جستجوی استاد راهنمای دانشگاهی

Giulio Fontana is affiliated with the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. His research spans robotics, artificial intelligence, and their applications in agriculture and healthcare. He contributes to benchmarking frameworks like ACRE and RoCKIn, focusing on standardized evaluation of robotic systems and AI applications. Primary Affiliation: Politecnico di Milano (DEIB) Research Focus: Robotics, AI, Agricultural Engineering, Bioengineering Fontana has pioneered benchmarking competitions such as ACRE (Agri-Food Competition for Robot Evaluation) and RoCKIn, emphasizing quantitative metrics for robotic performance. His work includes AI-driven pesticide reduction in agriculture, SLAM (Simultaneous Localization and Mapping) in autonomous robotics, and assistive devices for hospital logistics. Recent publications highlight AI-sprint for runtime management of AI applications and multimodal interfaces for robotic wheelchairs. Scientific Contributions : Coordinated design of benchmarking competitions (ACRE, RoCKIn) Developed SLAM benchmarking datasets (Rawseeds project) Innovated AI applications for sustainable agriculture Engineered assistive mobility solutions for healthcare

• Robotics
• Artificial Intelligence
• Agricultural Engineering
• +۳ مورد دیگر

Gwenn Englebienne is an Assistant Professor at the Digital Society Institute and Human Media Interaction group of Utrecht University. Their research focuses on Artificial Intelligence, Computer Vision, and Human-AI Interaction, with applications in robotics, health, and social computing. They have contributed to over 80 research outputs since 2007, emphasizing embodied AI, social robotics, and explainable machine learning. Research interests span activity recognition, teleoperation systems, and ethical AI design. Notable work includes developing GNN-based group detection algorithms and evaluating chatbot reliability through automated question-answering frameworks. Their studies often bridge technical innovation with human-centered design, such as measuring embodiment via pupil dilation or addressing asymmetry in video-conferencing interactions. Key collaborations include work on social robotics, telepresence systems, and health monitoring using ambient sensors. Publications span conferences like IDA, CogMI, and LREC-COLING, reflecting interdisciplinary impact. A dataset on robot social positioning behavior is publicly accessible via 4TU.Centre for Research Data. Current work explores semi-supervised domain adaptation, spiking neural networks, and the psychological dimensions of AI trustworthiness. They lead initiatives in the Digital Society Institute to align technological advancements with societal needs.

• Artificial Intelligence
• Computer Vision
• Natural Language Processing
• +۵ مورد دیگر

Kechen Zhang is an Associate Professor of Biomedical Engineering and Neuroscience at Johns Hopkins University School of Medicine. He holds affiliations with the Center for Hearing and Balance and the Kavli Neuroscience Discovery Institute. His research focuses on theoretical and computational neuroscience, particularly neural computation and spatial navigation models. Zhang earned a B.S. and M.S. from Peking University, a Ph.D. in Cognitive Science from UC San Diego, and completed a postdoc at the Salk Institute. Research Interests Zhang’s lab studies nervous system dynamics using mathematical and computational models, collaborating with experimental labs. Key areas include grid cells, place cells, path integration, oscillatory interference models, and neural coding mechanisms. His work bridges biophysical models and network-level computations. Publications Over 30 peer-reviewed articles in Neural Computation , PNAS , Journal of Neuroscience , and others, addressing topics like attractor networks, theta rhythms, and spatial representation. Recent work explores cognitive swarming and neuro-inspired robotics. Collaborations & Teaching Collaborates with Jim Knierim, Xiaoqin Wang, and others. Teaches Biomedical Systems II , Theoretical Neuroscience , and co-leads the Johns Hopkins Systems Neuroscience Journal Club.

• Theoretical Neuroscience
• Computational Neuroscience
• Neural Computation
• +۳ مورد دیگر

Jun Zhang is an Assistant Professor in the Mechanical Engineering Department at the University of Nevada, Reno. His research focuses on control systems, robotics, smart materials, and artificial muscles, with a particular emphasis on biomimetic, soft, and assistive robotics applications. He leads the Smart Robotics Lab, which develops technologies like twisted string actuators for advanced robotic systems. Dr. Zhang teaches courses including ME410 (Introduction to System Control) and ME422/622 (Introduction to Robotics). While specific educational details are not provided in the text, his work indicates expertise in mechanical engineering and robotics. His research spans from fundamental actuator modeling to practical applications in soft robotics and haptic systems. Over 30 articles from 2012–2025 highlight his contributions to smart materials, hysteresis compensation, and robotic actuation technologies. Current projects emphasize interdisciplinary approaches to enable more capable and adaptive robotic systems. Prospective students are encouraged to contact him regarding research assistantships requiring 12+ weekly hours. No scientific awards are explicitly listed. The Smart Robotics Lab’s work integrates innovation with real-world applications, such as assistive devices and advanced manufacturing techniques.

• Control Systems
• Robotics
• Smart Materials
• +۳ مورد دیگر

Nashra Ahmad is a Research Fellow at Durham University, affiliated with the Department of Music and the Institute for Medical Humanities. She is a PhD candidate supported by the Durham Doctoral Studentship and holds a Master's in Cognitive Science from IIT Gandhinagar (2021) and a BA in Psychology (First Class Honours) from Aligarh Muslim University (2018). Her research focuses on rhythm perception, consonance/dissonance dynamics, and music cognition, combining neuroscience and interdisciplinary approaches. She is an active member of the Music and Science Lab and an editorial assistant for DURMS . Additionally, she teaches Psychology at the Durham Centre for Academic Development (DCAD). Key research interests include: rhythmic entrainment in North Indian classical music, sensorimotor synchronization, and neural correlates of musical perception. Her work bridges cognitive science, musicology, and technology, with publications in Data in Brief , Frontiers in Neurorobotics , and Music & Science . Awards include the Sabarmati Bridge Fellowship (2021) for pre-doctoral research and the Durham Doctoral Studentship (2022). Education: Bachelor of Arts in Psychology (First Class Honours), Aligarh Muslim University, 2018 Masters in Cognitive Science, Indian Institute of Technology Gandhinagar, 2021 Her publications analyze EEG responses to music, resonance strategies in AI design, and beat prediction from neural data. She has presented at international conferences such as the International Conference of Students of Systematic Musicology (2023) and the Max-Planck-Institut für empirische Ästhetik (2022). Awards: 2022: Durham Doctoral Studentship 2021: Sabarmati Bridge Fellowship Teaching and Outreach: She teaches Psychology to foundation-year students at DCAD and has prior experience teaching guitar and music theory in India. Her creative interests include landscape painting and sculpting, reflecting her interdisciplinary engagement with art and science.

• Rhythm Perception
• Pattern Recognition
• Music and Entrainment
• +۳ مورد دیگر

Dr. Mihailo Ristic is a Senior Lecturer in the Department of Mechanical Engineering at Imperial College London, part of the Faculty of Engineering. He holds a First Class Honours Degree in Mechanical Engineering from University College London (1981), an M.Sc. in Control Systems (Imperial College London, 1982), and a Ph.D. in Robotics (Imperial College London, 1986). His research spans control systems, CAD/CAM, robotics, and medical engineering, with recent focus on Magnetic Resonance Imaging (MRI) systems and mechatronic devices for clinical applications. Dr. Ristic is a Chartered Engineer and Fellow of the Institution of Mechanical Engineers. He co-founded Turbo Power Systems, specializing in high-speed electric machines and power electronics. His work integrates robotics, medical imaging, and advanced manufacturing, addressing challenges in distributed power generation and biomedical device design. Key projects include novel MRI magnet configurations, intraoperative MRI tools, and robotic systems for MRI-guided interventions. Education: B.Sc. (First Class Honours) Mechanical Engineering, University College London (1981) M.Sc. Control Systems, Imperial College London (1982) Ph.D. Robotics, Imperial College London (1986) Affiliations: Robotics Forum CAD/CAM Research Group Mecheatronics in Medicine His research interests include medical engineering innovations, such as MRI system design, collagen fiber analysis, and robotic-assisted surgery. He has contributed to over 50 publications in journals and conferences, focusing on imaging technologies, robotics, and mechatronics. His work bridges academic research and industrial applications, particularly in energy systems and biomedical devices. Dr. Ristic’s awards include the Fellowship of the Institution of Mechanical Engineers. His grants and projects involve collaborations with industry partners to advance MRI hardware, teleoperated surgical systems, and energy-efficient power solutions.

• Medical Engineering
• Biomedical Engineering
• Control Systems
• +۷ مورد دیگر

Tim Salcudean is a Professor in the Department of Electrical & Computer Engineering and School of Biomedical Engineering at the University of British Columbia, holding the Charles A. Laszlo Chair in Biomedical Engineering. His research focuses on medical robotics, teleoperation systems, and image-guided interventions, with notable contributions to ultrasound technology, needle steering, and surgical robotics. He collaborates with clinicians to advance diagnostic and therapeutic methods, particularly in prostate cancer imaging and robot-assisted surgery. Key research themes include haptic interfaces, control systems for teleoperation, and biomedical device development. His work combines robotics, control theory, and medical imaging to enhance precision and safety in surgical procedures. Notable projects involve robotic systems for medical ultrasound and adaptive control strategies for stable teleoperation under time delays. Publications span over three decades, emphasizing medical robotics, image-guided interventions, and control systems. His research has been widely cited, reflecting significant impact in both engineering and healthcare fields. Current efforts aim to integrate artificial intelligence with medical imaging to improve cancer diagnosis and treatment planning.

• Medical Robotics
• Image-guided Surgery
• Teleoperation Systems
• +۳ مورد دیگر

Mattia Bacca is an Associate Professor in the Department of Mechanical Engineering at the University of British Columbia (UBC), affiliated with the School of Biomedical Engineering (SBME) and the Human Interfacing Devices research core. His work bridges mechanical engineering with biomedical applications, focusing on advanced material mechanics and biological systems. Research Interests : Mechanics of materials and nanomaterials Lipid membranes, viruses, and nanoparticle dynamics Mechanobiology and cytoskeletal mechanics Puncture mechanics and soft tissue interaction Design of hydrogels and biomaterials Research Trends : Recent work emphasizes mechanics of soft materials, biomimetic systems (e.g., insect-inspired cutting behaviors), and applications of machine learning in material design. Key contributions include theoretical models for puncture mechanics and viscoelastic characterization of biological tissues. Awards/Grants : No awards explicitly listed in the provided texts. His research is likely supported by grants focused on biomedical engineering and materials science. Labs/Teams : Active in the Human Interfacing Devices core within SBME, collaborating on projects involving bioinspired adhesives, microneedle arrays, and cancer cell mechanics.

• Mechanics of Materials
• Biomedical Engineering
• Mechanobiology
• +۴ مورد دیگر

Dr. Cameron N. Riviere is a Research Professor at Carnegie Mellon University (CMU), affiliated with the Robotics Institute, Department of Biomedical Engineering, and Department of Mechanical Engineering. He also holds an Adjunct Professorship at the University of Pittsburgh’s Department of Rehabilitation Science and Technology. His research focuses on surgical robotics, medical devices, and control systems, emphasizing minimally obtrusive robotic systems for microsurgery and minimally invasive surgery. Key projects include the Micron handheld tremor-canceling device and the HeartLander cardiac robot. Education: B.S. in Aerospace and Ocean Engineering from Virginia Tech (1989), Ph.D. in Mechanical Engineering from Johns Hopkins University (1995). Research Interests: Medical robotics, rehabilitation robotics, control systems, human-machine interfaces for biomedical applications, and physiological motion compensation. Recent work includes development of robotic systems for retinal surgery, cardiac therapy, and assistive technologies for individuals with movement disorders. Awards Best Paper of 2016 (IEEE/ASME Transactions on Mechatronics) Finalist for Best Medical Robotics Paper (IEEE ICRA 2016) Best Paper (IEEE MFI 2015, IROS 2014) Advising and Grants: Mentor to PhD students (e.g., Arpita Routray) and masters students (e.g., Aditti Ramsisaria). Projects include the HeartLander epicardial therapy robot and advanced tracking systems for handheld surgical tools. Collaborates with institutions like Mayo Clinic and NIH-funded initiatives. Labs: Director of the Surgical Mechatronics Laboratory at CMU’s Robotics Institute, focusing on interdisciplinary development of robotic systems for clinical applications.

• Medical Robotics
• Surgical Robotics
• Control Systems
• +۵ مورد دیگر

Kimberlee Kearfott, Sc.D., is a Professor in the Department of Nuclear Engineering and Radiological Sciences at the University of Michigan. Her primary affiliation is with the College of Engineering, and she holds an additional role as Affiliate Faculty in Biomedical Engineering (BME). Her research focuses on radiation protection, nuclear medicine, medical physics, and biomedical imaging. Key areas include radon gas dynamics, dosimetry techniques, environmental radiation monitoring, and the development of radiation-aware technologies like drones and weather stations. Her work spans theoretical and applied domains, including algorithm development for anomaly detection in radon time series data, advanced imaging systems, and radiation source mapping. She has contributed to the design of cost-effective radiation measurement instruments and systems for real-time environmental monitoring. Notable projects include the creation of an Intelligent Radiation Awareness Drone and a Low-cost Radiation Weather Station. Dr. Kearfott’s expertise also extends to radiation safety protocols, quality control in dosimetry calibration, and the application of machine learning to thermoluminescent dosimeter analysis. Her research has addressed critical issues such as earthquake prediction through radon gas analysis and sterilization techniques for SARS-CoV-2-contaminated equipment. Her laboratory focuses on interdisciplinary projects at the intersection of nuclear engineering, biomedical sciences, and environmental science. Collaborations involve both academic and industrial partners, emphasizing practical solutions for radiation-related challenges in healthcare, environmental safety, and homeland security.

• Radiation Protection
• Nuclear Medicine
• Medical Physics
• +۳ مورد دیگر

Joseph J. LaViola Jr. is the Charles N. Millican Professor of Computer Science at the University of Central Florida's Department of Computer Science. He is also affiliated with the Institute for Simulation and Training. His research focuses on 3D user interfaces (3DUI), virtual reality (VR), augmented reality (AR), pen-based computing, human motion estimation, and human-robot interaction. He serves as the director of the Interactive Computing Experiences Research Cluster and has authored influential textbooks like 3D User Interfaces: Theory and Practice . LaViola leads research initiatives in immersive technologies, emphasizing practical applications in gaming, education, and collaborative environments. His work spans gesture interaction design, spatial navigation, and AR/VR system development. He actively mentors students at undergraduate, master's, and Ph.D. levels, encouraging creativity and dedication in research projects. His recent publications explore topics such as redirected walking in VR, dual-camera interactions for smartphone AR, and perceptual studies in immersive environments. He emphasizes bridging academic research with real-world applications, particularly in healthcare, civil engineering, and human-centered systems. LaViola's contributions include advancing gesture recognition techniques, optimizing VR/AR interfaces for accessibility, and fostering interdisciplinary collaboration through his lab and authored tools like AffordIt! and MathPad 2 .

• Computer Science
• Virtual Reality (VR)
• Augmented Reality (AR)
• +۶ مورد دیگر

Dr. Muhammad Salman is an Associate Professor in the Department of Mechanical Engineering at Kennesaw State University (KSU), where he has served since 2012 after the merger of Southern Polytechnic State University into KSU. He holds a PhD in Mechanical Engineering from Georgia Institute of Technology (2012), an M.S. from Georgia Tech (2008), and prior degrees from the University of Engineering and Technology in Lahore, Pakistan, including a B.S. (1998) and M.S. (2003). He also completed M.S.-level courses in Mechatronics Engineering at TUHH, Germany (2005). His research focuses on biomechanics, particularly in dynamics and vibrations of human musculoskeletal systems, with an emphasis on non-invasive measurement techniques like surface wave and shear wave methods to assess muscle/tendon stiffness. He has developed cost-effective devices for stiffness quantification and published extensively in journals such as Journal of Biomechanics and Acoustical Society of America . Dr. Salman has received notable recognition, including the PhD Fulbright Scholarship (2006) , and has secured grants totaling over $500,000, including an NSF CAREER Award (though not funded) and OVPR grants for tendon stiffness research. His work involves collaborations with students on projects like motorcycle stability systems, muscle fatigue analysis, and biomedical sensor development. He teaches courses in dynamics, vibrations, thermodynamics, and design, and has mentored numerous undergraduates and graduates in research through programs like NCUR and GURC. His lab emphasizes experimental research, with a focus on biomechanical applications of vibration analysis and sensor technology. Recent projects include developing low-cost stiffness measurement tools and studying tendon behavior under fatigue. He actively participates in conferences such as ASME IMECE and the American Society of Biomechanics, showcasing innovations in both mechanical engineering and biomedical research.

• Biomechanics
• Vibration Analysis
• Mechanical Engineering
• +۳ مورد دیگر

Prof. Felix Bießmann holds a professorship in Computer Science and Media at Berlin University of Applied Sciences' Department VI. His research focuses on machine learning applications in diverse fields including healthcare, urban planning, environmental science, and robotics through his Cognitive Algorithms Lab. He teaches courses such as Machine Learning, Deep Learning, and Data Science Workflows, alongside roles at TU Berlin and Korea University. Education: PhD (Dr. rer. nat.) in Natural Sciences Research interests span machine learning theory and practical implementations across domains like computer vision, generative AI, and sensor data analysis. His work addresses challenges in automated systems, healthcare monitoring, and sustainable technologies. Recent student theses explore topics like license plate recognition, adaptive game soundtracks, and bird song detection using TinyML. Collaborations include projects with the Charité Berlin and Robert-Koch Institute. Lab: Cognitive Algorithms Lab (developing machine learning methods/applications) Contact: felix.biessmann@bht-berlin.de | Office D138, Berlin University of Applied Sciences.

• Machine Learning
• Artificial Intelligence
• Computer Science
• +۳ مورد دیگر

Eunsik Kim is a Professor at the University of Windsor , holding a position in the Department of Mechanical, Automotive, and Materials Engineering within the Faculty of Engineering . His research focuses on ergonomics, occupational safety, and biomechanics, with applications in automotive design, workplace safety, and human-machine interaction. He leads the Occupational Safety and Ergonomics research lab , where students explore real-world solutions for challenges such as driver fatigue, musculoskeletal risks in manual labor, and automation in agriculture. Key research interests include: Ergonomics : Optimizing workstation designs, automotive seating, and anti-vibration tools Biomechanics : Analyzing human posture, musculoskeletal loading, and workplace ergonomics Machine Learning : Developing AI-driven systems for posture recognition, workload prediction, and task automation Autonomous Vehicles : Investigating human factors in driving automation and takeover scenarios Education Innovation : Gamification in engineering labs to enhance student motivation and learning Collaborations include projects with Ewha Womans University (South Korea) on autonomous vehicle comfort and a prototype robotic system for mushroom harvesting. His work often bridges theoretical research with practical applications, addressing both industry and academic challenges. Awards and Recognition: Students Ilfeoma Michael and Elnaz Akhavan Rezaee received accolades at the Association of Canadian Ergonomists conference for their lab research Advising and Grants: Professor Kim mentors students in interdisciplinary projects, focusing on ergonomics, robotics, and AI. His research has led to innovations in workplace safety and automated systems, supported by institutional and collaborative funding. Labs/Teams: The Occupational Safety and Ergonomics Lab and partnerships with South Korean institutions drive cutting-edge studies in automotive safety, robotics, and human factors engineering.

• Ergonomics
• Biomechanics
• Human Factors Engineering
• +۵ مورد دیگر

Nitish V. Thakor is a Professor of Biomedical Engineering and Neurology at Johns Hopkins University School of Medicine, with secondary appointments in Electrical and Computer Engineering. He directs the Laboratory for Neuroengineering and oversees the NIH Neuroengineering Training Grant. His research focuses on neural prosthetics, brain-machine interfaces, and clinical neurorehabilitation technologies. Education: B.Tech from IIT Bombay (India), M.S. and Ph.D. in Biomedical Engineering from University of Wisconsin-Madison Joined Johns Hopkins faculty in 1983 Research emphasizes translational neuroengineering: developing prosthetic limbs with sensory feedback, advanced neural interfaces, and diagnostic technologies for brain injury monitoring. The lab integrates microfabrication, stem cell biology, and integrated circuit design with clinical applications. Notable projects include DARPA-funded advanced prosthetic systems and temperature-sensitive prosthetic fingertips. Recent lab milestones include robotic hand research published in Science Advances, and student achievements like NIH fellowships and Siebel Scholar awards. Honors: IEEE Fellow (1997), AIMBE Fellow (1996), NSF Presidential Young Investigator (1985) Advising over 20 students/postdocs, he also serves as editor-in-chief of Medical and Biological Engineering and Computing . Active in global biomedical engineering outreach through conferences and educational programs.

• Biomedical Engineering
• Neuroengineering
• Neural Prosthetics
• +۵ مورد دیگر