جست‌وجوی استاد و پژوهشگر

Samuel Marcos Pablosمشاهده پروفایل

مدرس پاره‌وقت

• Social Robotics
• Virtual Reality Education
• Emotion Recognition Systems
• +۳ مورد دیگر

Dr. Samuel Marcos Pablos is a Part-Time Lecturer at the College of Computer Science , Universidad Pontificia de Salamanca, specializing in Systems Engineering and Automation . As a member of the MARATON research group, his work focuses on mobile applications, internet of things, and data processing for healthcare robotics. PhD in Robotics (2011) from Universidad de Valladolid Supervised by Dr. Eduardo Zalama Casanova and Dr. Jaime Gómez García-Bermejo Active in social robotics, virtual reality education, and emotion recognition systems His recent work explores dynamic VR learning environments, healthcare technology integration, and emotion-aware AI systems. From 2020-2024, he has contributed to digital health ecosystems and robotic companions for elderly care. Research interests include: Human-Computer Interaction Technological Adoption in Health Sciences Emotion Recognition Tools Service Robotics Applications Medical Simulation Systems Current projects involve low-cost humanoid robot development and metaverse-based clinical training platforms, with emphasis on user acceptance and adaptive educational environments.

Martin Cooneyمشاهده پروفایل

مدرس ارشد

• Social Robotics
• Human-Robot Interaction
• Affective Robotics
• +۱۲ مورد دیگر

Martin Cooney is a Senior Lecturer at Halmstad University's School of Information Technology, where he serves as Programme Director for the Master's Programme in Information Technology (TAITE) and the Master's Programme in Embedded and Intelligent Systems (TAEIS). He holds the title of Docent (Associate Professor) in Sweden and maintains significant international collaborations, including his role as Visiting Associate Professor at Nara Women's University in Japan and Collaborative Researcher at the Deep Interaction Laboratory Group (DIL) at ATR in Kyoto. Dr. Cooney's research focuses on social robotics and human-robot interaction with applications for human well-being. His work explores how robots can recognize and respond to human emotions, support creative processes, and provide social assistance in various contexts. He has developed theoretical frameworks for designing robots capable of recognizing social touch behavior and generating appropriate responses that foster positive human-robot relationships. His research has evolved from foundational work on affectionate interaction with small humanoid robots to more complex systems addressing robot self-defense, ethical considerations in robotics, and applications in healthcare and education. His recent publications reveal a growing emphasis on robot ethics, particularly around self-defense capabilities and cultural implications of robots using force to protect humans. He has also expanded into educational applications of robotics, examining how AI and robotics can enhance teaching and learning experiences in the post-pandemic 'new world' of education. 10 awards in robotics competitions Excellent Teacher award at Halmstad University As an educator, Dr. Cooney has developed and taught courses on Design of Embedded and Intelligent Systems, User Experience Design for AI, Fundamentals of Computer Vision with Deep Learning, and Design for Extended Realities. He serves as a Responsible Examiner for several programs and has developed Robots and AI specifically for teaching purposes at his university's Pedagogical Center. His research is conducted through multiple international collaborations, most notably with the Deep Interaction Laboratory Group at ATR in Japan, where he contributes to cutting-edge research in human-robot interaction. He also serves as Local Coordinator for the EU Remind Project at Halmstad University, indicating active involvement in European research initiatives, and has previously led the KKS RELIFE project with visiting research positions in Norway, Spain, and Italy.

Erdal Aksoyمشاهده پروفایل

دانشیار

• Semantic Scene Perception
• Action Semantics
• Autonomous Systems
• +۹ مورد دیگر

Erdal Aksoy is an Associate Professor at Halmstad University 's School of Information Technology , with visiting scholar roles at Volvo Group Trucks Technology and Zenseact AB . His work focuses on semantic scene perception , action semantics , and environment understanding for autonomous systems including robots and unmanned vehicles. Education : PhD from University of Göttingen, postdoctoral research at Karlsruhe Institute of Technology (KIT) and University of Göttingen Research Interests : Semantic scene perception, action semantics, autonomous systems, human-robot interaction, LiDAR processing, and deep learning applications His recent publications demonstrate expertise in LiDAR data processing (SalsaNet, SalsaNext), semantic state estimation for robotic cloth manipulation, and multimodal failure detection systems. He has coordinated the HORIZON Europe ROADVIEW consortium with 15 partners. Scientific recognition includes Best Student Paper Award at IJCAI 2021 AI4AD workshop Best AI Master’s Thesis Award from Swedish AI Society (SAIS) Wimanska Prize for best bachelor thesis Distinguished Service Award as IEEE Robotics and Automation Letters Associate Editor His advising track record shows mentorship of award-winning students across bachelor, master, and PhD levels. Erdal Aksoy maintains active collaborations between academia and industry, particularly with automotive technology companies.

Michael Madaryمشاهده پروفایل

دانشیار

• Philosophy of Mind
• Ethics of Emerging Technology
• Philosophy of Perception
• +۲ مورد دیگر

Michael Madary is an Associate Professor and Department Chair in the Department of Philosophy at the University of the Pacific. He holds a PhD in Philosophy from Tulane University (2007), an MA in Philosophy/Cognitive Science from the University of Houston (2003), and a BA in Philosophy from the University of Dallas (1999). Education PhD, Philosophy, Tulane University, 2007 MA, Philosophy / Cognitive Science, University of Houston, 2003 BA, Philosophy, University of Dallas, 1999 Research Interests Madary's research spans the philosophy of mind, ethics of emerging technology, and philosophy of perception using an interdisciplinary approach integrating psychology, neuroscience, and history of philosophy. He co-authored the pioneering Code of Ethics for Virtual Reality (2016), covered by major media including The New Yorker and The Guardian, and authored Visual Phenomenology (MIT Press, 2017). Current work explores technology's impact on human cognition and agency through experiential learning frameworks. Publication Trends His recent publications (2023-2016) reveal sustained focus on virtual reality ethics, illusion of agency in human-computer interaction, and Husserlian phenomenology applied to technology. Key themes include mediated reality, cognitive technology ethics, and perceptual abnormalities, consistently bridging theoretical philosophy with practical technological concerns. Professional Impact Madary co-founded the first VR ethics code with Thomas Metzinger, influencing industry standards and generating international media discourse. His public engagement includes CBC Radio interviews and podcasts like Overthink and 88 Names, addressing virtual reality's societal implications and therapeutic potential.

• Machine Learning
• Artificial Intelligence
• Case-Based Reasoning
• +۵ مورد دیگر

Kerstin Bach is a Professor in Artificial Intelligence at the Norwegian University of Science and Technology (NTNU), where she serves as Director of the Norwegian Open AI Lab and Research Director of the Norwegian Research Center for AI Innovation (NorwAI). She also holds the position of Deputy Head of the Data and Artificial Intelligence group within NTNU's Department of Computer Science. Her leadership extends to multiple national AI initiatives that bridge industry and academia in Norway. Dr. Bach earned her Dr. rer. nat. (summa cum laude) in Computer Science from the University of Hildesheim, Germany in 2012. Prior to joining NTNU in 2015, she worked as a researcher at the German Research Center for AI (DFKI) and as both a research scientist and software engineer at Verdande Technology, an AI startup developing case-based reasoning technology for various industries. Her research focuses on developing AI methods that combine reasoning, context-awareness, and interpretability to support complex, knowledge-intensive decisions. She specializes in case-based reasoning, explainable AI, and human-AI interaction, with particular emphasis on healthcare applications. Her work explores how to build transparent AI systems that work across domains and are grounded in real-world use cases, especially in medical decision support and patient-centered care. Analysis of her recent publications reveals a strong focus on applying AI to healthcare challenges, particularly musculoskeletal pain management through the selfBACK project. Her research spans human activity recognition, explainable AI methods, clinical decision support systems, and reinforcement learning applications. A consistent theme is the development of trustworthy AI systems that maintain interpretability while addressing complex healthcare problems. Dr. Bach actively mentors students and has established FEMAIS, a mentorship program for aspiring female AI students. She serves on the boards of both the Norwegian AI Society and the German AI Society, demonstrating her commitment to advancing the field and promoting diversity in AI. She leads multiple interdisciplinary projects funded by the Norwegian Research Council and NTNU, focusing on AI-driven healthcare services. Her leadership in the Norwegian Open AI Lab involves organizing events, giving talks, and participating in panels to discuss AI research with both professionals and the public.

• Instructional Technology
• Learning Sciences
• Early Childhood Education
• +۷ مورد دیگر

Jody Clarke Midura is Associate Dean for Graduate Studies and faculty member in the Department of Instructional Technology & Learning Sciences at Utah State University’s Emma Eccles Jones College of Education and Human Services. She leads graduate programs while actively researching the integration of computer science, mathematics, and early childhood education. Education: While specific degrees are not listed in the provided text, her prolific research record in instructional technology and learning sciences indicates advanced graduate training in education, computer science education, or learning sciences. Research Interests: Computational Thinking in Early Childhood: Designing assessments and curricula that introduce programming concepts to kindergarten and elementary learners using tangible coding toys. Cross-Curricular Integration: Blending mathematics and computer science instruction to leverage synergies between pattern recognition, algorithmic reasoning, and mathematical concepts. Assessment Design: Creating stealth, game-based, and performance assessments that capture young learners’ computational and mathematical thinking. Educational Data Mining & AI: Employing learning analytics and generative AI tools to analyze classroom interaction data and improve instructional design. Research Trajectory: Across more than 50 recent publications (2022–2025), Midura explores how robot toys, board games, and digital platforms can foster early computational thinking, spatial reasoning, and multiplicative understanding. A consistent theme is participatory design—engaging teachers and students as co-designers of culturally relevant, inclusive CS and math activities. Awards & Honors: No specific awards are mentioned in the provided text. Lab, Teams & Collaborations: Midura works closely with interdisciplinary teams within the Emma Eccles Jones College, including the Center for the School of the Future, integrating research and practice partnerships with local elementary schools to pilot and scale innovative curricula.

Le Chenمشاهده پروفایل

پژوهشگر

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

Le Chen is a Doctoral Researcher at the Empirical Inference Department of the Max Planck Institute for Intelligent Systems and ETH Zurich , advised by Prof. Bernhard Schölkopf and Prof. Dieter Büchler. Previously, he obtained his M.S. in Electrical Engineering and Information Technology from ETH Zurich and gained research experience at Microsoft Mixed Reality & AI Lab, Tencent AI Lab, and Tencent Robotics X Lab. Research Interests: Le Chen focuses on the intersection of robotics and machine learning, with a specific emphasis on reinforcement learning for dexterous manipulation, visual-inertial calibration, and uncertainty-aware robotic perception. His work spans dynamic motion control, policy gradient subspaces, and novel algorithms for 3D/4D reconstruction. Key Contributions: He co-developed the RP1M dataset for bimanual piano manipulation and contributed to tendon-driven robot design ( Safe & Accurate ) and LEAP-VO for robust visual odometry. His research also includes Gaussian splatting dynamics for 4D content creation ( GaussianFlow ). Scientific Awards: Best Systems Paper Finalist at RSS 2024 for the RP1M dataset

Manling Liمشاهده پروفایل

استادیار

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Manling Li is an Assistant Professor at the Department of Computer Science, Northwestern University. She previously served as a postdoc at Stanford University's Vision and Learning Lab under Prof. Jiajun Wu and received her Ph.D. from the University of Illinois at Urbana-Champaign (advisor: Prof. Heng Ji). Her research spans Language + Vision + Robotics with applications in Embodied AI and AI for Science . Key Research Areas : Knowledgeable Foundation Models, Reasoning & Planning, Compositionality, Multimodal Knowledge Extraction, Factuality & Trustworthiness in AI Leadership Roles : Organizing Committee for ACL 2025, NAACL 2025, EMNLP 2024 Research Trends in her 15 most recent publications show: Advancing Embodied AI through structured reasoning and planning frameworks Developing Vision-Language Models for 3D layout optimization and video understanding Addressing LLM Hallucinations via knowledge shadowing and mechanistic interpretability Creating collaborative agent systems with out-of-sync recovery mechanisms Scientific Recognition : ACL 2024 Outstanding Paper SoCal NLP 2024 Best Paper Microsoft Research Fellowships (PhD & Postdoc) DARPA Riser & EE CS Rising Star Advising Impact : Mentored 19 students in developing the UIUC information extraction system. Currently advising 12 students across PhD, Master's, and undergraduate levels, with particular emphasis on supporting underrepresented groups. Led teams to rank 1st in DARPA AIDA evaluations.

• Robotics
• Human-Robot Interaction
• Motion Prediction
• +۵ مورد دیگر

Emmanuel Dean is a Senior Researcher in the Automation research group at Chalmers University of Technology, School of Electrical Engineering. His work focuses on robotics, human-robot interaction, and assistive technologies. Dean's research interests span multiple areas of robotics and human-computer interaction: Robotics and autonomous navigation systems Human-robot collaboration and interaction Tactile sensing and physical interaction Motion prediction and obstacle avoidance Brain-computer interfaces for robotic control Assistive robotics for physical therapy His recent publications show a strong focus on developing advanced navigation systems for mobile robots that can predict human motion and avoid collisions in dynamic environments. Dean has also made significant contributions to tactile-based interaction methods, particularly for assistive robotics applications in physical therapy contexts. Dean has received research funding for the CRAFT (Collaborative-Robot Assistant for Technicians) project (2021-2023), which focused on developing robotic assistants for industrial technicians. His work demonstrates strong interdisciplinary collaboration, with publications spanning robotics, neuroscience, and rehabilitation engineering.

• Robotics
• Control Systems
• Reinforcement Learning
• +۴ مورد دیگر

Zhen Kan is a Professor in the Mechanical and Aerospace Engineering Department at the University of Florida's College of Engineering, with previous affiliations at the University of Iowa and the Air Force Research Laboratory (AFRL). His extensive publication record spans over 15 years with significant output in recent years, indicating an active research career in robotics and control systems. Dr. Kan's research focuses on advanced robotics systems with expertise in temporal logic motion planning, reinforcement learning, and human-robot interaction. His work bridges theoretical control systems with practical robotics applications, particularly in multi-robot coordination, autonomous systems, and wearable robotics. The research demonstrates a strong emphasis on formal methods for ensuring safety and correctness in complex robotic systems. Analysis of recent publications reveals a consistent research trajectory centered around temporal logic specifications for robotic systems, with increasing integration of machine learning techniques. His work shows progression from theoretical control frameworks to practical implementations in quadruped robots, exoskeletons, and multi-robot systems operating in dynamic environments. Dr. Kan has established significant collaborations with researchers across multiple institutions, particularly with Warren E. Dixon (35 co-authored papers), Zhijun Li (23 papers), and Mingyu Cai (22 papers), indicating leadership in collaborative research projects. His publications appear in top-tier venues including IEEE Transactions on Robotics, IEEE Transactions on Automatic Control, and International Journal of Robotics Research. While specific grant information isn't visible in the provided text, the volume and quality of publications suggest substantial research funding. Dr. Kan's work has practical applications in autonomous systems, human-robot collaboration, and assistive technologies, with potential impact in defense, healthcare, and industrial automation sectors.

Benjamin Altمشاهده پروفایل

پژوهشگر

• Cognitive Robotics
• Neurosymbolic AI
• AI Safety
• +۴ مورد دیگر

Dr. Benjamin Alt serves as the Technical Director at the AICOR Institute for Artificial Intelligence, affiliated with the University of Bremen. His research focuses on enabling robots to understand and execute complex manipulation tasks collaboratively with humans, emphasizing cognitive robotics , neurosymbolic AI , AI safety , and human-AI interaction . Education: PhD (Dr.-Ing.) in Computer Science, University of Bremen. Current Role: Technical Director at AICOR Institute, operationalizing research strategy and coordinating interdisciplinary teams. Research Goals: Building embodied AI systems that are intuitive, explainable, and safe for human collaboration.

Milton Aguirreمشاهده پروفایل

استادیار

• Compliant Mechanisms
• Wearables and Exoskeletons
• Human-Centered Product Design
• +۲ مورد دیگر

Milton Aguirre serves as Assistant Professor at Purdue Polytechnic Institute, Purdue University, leveraging over ten years of market-oriented product design expertise to bridge academic research and entrepreneurship. His work in creative mechanism design has driven international technology valorization initiatives, including concept-to-market projects during his post-doctoral tenure at Delft University of Technology. His academic foundation includes a Post-Doctorate from Delft University of Technology's Department of Mechanical, Maritime, and Materials Engineering, Ph.D. and M.S. degrees in Mechanical Engineering from Pennsylvania State University, and a B.S. in Mechanical Engineering from Virginia Military Institute. Dr. Aguirre's research centers on compliant mechanisms, wearables and exoskeletons, and human-centered product design, with strong emphasis on medical device innovation. He investigates mechanical systems that enhance user interaction, particularly in surgical tools and mobility assistance, focusing on translating academic concepts into commercial products through rigorous market-oriented development. His 2021-2025 publications reveal dominant trends in medical device engineering, especially compliant mechanisms for surgical safety and mobility aids. Key themes include haptic feedback integration in walking canes, force-sensitive surgical graspers, and stress management wearables, demonstrating consistent focus on user-centered solutions for healthcare challenges. Major funded projects include: 2024 NIH STTR/SBIR Phase I grant for stress management intervention development 2023 NIST grant on standards in product innovation Multiple NIH MedTech Think Tank projects for mental health and mobility devices Industry-sponsored mobility aid device research As Seed Lab director, he leads interdisciplinary teams developing stress management technologies and mobility aids through NIH collaborations and industry partnerships. His work emphasizes rapid prototyping and commercialization pathways, with recent projects including an NIH-funded stress management device and mobility assistance systems.

• Robotics
• Mechatronic Systems
• Human-Robot Interaction
• +۴ مورد دیگر

Xiumin Diao is an Associate Professor at Purdue University's School of Engineering Technology, specializing in robotics and mechatronic systems for healthcare and manufacturing applications. His work emphasizes human-robot interaction, control algorithms, and energy-efficient UAV designs. Education: Ph.D. in Mechanical Engineering (2007, New Mexico State University) M.S. in Measurement Technology and Automatic Device (2003, Beihang University) B.S. in Mechanical Design and Manufacturing (2000, Yantai University) Research focuses on cable-driven parallel robots , reinforcement learning , and intention prediction using neural networks. Recent publications explore stiffness analysis, UAV arm rotation efficiency, and hybrid control strategies. Key trends in his work include: Advancing adaptive control for robots with unknown dynamics Optimizing energy efficiency in aerial robotics Applying deep learning to human motion understanding His lab develops hardware-in-the-loop microgravity simulators and rehabilitation devices, with applications in disaster exploration and satellite docking.

Aude Billardمشاهده پروفایل

استاد

• Robotics
• Human-Robot Interaction
• Imitation Learning
• +۷ مورد دیگر

Aude Billard is a Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she leads the Learning Algorithms and Systems Laboratory (LASA). Her work focuses on enabling robots to learn complex tasks through human demonstration, with applications in manipulation, sports, and safe human-robot interaction. Her educational background includes: M.Sc. in Physics, EPFL (1995) M.Sc. in Knowledge-Based Systems, University of Edinburgh (1996) Ph.D. in Artificial Intelligence, University of Edinburgh (1998) Aude Billard's research centers on imitation learning, where robots learn from few demonstrations and even failed attempts to improve generalization and robustness. She emphasizes feasibility over optimality in control, modeling human-like variability to allow rapid adaptation in dynamic environments. Her work enables robots to perform delicate tasks like handling fragile objects and reacting instantly to perturbations, such as catching fast-moving items or playing golf with moving targets. Her research has been widely recognized and featured in BBC and IEEE Spectrum, highlighting its impact on real-world robotics applications. Notable scientific recognitions include: Intel Corporation Teaching Award Swiss National Science Foundation Career Award Outstanding Young Person in Science and Innovation (Swiss Chamber of Commerce) IEEE-RAS Best Reviewer Award Seven best paper awards at premier robotics conferences (ICRA, IROS, ROMAN) She has played key leadership roles in the robotics community, serving as an elected member of the IEEE Robotics and Automation Society Administrative Committee (2006–2008, 2009–2011), keynote speaker at ROMAN 2005, General Chair for HRI 2011, and Co-General Chair for Humanoids 2006. She has also contributed significantly to conference organization and peer review excellence. Aude Billard leads the Learning Algorithms and Systems Laboratory (LASA) at EPFL, a leading research group dedicated to developing intelligent robotic systems capable of learning complex motor skills through interaction with humans and environments.

Aldo Jonathan Muñoz Vazquezمشاهده پروفایل

دانشیار

• Robotics and autonomous systems
• Sliding mode techniques for control and observation
• Fractional calculus applications
• +۲ مورد دیگر

Aldo Jonathan Muñoz Vazquez serves as an Instructional Associate Professor in the Department of Multidisciplinary Engineering at Texas A&M University, where he focuses on advanced control systems research. He holds significant recognition as a Level I member of the Mexican National System of Researchers (SNI) and contributes to academic discourse as Associate Editor for Transactions of the Institute of Measurement and Control and International Journal of Control, Automation and Systems, following prior editorial service for IEEE Latin America Transactions (2018-2019). His research centers on Robotics and autonomous systems, Sliding mode techniques for control and observation, Fractional calculus applications, Fuzzy logic-based control, and Lyapunov stability theory. These interconnected domains emphasize developing robust, stable control strategies for complex systems with real-time performance guarantees, particularly addressing challenges in nonlinear dynamics and time-constrained operations. Recent publications reveal a concentrated research trajectory in predefined-time control methodologies, fractional-order systems, and sliding mode techniques applied to robotics and electromechanical systems. This work demonstrates consistent innovation in cooperative manipulation, second-order system stabilization, and data-driven control frameworks across high-impact engineering journals. His scientific recognition includes: Member of the Mexican National System of Researchers (SNI), Level I Publons Peer-review Award: Top 1% of Reviewers in Engineering While current advising activities and grant funding details remain unspecified in available records, his editorial roles and research output indicate active engagement in the global control engineering community. Laboratory affiliations or specialized research teams are not documented in the provided materials.