جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction (HCI) Education
• Inclusive Design
• Computing Education Research
• +۳ مورد دیگر

Alannah Oleson is an Assistant Professor in the Department of Computer Science at the University of Denver's Ritchie School of Engineering and Computer Science. Her work focuses on inclusive design, computing education, and addressing equity issues in technology. She is actively involved in the KIHA Innovation Labs, exploring human-centered approaches to computing education and HCI. Her research investigates how demographic factors influence learning outcomes in computing courses, develops pedagogical methods for teaching inclusive design (e.g., the CIDER framework), and examines the ethical implications of technology in K-12 and university settings. Notable areas include algorithmic fairness, gender bias in software systems, and culturally responsive computing education for underrepresented groups. Dr. Oleson's research emphasizes practical methods for integrating critical thinking into software design processes, with recent work exploring peer feedback systems for equity analysis in large courses and curriculum reforms to promote ethical awareness. Her contributions bridge theory and practice, aiming to make computing education more equitable and socially responsible.

Maarten Goosمشاهده پروفایل

استاد

• Labor Economics
• Technological Change
• Economic Inequality
• +۷ مورد دیگر

Maarten Goos is a Full Professor of Economics and Institutions at Utrecht University's Faculty of Law, Economics and Governance. He previously held positions at Erasmus University Rotterdam, University College London, KU Leuven, and had visiting roles at Princeton University, MIT, Boston University, and Fudan University. His research focuses on labor markets, technological progress, wage inequality, and institutional impacts. He is also an award-winning teacher, specializing in European macroeconomics, economic growth, and labor economics. Education: He earned his PhD from the London School of Economics (LSE). His academic journey includes roles at multiple prestigious institutions, reflecting deep expertise in labor and technological economics. Research interests include the interplay between technology and labor markets, specifically automation's effects on employment, wage polarization, and the role of institutions in shaping labor dynamics. He examines how skill-biased technological changes and globalization influence job structures and income distribution. His work also addresses the declining labor share in economies, exploring explanations rooted in firm behavior and productivity shifts. He collaborates with the European Commission, national policy institutes, and multinational corporations, contributing to policy initiatives and economic analyses. His research bridges theoretical models with empirical evidence, offering frameworks like the canonical CES model and task-based automation theories to dissect labor market trends. Though no specific awards are listed, his work is noted as award-winning in international publications. Advising/Grants: Goos has advised various organizations and contributed to policy projects, though formal advisee names or grant details are not explicitly stated. His teaching and research emphasize practical implications of economic theories for real-world labor market challenges and institutional reforms. Labs/Teams: Collaborates within Utrecht University's School of Economics and with external networks through European Commission projects and corporate partnerships.

Taran Raiمشاهده پروفایل

پژوهشگر

• Computational Pathology
• Deep Learning
• Digital Pathology
• +۳ مورد دیگر

Dr. Taran Rai is a Researcher at the University of Surrey, affiliated with the Centre for Vision, Speech and Signal Processing (CVSSP) and the School of Veterinary Medicine. His work focuses on computational pathology, deep learning for medical imaging, and applying AI to veterinary medicine. Rai holds a PhD and has contributed to advancements in necrosis and mitosis detection in canine tumors, leveraging CNNs and digital pathology. His research interests include AI-driven diagnostic tools, social media listening for health insights, and optimizing neural networks for medical applications. He has published extensively on topics like synthetic histopathology data evaluation, diffusion models, and adaptive thresholding methods in pathology. Rai's recent work explores the integration of large language models with medical imaging (e.g., the IPATH dataset) and addresses challenges in veterinary healthcare through social media data. His studies often bridge computational methods with real-world clinical needs, aiming to improve diagnostic accuracy and patient care.

• Orthodontics
• Biomechanics
• Dental Materials Science
• +۳ مورد دیگر

Prof. Dr. Andrea Wichelhaus is a full professor and head of the Department of Orthodontics at the LMU University Hospital Munich. She holds a medical dentistry degree from the Universities of Cologne and Heidelberg (1985), a PhD (1987), and completed habilitation at the University of Ulm (1996). Her career includes roles as deputy director of the Department of Orthodontics at Ulm University (1990–1999) and professorships at the Universities of Basel (2008) and Munich (2008–present). She conducted research at Harvard University (1996). Research focuses on biomechanics, mechanobiology, and orthodontic materials. Key areas include orthodontic appliance design, force/moment analysis, and material testing. Awards include the 1995 Walter-Engel-Preis and the German Society of Orthodontics' best publication award. Publications span over 30 years, emphasizing clinical and biomechanical studies. Recent work explores NiTi alloys, CAD/CAM retainers, 3D-printed bonding trays, and robotic simulation systems (ROSS/HOSEA). Her textbook Kieferorthopädie - Therapie (2024) outlines advanced treatment concepts. Her team conducts interdisciplinary studies involving finite element analysis, in vitro testing, and clinical trials. Collaborations include biomechanical engineering and material science groups.

• Medical Robotics
• Agricultural Robotics
• Infrastructure Robotics
• +۴ مورد دیگر

Chao Chen is an Associate Professor at the Department of Mechanical & Aerospace Engineering, Monash University, and Director of the Laboratory of Motion Generation and Analysis (LMGA). He holds an adjunct position as Associate Professor at the Chinese University of Hong Kong. His research focuses on medical, agricultural, and infrastructure robotics, emphasizing design, dynamics, control, and intelligence. Key innovations include the Robotic Transverse Profiler (delivered to the Australian Road Research Board in 2016), the 3D Printed Prosthetic Hand (2017 Award), and the Apple Harvesting Robot (2019 Global AI Expo). Dr. Chen has secured over $2M in lead research funding and contributed to $18M in collaborative projects, supported by ARC, Collier Charitable Fund, and International Science Linkages. His awards include the 2017 Innovation Award from the Australian Hand Therapy Association and scholarships from ASME and FQRNT. Education: PhD in Mechanical Engineering (details not explicitly stated in text) Research interests span medical robotics (surgery and rehabilitation), mobile robotics with advanced mobility, and reconfigurable mechatronic systems . LMGA’s mission is to address real-world challenges via robotic technologies, targeting healthcare, agriculture, and infrastructure sectors. Recent projects include fruit harvesting systems, drug delivery sensors, and embodied AI frameworks. Publications highlight advancements in robotic perception (e.g., LiDAR-camera fusion), control systems, and tactile-enabled grasping. His work aligns with UN Sustainable Development Goals, particularly in advancing industry innovation and infrastructure (SDG 9) and sustainable agriculture (SDG 2). Awards: 1996 Dean’s Honor List (Shanghai Jiao Tong University), 2004 ASME Scholarship, 2005 FQRNT Doctorate Scholarship Grants and collaborations include leading the ALF 1 Transverse Profiler and participating in the $18M ARC Smart Process Design Hub . Current projects address robotic fruit harvesting, hydrogel drug delivery systems, and AI-driven manipulation frameworks. Labs/Teams: Director of LMGA, collaborating internationally with institutions like IRCCyN (France), Shanghai Jiao Tong University, and Agriculture Victoria.

Michael Fisherمشاهده پروفایل

استاد

• Autonomous Systems
• Robotics
• Formal Verification
• +۳ مورد دیگر

Michael Fisher is the Royal Academy of Engineering Chair in Emerging Technologies and Professor of Computer Science at the University of Manchester. He also holds an Honorary Professorship at the University of Liverpool (2020–2023). His research focuses on autonomous systems, formal verification, robotics ethics, and AI safety. Fisher leads projects such as the Centre for Robotic Autonomy in Demanding Environments (CRADLE) and contributes to IEEE standards for fail-safe autonomous systems. He is a Senior Associate Editor of the Annals of Mathematics and Artificial Intelligence and co-chair of the IEEE Verification of Autonomous Systems committee. His work integrates formal methods with robotics, emphasizing ethical reasoning and assurance in autonomous systems. Key research interests include temporal logic, model checking, and the verification of robotic decision-making. Fisher has received Best Paper Awards in 2018 and 2014, recognizing contributions to human-robot team validation and ethical reasoning frameworks. Fisher’s projects span space robotics, industrial automation, and safety-critical systems. He collaborates with industry partners like Amentum and advises the UK government on AI and robotics policy. His recent work explores neuro-symbolic AI integration and compositional verification for modular robotic systems.

Luan Oliveiraمشاهده پروفایل

استادیار

• Precision Agriculture
• Agricultural Engineering
• Crop Production
• +۳ مورد دیگر

Dr. Luan Oliveira is an Assistant Professor and Precision Agriculture Extension Specialist at the University of Georgia's College of Agricultural & Environmental Sciences (CAES), Department of Horticulture. His roles are distributed as 75% Extension, 20% Research, and 5% Service. He holds a Ph.D. in Agronomy (Crop Production) from São Paulo State University and a B.Sc. in Agronomic Engineering from Federal University of Paraíba, Brazil. His research focuses on precision agriculture tools, agricultural machinery optimization for vegetables and specialty crops, and mechanized operations like planting, spraying, and harvesting. He leads the Precision Horticulture Team, aiming to improve crop quality through innovative technologies. Dr. Oliveira has received the 2021 Gerald O. Mott Award for Meritorious Graduate Student in Science. He has authored/co-authored 9 refereed articles, 7 Extension Publications, 40 conference papers, and 13 book chapters, securing ~$220,000 in grants as PI/Co-PI. His work emphasizes practical applications in precision agriculture, including drone spraying, robotic systems, and mechanized sugarcane planting. Key grants and awards highlight his contributions to agricultural technology and crop management. His research spans diverse crops like peanuts, corn, cotton, and sugarcane, addressing challenges in seeding depth, soil compaction, and equipment wear. He collaborates with the Institute for Integrative Precision Agriculture and UGA's Precision Agriculture initiatives.

Stephen Lee-Urbanمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Game AI
• +۳ مورد دیگر

Stephen Lee-Urban is a Teaching Associate Professor in the Department of Computer Science & Engineering at Lehigh University, affiliated with the Rossin College of Engineering. He holds a Ph.D., M.S., and B.S. in Computer Science and Engineering from Lehigh University, all completed with summa cum laude distinction. His research focuses on fundamental and applied artificial intelligence, machine learning, game AI, cognitive systems, and automated planning. He has contributed to innovative projects such as HuManIC (human-machine interpretive control), CORA (cognitive systems framework), and crowdsourced narrative generation systems. His academic career includes significant work in cybersecurity through intelligent agent modeling of malware, as well as contributions to game AI for strategy games and military training simulations. Notable awards include summa cum laude honors for all three of his university degrees. Lee-Urban's scholarly output spans over 20 publications since 2000, with recent emphasis on AI applications in collaborative storytelling, adaptive planning systems, and human-computer interaction. His research integrates machine learning techniques with sociocultural analysis, crowd-powered content creation, and hierarchical task networks. Current work explores autonomous systems capable of leveraging crowd intelligence for generating interactive narratives and optimizing military training scenarios. While no specific grants or advising roles are listed, his interdisciplinary approach bridges computer science with game design, cybersecurity, and cognitive modeling.

Luigi Manfrediمشاهده پروفایل

مدرس ارشد

• Endorobotics
• Gastrointestinal Tract Screening
• Soft Materials Engineering
• +۳ مورد دیگر

Luigi Manfredi is a Senior Lecturer and Principal Investigator at the University of Dundee's Respiratory Medicine and Gastroenterology department. He completed his PhD and Post-Doc at the Biorobotics Institute in Pisa, Italy, before joining Dundee in 2011 as Project Coordinator for the ERC-funded CODIR project and Co-Investigator for CARPE. His research focuses on developing soft materials and endorobots for GI tract screening and treatment. Key achievements include winning the Surgical Innovation Award (2013) and Dundee Venture Competition (2020) for low-cost colonoscope proposals. Education: PGCAPHE Fellowship Module with Advance HE (2022–2024). Research expertise spans actuators, colonoscopy technologies, bio-inspired robotics, and shape-memory alloys. He has led projects like SoftEn (EPSRC-funded) and Softech High Growth Phase 1. Over 56 publications highlight contributions to medical robotics and endoscopic innovation. Recent work emphasizes ergonomics in robotic endoscopy, monocular depth estimation for autonomous colonoscopy, and AI-driven solutions for colorectal screening. Editorial roles include Frontiers in Robotics and AI. Active collaborations involve global institutions, focusing on self-supervised depth estimation and lumen detection technologies.

Elena Panteleyمشاهده پروفایل

پژوهشگر

• Nonlinear Control Systems
• Networked Systems
• Multi-Agent Systems
• +۵ مورد دیگر

Elena Panteley is a Research Director at the CNRS and a member of the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. She holds a PhD in Applied Mathematics from Saint Petersburg State University (1997) and has extensive experience in research, including roles at the Institute of Problems in Mechanical Engineering, Russian Academy of Sciences (1986–1998). She co-chairs the International Graduate School of Control at the European Embedded Control Institute (EECI-IGSC) and serves as a Book-reviews Editor for Automatica and Associate Editor for IEEE Control Systems Letters . Education: PhD in Applied Mathematics, Saint Petersburg State University, 1997 MSc/BSc in relevant fields (implied by career progression) Research Interests: Focuses on stability and control of nonlinear dynamical systems, networked systems, multi-agent systems, and their applications. Her work emphasizes robust control, consensus algorithms, synchronization, and distributed control strategies for autonomous systems. She explores theoretical frameworks like Lyapunov methods and adaptive control, with practical applications in robotics and communication networks. Publications: Over 100 peer-reviewed articles in top journals like IEEE Transactions on Automatic Control and Automatica . Recent trends include advancements in consensus algorithms for multi-agent systems, synchronization of nonlinear oscillators, and control under communication delays. Awards: No specific awards mentioned, but contributions to control theory and networked systems are widely recognized. Grants/Advising: Leads research on adaptive control, network synchronization, and robotics. Collaborates internationally and advises on projects involving autonomous vehicles and distributed systems. Labs/Teams: Active in L2S and affiliated with CNRS, contributing to teams like MODESTY, COMEDY, and SYCOMORE. Engaged in transverse research on energy, industry automation, and healthy systems.

Jiju Poovvancheriمشاهده پروفایل

دانشیار

• Computer Graphics
• 3D Vision
• Machine Learning
• +۸ مورد دیگر

Dr. Jiju Poovvancheri is an Associate Professor in the Department of Math & Computing Science at Saint Mary’s University, Halifax, Canada. He holds affiliations with the Graphics & Spatial Computing Lab and previously held postdoctoral positions at the University of Victoria and University of Calgary. His research focuses on computer graphics, 3D vision, and machine learning, with applications in virtual/augmented reality, autonomous robotics, urban planning, and bio-mechanical studies. Key research areas include point cloud processing, semantic surface reconstruction, spatial data structures, and geometric deep learning. Education: PhD from Indian Institute of Technology Madras (2011–2014), supervised by Prof. Ramanathan Muthuganapathy. Postdoctoral work at University of Calgary (EYES-HIGH Fellowship, 2015–2017) and University of Victoria (MITACS Elevate Fellowship, 2018). Research & Awards: Winner of MITACS Elevate Fellowship (2018), EYES-HIGH Fellowship (2015–2017), and multiple grants including NSERC DG (2019–2026). His work has been supported by NVIDIA GPU hardware, NSERC, CFI, and industry partners like Modest Tree Media and Caterpillar. Professional Activities: Associate Editor for IEEE Access , Guest Editor for special issues in Remote Sensing and Sensors , and reviewer for top conferences like CVPR, ICCV, and ECCV. Member of ACM SIGGRAPH, Solid Modeling Association, and IEEE Geoscience & Remote Sensing Society. Lab & Collaborations: Leads the Graphics & Spatial Computing Lab, collaborating with institutions globally. Current projects include "Interaction and navigation in virtual spaces" and industry partnerships with Modest Tree Media for real-time object recognition. Advising: Supervised over 20 graduate and undergraduate students, with notable alumni advancing to roles at ReelData AI, Royal Canadian Air Force, and academic institutions like Dalhousie University.

• Marketing
• Consumer Behavior
• Technology Adoption
• +۴ مورد دیگر

Gaël Bonnin is a Professor of Marketing at NEOMA Business School, France, where he has held the role of Director of Research from 2020 to 2023. He teaches technology innovation, marketing strategies, design, and qualitative research methods across undergraduate, graduate, and doctoral programs (DBA/PhD). His research focuses on product/place design, technology adoption, and narrative approaches to market construction, with notable contributions to healthcare servicescape optimization, consumer resistance to misinformation, and senior engagement with new technologies. Director of Research (2020–2023), NEOMA Business School Co-led EU-funded projects on companion robots, agricultural robotics, and AR tourism applications Published in International Journal of Hospitality Management , Advances in Consumer Research , and Journal of Retailing and Consumer Services Research highlights include analyzing sensory elements (colors/music/scent) in hospital environments to reduce patient anxiety, studying emotional responses to fake news warnings, and evaluating anthropomorphic design impacts on robot acceptance among elderly populations. His work bridges consumer behavior theory with practical applications in retail, healthcare, and technology sectors. Key contributions span over 30 years, including book chapters on B2B technology branding, neutralization strategies in piracy contexts, and design marginalization in retail spaces. He frequently presents at conferences like ACR, IMP, and CAUTHE, emphasizing interdisciplinary approaches to market dynamics.

Gady Agamمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۸ مورد دیگر

Dr. Gady Agam is an Associate Professor in the Department of Computer Science at Illinois Institute of Technology (Illinois Tech), affiliated with the College of Computing. His primary research focuses on Computer Vision, Machine Learning, and Artificial Intelligence, with applications in medical imaging, remote sensing, and security systems. He leads the Visual Computing Lab, which explores topics such as deep learning, geometric modeling, and computational methods for data analysis. Dr. Agam teaches courses including CS584 (Machine Learning), CS512 (Computer Vision), and CS577 (Deep Learning). His research has resulted in over 100 peer-reviewed publications and collaborations with organizations like SPIE. He has held leadership roles in conferences such as Document Recognition and Retrieval and has contributed to industry-relevant projects like the MuscleX software. His academic contributions include advancements in image registration, feature detection, and automated medical diagnostics. He actively supervises graduate students in his lab and maintains partnerships with academic and industrial entities to drive innovation in visual computing technologies.

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Prof. Margret Keuper is a Professor in the Department of Computer Vision and Machine Learning at the Max Planck Institute for Informatics. Her research focuses on advancing machine learning and computer vision techniques, with an emphasis on model fairness, adversarial robustness, and multimodal interactions. She leads interdisciplinary projects exploring topics such as dataset analysis, generative models, and climate action through visual narrative analysis. Research Interests: Her work bridges theoretical foundations and practical applications in domains like adversarial training, image classification robustness, and robotics perception. She explores how vision-language models can be steered to align with human biases and develops methods for data-efficient learning and interpretability. Recent Contributions: Recent work includes FAIR-TAT (model fairness via adversarial training), VSTAR (video synthesis), and TikZero (zero-shot graphics program generation). Her publications in top venues like CVPR, ICCV, and ICLR highlight contributions to both methodological innovation and real-world impact. Collaborations: Works closely with researchers across Max Planck and academic partners, focusing on projects such as sensor layout optimization, climate discourse analysis via social media imagery, and domain-aware foundation model fine-tuning.

Dale Lawrenceمشاهده پروفایل

استاد

• Astrodynamics
• Satellite Navigation Systems
• Autonomous Systems
• +۱۰ مورد دیگر

Dale Lawrence is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, where he has served continuously since 1991. He directs research at the Research and Engineering Center for Unmanned Vehicles (RECUV), focusing on astrodynamics, satellite navigation systems, and autonomous aerial platforms for atmospheric science. His academic credentials include: PhD in Electrical Engineering from Cornell University (1985) MS in Electrical Engineering from Cornell University (1982) BS in Electrical Engineering from Colorado State University (1980) Professor Lawrence's research spans spacecraft attitude control , vibration isolation , and adaptive control systems , with pioneering work in haptic interfaces for scientific visualization and teleoperation. His recent work emphasizes unmanned aerial systems for Arctic atmospheric research, particularly turbulence measurement and boundary layer studies using custom UAV platforms like DataHawk. This work bridges aerospace engineering with climate science through field campaigns such as MOSAiC and LAPSE-RATE. His publication record reveals a clear trajectory toward Arctic atmospheric science and UAV-based sensing , with increasing focus on turbulence dynamics, sea-ice interactions, and autonomous system validation. The work consistently integrates hardware development (sensors, UAVs) with field deployment in extreme environments. Selected honors include: Best Commercial Potential Award at IEEE Symposium on Haptic Interfaces (2004) Best Paper Presentation at American Control Conference (1994) Teaching Excellence Awards from University of Cincinnati (1990, 1991) Distinguished Publication Award from Martin Marietta Astronautics (1988) Professor Lawrence has led major field campaigns including MOSAiC and LAPSE-RATE, securing funding from NSF and DOE for projects like ERASMUS and ShUREX. His RECUV team develops specialized UAV platforms (DataHawk, HELiX) for atmospheric research, with recent work focusing on machine self-confidence for autonomous decision-making in complex environments. While student advising details aren't specified, his projects involve extensive student participation in hardware development and field operations. He maintains active leadership in Arctic atmospheric research through the DataHawk UAV program and HELiX multispectral systems, with ongoing work on gossamer propeller technology for high-altitude applications and machine self-confidence frameworks for autonomous systems.