supervised over 20 MSc and 70 undergraduate projects. Research Interests: Mobile gaming, social sensing, VR/AR applications, crowd behavior analysis, and adaptive recommendation systems. Her work includes the SensingKit framework for mobile sensing and the adaptive Twitter crawler for event detection. Grants & Awards: Recipient of the Drapers award for Teaching (2010/11), EPSRC grants (e.g., DSTL PhD Studentship, TRIDEC EU FP7), and leadership roles in IGGI (Intelligent Games and Game Intelligence). She has published over 50 peer-reviewed articles and serves on program committees for IEEE Conference on Games and others. Labs & Teams: Active in CIS, leading research on sensor-based systems and collaborating with industry partners like BBC and Somethin’ Else. Her lab develops tools like SensingKit and adaptive crawling software for real-time event analysis.

Ludovic Righettiمشاهده پروفایل

دانشیار

• Robotics and applications
• Optimal control
• Reinforcement learning
• +۷ مورد دیگر

Ludovic Righetti is an Associate Professor at the Tandon School of Engineering, New York University, holding joint appointments in Electrical and Computer Engineering and Mechanical and Aerospace Engineering. He is also an International Chair at the Artificial and Natural Intelligence Toulouse Institute. His research focuses on robotic motion planning and control, particularly legged locomotion and manipulation, with interdisciplinary interests in decision-making, optimization, and AI ethics. He leads the Machines in Motion Laboratory and co-directs the Center for Robotics and Embodied Intelligence. Education: He earned a Doctorate in Science from the Ecole Polytechnique Fédérale de Lausanne (EPFL) and a postdoctoral fellowship at the University of Southern California. Previously, he led a research group at the Max-Planck Institute for Intelligent Systems before joining NYU in 2017. Research Interests: His work spans robotics applications, optimal control, reinforcement learning, and societal implications of AI. Key areas include legged robots, manipulation, and ethical technology use to improve societal equity and quality of life. Scientific Awards: Recipient of the 2010 Georges Giralt PhD Award, 2011 IROS Best Paper Award, 2016 IEEE Early Career Award, Heinz Maier-Leibnitz Prize, and 2024 NYU Jacobs Excellence in Education Innovation Award. Affiliations: Member of NYU's Center for Responsible AI, Center for Urban Science + Progress, and Center for Advanced Technology in Telecommunications. His lab explores principles of robot locomotion and manipulation, with recent work on 5G-enabled remote control and AI ethics.

• Computer Vision
• Autonomous Systems
• Artificial Intelligence
• +۳ مورد دیگر

Rudolf Mester is a Professor at NTNU's Department of Computer Science and holds the DNV GL Endowed Professorship. He leads research in intelligent visual sensorics, AI applications for autonomous vehicles (cars, ships, underwater robots), and performance assurance of AI systems. His current projects include SFI Autoship (maritime autonomy), AutoSight (resilient perception), and cAIge (AI-based salmon health monitoring). He teaches the PhD course "Intelligent Agents" and supervises MSc/PhD students in Embodied AI and Aquaculture projects. His research group focuses on environment perception for autonomous marine vehicles, multi-sensor surveillance, reinforcement learning, and AI validation methods.

Rachelle Tsachorمشاهده پروفایل

دانشیار

• Theatre
• Movement Science
• Somatic Practices
• +۷ مورد دیگر

Rachelle Tsachor is an Associate Professor in the Department of Theatre at the University of Illinois at Chicago (UIC), part of the School of Theatre and Music. Her work bridges arts and sciences, using Laban Movement Analysis and Alexander Technique to explore movement's impact on artistic practice, human health, and technological interaction. She has held academic roles at institutions including the University of Iowa, Grinnell College, and guest positions at international universities. Education includes a Master of Arts in Choreography/Directing from City College of New York, a Bachelor of Fine Arts in Dance from Juilliard, and certifications in Laban Movement Analysis and the Alexander Technique. She serves as senior faculty at the Laban/Bartenieff Institute of Movement Studies (NYC) and Israel’s Wingate College. Her research investigates three core areas: movement’s role in artistic creativity, its physiological/emotional effects, and its application to future technology. Notable projects include choreographing theatre productions at UIC and reconstructing Renaissance dance forms like *Nido d’Amore*. Recent work explores affective computing, robotics, and machine learning through movement analysis. Publications span scholarly editions of historical dance manuscripts (*Dances for the Sun King*) to neuroscience studies on emotion regulation. Her TedX talk *How your body affects your happiness* has garnered over 250,000 views. Media features include interviews with *Everyday Health* and *The New York Times*. Labs/Teams involvement includes collaborations with the Labanarium international movement network and co-investigator roles in interdisciplinary research projects. She actively develops somatic training programs and contributes to global health studies through performing arts integration.

Yoonsuck Choeمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Networks
• Neuroevolution
• +۹ مورد دیگر

Yoonsuck Choe is a Professor in the Department of Computer Science and Engineering at Texas A&M University and Director of the Brain Networks Laboratory. He has held roles including Corporate Vice President at Samsung Research (2017–2019) and served as a Fellow in the College of Engineering. His expertise spans computational neuroscience, brain imaging, neuroevolution, and deep learning, with a focus on temporal brain dynamics, sensorimotor learning, and AI-driven neuroimaging analysis. Education : Ph.D. (2001), M.A. (1995) from University of Texas at Austin; B.S. (1993) from Yonsei University. His research interests include predictive neural dynamics, consciousness, thalamocortical function, and biologically inspired AI systems. Recent publications emphasize energy-efficient neural networks, tool-use evolution, and connectomics. He has received awards for teaching excellence and research innovation, including the 30th Anniversary Distinguished Alumni Award from Yonsei University (2013). Advising and grants: Prof. Choe has guided over 20 students in their theses and dissertations, focusing on topics like motor learning, neural integration, and medical imaging. His Samsung tenure involved AI core team leadership and high-throughput brain dynamics automation. Grants include work on KESM brain atlas development and neurovascular modeling. Lab and teams: Directs the Brain Networks Lab (Choe Lab) at Texas A&M, exploring brain networks, predictive systems, and AI applications. Collaborates with interdisciplinary teams in neuroscience and biomedical engineering.

Zhengzhong Tuمشاهده پروفایل

استادیار

• Spatial Intelligence
• 3D Vision
• Multimodal and Generative AI
• +۳ مورد دیگر

Zhengzhong Tu is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, College of Engineering. His research focuses on spatial intelligence, 3D vision, multimodal AI, autonomous driving, and trustworthy large language models. He holds a Ph.D. from The University of Texas at Austin (2022) and M.S./B.S. degrees from Fudan University (2018/2016). Education Ph.D., Electrical and Computer Engineering, The University of Texas at Austin – 2022 M.S., Electrical Engineering, Fudan University – 2018 B.S., Electrical Engineering, Fudan University – 2016 Research Interests Tu’s work bridges generative AI, autonomous systems, and multimodal perception. He explores challenges in 3D reconstruction, cross-modal alignment, and safety-critical applications like autonomous driving. His recent projects focus on enhancing model trustworthiness through robust watermarking and constraint optimization, while advancing benchmarks for vision-language models in spatial reasoning. Publications Trends His 2025 articles emphasize generative AI applications in autonomous driving (e.g., crash prediction, sensor fusion), multimodal systems (e.g., vision-language navigation), and video quality enhancement. He also contributes to benchmark development (e.g., NTIRE challenges) and ethical AI practices. Awards No scientific awards explicitly mentioned in the text. Advising & Grants No student advisees or grant information listed. His research is supported by institutional affiliations and collaborative projects. Labs & Teams Not explicitly mentioned in the provided text. His work likely involves Texas A&M’s autonomous systems and AI research groups.

Helen J Burgessمشاهده پروفایل

استاد

• Digital Humanities
• Electronic Literature
• Multimodal Composition
• +۴ مورد دیگر

Helen J. Burgess is a Professor of English and Director of the Communication, Rhetoric and Digital Media PhD Program at North Carolina State University. She holds a BA(Hons) and MA(Dist.) from Victoria University of Wellington (New Zealand) and a PhD from West Virginia University. Her work bridges digital rhetorics, electronic literature, critical making, and feminist crafting. She has previously taught at Washington State University-Vancouver and UMBC. Her research explores digital humanities, electronic literature, and multimedia development. Notable publications include Biofutures: Owning Body Parts and Information (2008), Red Planet: Scientific and Cultural Encounters with Mars (2000), and co-editing The Routledge Research Companion to Digital Medieval Literature (2017). She edits Hyperrhiz: New Media Cultures and contributes to Rhizomes and thresholds journals. Burgess’s creative projects include installations like Imaginal Pockets (2025) and Intimate Fields (2018). Her current work focuses on a book about silkworms, blending biological inquiry with digital media practices. She advocates for interdisciplinary approaches to new media and critical code studies.

Shigang Yueمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Robotics
• +۴ مورد دیگر

Professor Shigang Yue is a Professor of Computer Science at the University of Leicester's Computing and Mathematical Sciences department. His research focuses on artificial intelligence, computer vision, robotics, neuroscience, and bio-inspired systems. He has published over 200 papers and led EU-funded projects. He holds a PhD from Beijing University of Technology (1996) and was an Alexander von Humboldt Research Fellow (2000-2001). Research interests include bio-inspired visual neural networks, autonomous robotics, medical image analysis, machine learning, and swarm intelligence. He has coordinated EU FP7 and Horizon 2020 projects and examined over 20 PhD theses. His work bridges biological systems and robotics, emphasizing collision avoidance, motion detection, and swarm robotics. Notable contributions include the I2Bot platform for insect navigation simulation, bio-inspired collision detection models (e.g., LGMD), and frameworks for small target tracking. He is an EPSRC peer reviewer and editorial board member for international journals. Labs and teams: Active in developing bio-inspired robotics systems and collaborative platforms like Colcos φ for swarm robotics. His group welcomes PhD and visiting students in AI and robotics.

Pirkko Liisa Raudaskoskiمشاهده پروفایل

استاد

• Conversation Analysis
• Ethnomethodology
• Multimodal Interaction Analysis
• +۱۷ مورد دیگر

Pirkko Liisa Raudaskoski is a Professor in the Department of Communication and Psychology at Aalborg University, Faculty of Humanities and Social Sciences. She is affiliated with the Mediated Communication research group and the Center for Cultural Psychology, where she leads the VILA - Video Research Lab. Her research spans practical studies, discourse analysis, and sociomaterial approaches, with a focus on intelligibility-in-practice through video-based methods. Her research interests center on how people make sense of and accomplish actions in everyday and institutional settings. She employs ethnomethodological conversation analysis, multimodal interaction analysis, and membership categorization analysis to study social practices. Her theoretical framework is grounded in sociomaterialism, linking micro-level interactions to broader societal issues such as public participation, healthcare, and environmental sustainability. She contributes to the UN Sustainable Development Goals through work in communication, pedagogy, media research, and professional discourse. Her recent publications and projects reflect a strong trend in methodological innovation, particularly in the use of 360-degree video, immersive analytics, and software tools for qualitative research. Themes include assemblage theory, affective orientation in learning, healthcare interaction, and social robotics. She has contributed to major publications such as The Cambridge Handbook of Analysing Discourse and developed open-source tools like 360mash. Research leader of the Velux-funded HUMpraxis project How to talk about medicines? (2024–2027) Co-investigator in Touch and Affect in Health Care Interaction (2021–2025) Participant in Environmental Humanities Cluster and SIMVIDIA projects Active peer reviewer and academic contributor, including service for the Swiss National Science Foundation She supervises PhD students and teaches methodological courses in communication and psychology, covering ethnomethodology, discourse analysis, and qualitative research design. She has been involved in organizing conferences and workshops internationally and has contributed to academic discourse through public engagement and media appearances on topics such as propaganda and research freedom. Her research is supported by multiple grants from national and international bodies, and she collaborates across disciplines and institutions. She leads and participates in labs and research groups including VILA - Video Research Lab and DigHumLab, focusing on digital tools for qualitative inquiry and immersive analytics.

• Game Studies
• AI Ethics
• Surveillance Studies
• +۳ مورد دیگر

Ragnhild Solberg is a Guest Lecturer at the Department of Art and Media Studies at NTNU. Her research focuses on intersections of artificial intelligence, digital culture, and posthumanism, particularly in games, visual media, and surveillance studies. She holds a doctoral degree from the University of Bergen (UiB) and has contributed to the ERC-funded 'Machine Vision in Everyday Life' project led by Prof. Jill Walker Rettberg. Education: Completed her doctoral dissertation titled 'Playing posthumanism: A study of machine vision and tensions of human-machine relations in digital games' at UiB (2023). Research Interests: Explores representations of gender, AI, and power dynamics in digital games; human-machine relationships through machine vision technologies; and posthumanist frameworks in visual culture. Her work bridges game studies, digital humanities, and surveillance theory. Publications: Over 9 peer-reviewed articles and reports since 2019, focusing on machine vision in art/games, agency in AI systems, and cyborg identities. Recent works include analysis of surveillance mechanisms in digital games and exhibitions addressing societal impacts of algorithmic technologies. Teaching: Instructs courses such as HFO1001 (Digital Changes), MV2012 (The Image in Society), and supervises bachelor's theses in media studies at NTNU. Outreach: Created video abstracts for academic papers and contributed to public exhibitions like 'Maskinsyn: Ditt digitale liv' exploring digital surveillance ethics.