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Ming JinView profile

Assistant Professor

• Trustworthy AI
• Cyber-physical systems
• Machine Learning
• +4 more

Ming Jin is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. He holds a PhD from UC Berkeley and a B.Eng. from Hong Kong University of Science and Technology. His research focuses on trustworthy AI, CPS security, and energy systems, with affiliations to the Power and Energy Center and Autonomy and Robotics @ VT. Education: PhD in Electrical Engineering and Computer Science (UC Berkeley, 2017), B.Eng. (Honors) in Electronic and Computer Engineering (HKUST, 2012). Postdoc in Industrial Engineering and Operations Research at UC Berkeley. Research interests include safe reinforcement learning, foundation models, cybersecurity, and power systems. Awards include the Siebel Scholarship (2018) and first place in the 2021 CityLearn Challenge. Active in conference organization (e.g., ICML, AAAI) and tutorial development on topics like Safe RL and CPS security. Grants include NSF support for embodied optimization (2025), Amazon-VT Initiative (2023), and Commonwealth Cyber Initiative projects. Involved in labs focused on AI, robotics, and energy systems. Publications span AI safety, RL frameworks, and CPS resilience, with over 50 peer-reviewed articles since 2015.

Bradley HayesView profile

Associate Professor

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +5 more

Bradley Hayes is an Associate Professor in the Department of Computer Science at the University of Colorado Boulder, affiliated with the College of Engineering and Applied Science. He leads the Collaborative AI and Robotics (CAIRO) Lab, focusing on creating autonomous robots that collaborate effectively with humans through advances in explainable AI, machine learning, and human-robot interaction. His prior research includes foundational work at MIT's Interactive Robotics Group and Yale's Social Robotics Lab. Research interests span Explainable AI, Learning from Demonstration, Hierarchical Reinforcement Learning, Computer Vision, Natural Language Processing, and Cognitive Science. His work emphasizes making human-robot teams more efficient and safe through innovations like emotionally expressive robotic motion, socially aware navigation, and AR-based collaboration tools. Key contributions include techniques for robust robotic exploration, generative occupancy mapping, and systems for improving human trust through predictable robot behavior. His work has been applied to teleoperation training, surgical assistance, and space exploration scenarios. Grants and partnerships support development of assistive robotic canes and AR interfaces for collaborative tasks. Lab activities emphasize translating theoretical advancements into practical systems through close collaboration between researchers, engineers, and end-users. Education efforts include developing foundational robotics curricula addressing autonomy, perception, and control systems.

Frank DittmannView profile

Researcher

• History of Electrical Engineering
• Cybernetics and Systems Theory
• Technology in COMECON
• +3 more

Dr. Frank Dittmann is a Curator at the Deutsches Museum in Munich since 2005, specializing in the history of technology. He holds a Dr. phil. in the history of technology from TU Dresden (1993) and a Dipl.-Ing. in electrical engineering (1987). Prior roles include curator positions at the Heinz Nixdorf MuseumsForum in Paderborn (1999–2005) and the Berlin City Museum (1996–1999). His research focuses on the history of electrical engineering, the genesis of cybernetics and systems theory in the Eastern Bloc, and the technological evolution of artificial intelligence and robotics. He has curated major exhibitions, including the 2022 permanent robotics exhibition at the Deutsches Museum and the 2013 energy technology update. Key projects include analyzing technology transfer during the Cold War and exploring early solar energy use. Publications span books like Technik - Innovation - Sicherheit (2021) and essays on topics such as semiconductor technology in East Germany and the history of electrical measurement systems. His work bridges historical analysis with public engagement through museum curation.

• Human-Computer Interaction (HCI) Education
• Inclusive Design
• Computing Education Research
• +3 more

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 GoosView profile

Professor

• Labor Economics
• Technological Change
• Economic Inequality
• +7 more

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 RaiView profile

Researcher

• Computational Pathology
• Deep Learning
• Digital Pathology
• +3 more

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
• +3 more

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
• +4 more

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 FisherView profile

Professor

• Autonomous Systems
• Robotics
• Formal Verification
• +3 more

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 OliveiraView profile

Assistant Professor

• Precision Agriculture
• Agricultural Engineering
• Crop Production
• +3 more

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-UrbanView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Game AI
• +3 more

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 ManfrediView profile

Senior Lecturer

• Endorobotics
• Gastrointestinal Tract Screening
• Soft Materials Engineering
• +3 more

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 PanteleyView profile

Researcher

• Nonlinear Control Systems
• Networked Systems
• Multi-Agent Systems
• +5 more

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 PoovvancheriView profile

Associate Professor

• Computer Graphics
• 3D Vision
• Machine Learning
• +8 more

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
• +4 more

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.