جستجوی استاد راهنمای دانشگاهی

Yayun Duمشاهده پروفایل

استادیار

• Bioelectronics
• Intelligent Systems
• Wearable and Implantable Sensors
• +۷ مورد دیگر

Dr. Yayun Du is an Assistant Professor in the Department of Electrical and Computer Engineering at Vanderbilt University School of Engineering. She holds a Ph.D. in Robotics and System Control (Minor: Solid Mechanics) from UCLA (2022) and was a postdoctoral scholar at Northwestern University's Rogers Group through 2024. Current faculty at Vanderbilt University Ph.D. from University of California, Los Angeles Postdoctoral experience at Northwestern University Her research integrates bioelectronics and robotics through three core directions: 1) Developing multimodal wearable/implantable sensors for health monitoring, 2) Creating human-in-the-loop interaction systems using brain-computer interfaces, and 3) Applying machine learning to medical environment robotics. She has deployed four sensor types across seven hospitals globally, serving users from neonates to elderly patients. Dr. Du's recent publications focus on wireless bioelectronic devices ( PNAS ), sustainable sensor materials ( ACS Sustainable Chemistry & Engineering ), and agricultural robotics ( ICRA , IROS ). She serves as Associate Editor for ICRA 2025 and has received two Best Paper Award final nominations at IROS 2021. Finalist - Best Paper Award in Agri-Robotics (IROS 2021) Finalist - Best Paper Award in Robot Mechanisms and Design (IROS 2021) As head of the Du Group, she leads interdisciplinary research with applications in both healthcare and agricultural contexts, collaborating with Vanderbilt Institute for Surgery and Engineering (VISE) and clinical partners. Her work emphasizes deployable systems that transition from academic research to real-world implementation in medical and industrial environments.

Howie Chosetمشاهده پروفایل

استاد

• Robotics
• Medical Robotics
• Snake Robots
• +۱۱ مورد دیگر

Howie Choset is a Professor of Robotics at the Robotics Institute, Carnegie Mellon University. He directs the Undergraduate Robotics Minor and leads the Biorobotics Laboratory, where his research focuses on snake robots, motion planning, and medical robotics. He is also affiliated with the Manufacturing Futures Institute. Ph.D., Mechanical Engineering, California Institute of Technology (1996) M.S., Mechanical Engineering, California Institute of Technology (1995) B.S.E., Computer Science and Engineering, University of Pennsylvania (1990) B.S., Economics, The Wharton School of Business (1990) Choset's research centers on robotics for confined and complex environments, particularly through the development of snake robots. His work integrates mechanism design, path and motion planning, and estimation to enable applications in surgery, manufacturing, infrastructure inspection, and search and rescue. He is a pioneer in medical robotics and has co-founded Medrobotics to commercialize minimally invasive surgical robots. His recent publications highlight a strong focus on ergodic exploration, multi-agent systems, motion planning under uncertainty, and medical robotics. Themes include optimizing robot trajectories for information gathering, solving complex path planning problems with dynamic obstacles, and advancing autonomous systems for disaster response and space exploration (e.g., the EELS robot for Enceladus). MIT Technology Review Top 100 Innovators under 35 (2002) Best Paper Award, RIA (1999) Best Paper Award, ICRA (2003) Best Paper, IEEE Bio Rob (2006) Best Video, ICRA (2011) Nominations for best papers at ICRA, IROS, and CLAWAR Choset has advised numerous students, many of whom have won top awards. His lab has received significant funding for robotics research, including projects in surgical robotics, additive manufacturing, and autonomous exploration. He is the lead author of the textbook Principles of Robot Motion and is actively involved in educational innovation through custom robotics labs. He leads the Biorobotics Laboratory at CMU, which develops advanced robotic systems like snake robots and the EELS (Exobiology Extant Life Surveyor) robot for NASA missions. The lab collaborates with industry and government agencies on applications ranging from surgery to space exploration.

Guy Wallisمشاهده پروفایل

استاد

• Visual neuroscience
• Object recognition
• Visuomotor control
• +۵ مورد دیگر

Professor Guy Wallis is a Professor and Director of Research at the School of Human Movement and Nutrition Sciences, Faculty of Health, Medicine and Behavioural Sciences at the University of Queensland. He is also an Affiliate of the Centre for Sensorimotor Performance. His work bridges visual neuroscience, computational modeling, and applied human factors research, with significant contributions to understanding visual recognition and visuomotor behavior. Education: Bachelor (Honours) of Engineering in Electrical and Electronic Engineering from Imperial College London PhD in Visual Neuroscience from University of Oxford, UK Prof. Wallis's research program combines computational modeling with behavioral studies, many conducted in computer-controlled virtual environments. His work spans visual neuroscience, object recognition, visuomotor control, and simulator-based training. He has made significant theoretical contributions to understanding how visual recognition is achieved in biological systems and how everyday visuomotor tasks are regulated, challenging existing paradigms and offering new insights. His recent publications reveal a strong focus on virtual reality applications, visual-motor integration challenges, and cross-species cognitive studies. There's a clear trend toward investigating how virtual environments can be optimized for training and assessment, with particular attention to visual perception limitations and how humans adapt to these environments across diverse contexts from surgical training to aviation. Scientific Awards and Recognitions: Elected Fellow of the Queensland Academy of Arts and Sciences (2022) ARC Medical Research Advisory Group (2022-2024) ARC College of Experts (2019-2021) CSIRO CSS Human Research Ethics Committee member (2020-2022) UQ Health and Behavioural Sciences Faculty, HDR Supervision Award (2018) ARC Future Fellowship (2011-2014) ARC QEII Fellowship (2003-2007) UQ Postdoctoral Fellowship (2001-2003) Prof. Wallis has successfully secured funding from major organizations including the Australian Research Council, the Human Frontier Science Program, and the Wellcome Trust. His industry partnerships span diverse sectors such as construction training, mining, healthcare, and aerospace. His research has led to the development of novel training programs for health professionals, impacted the design of man-machine interfaces for mining equipment, and informed the design parameters for pilot training systems. As Director of Research, he oversees the research direction of the School of Human Movement and Nutrition Sciences, fostering interdisciplinary collaborations and supporting early-career researchers through his leadership in the Centre for Sensorimotor Performance.

• Robotics
• Mechatronics
• Humanoid Robots
• +۴ مورد دیگر

Atsuo Takanishi is a distinguished Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, with appointments in both the Department of Bioscience and Biotechnology and the Department of Modern Mechanical Engineering. With over 700 publications, 10,399 citations, and an h-index of 47, Professor Takanishi has established himself as a leading figure in robotics research. His work spans multiple institutions, including visiting positions at Showa University School of Dentistry and KDDI Research, Inc. Professor Takanishi received his Doctor of Engineering degree from Waseda University in 1985, following his undergraduate studies in the Faculty of Science and Engineering at the same institution, which he completed in 1980. His academic journey began with positions as an Assistant at Waseda University (1985-1988), Lecturer (1988-1990), and Associate Professor (1990-1997) before achieving his current Professor status. Professor Takanishi's research interests center around robotics and intelligent systems, with particular expertise in humanoid robotics, surgical dentistry applications, and biomechatronics. His work demonstrates a unique integration of mechanical engineering principles with biological systems, resulting in innovative robotic platforms that mimic human capabilities. Notably, his laboratory has developed the Waseda Anthropomorphic Saxophonist Robot series and various medical training simulators that have significantly advanced the field of human-robot interaction. His research in experimental psychology complements his robotics work, particularly in human-robot interaction studies. Analysis of Professor Takanishi's recent publications reveals a strong focus on practical applications of robotics technology, particularly in assistive devices for elderly mobility, medical training simulators, and agricultural robotics for Synecoculture environments. His work consistently bridges theoretical robotics with real-world implementation, with recent papers emphasizing reinforcement learning approaches, haptic feedback systems, and computer vision techniques for complex environments. The Waseda Anthropomorphic Saxophonist Robot series represents a culmination of decades of research in humanoid robotics and musical expression. IEEE Fellow (2020-present) Robotics Society of Japan Fellow (2012-present) Japan Society of Mechanical Engineers Fellow (2007-present) Multiple Best Paper Awards from IEEE conferences (ICRA, IROS, ROMANSY) BusinessWeek Asia's Stars Bloomberg (2001) IFToMM Award of Merit (2010) Professor Takanishi has maintained extensive collaborations with research institutions worldwide, particularly with Italian institutions through the Italy-Japan Workshop series. His laboratory has secured substantial funding from Japanese government agencies including the Japan Science and Technology Agency, with particular emphasis on projects bridging robotics with medical applications and human-centered technologies. His international recognition is evidenced by his numerous visiting professorships and collaborative projects across continents. Professor Takanishi leads the Takanishi Laboratory at Waseda University, which maintains specialized facilities for humanoid robotics development, medical robotics research, and human-robot interaction studies. The laboratory has developed several notable robotic platforms including the WABIAN series of bipedal humanoid robots, the WASEDA FLUTIST ROBOT, and various medical training simulators used in clinical education settings. His work on the WASEDA SAXOPHONIST ROBOT represents a unique fusion of musical artistry and robotics engineering.

• Medical Imaging
• Computed Tomography
• Inverse Problems
• +۳ مورد دیگر

Dr. Owen Dillon is a Research Fellow in the Discipline of Medical Imaging Sciences at the University of Sydney's Faculty of Medicine and Health. He holds affiliations with the ACRF Image X Institute and the Dodd-Walls Centre for Photonic and Quantum Technologies. His work focuses on advanced imaging techniques for medical applications, particularly computed tomography (CT) and motion compensation in radiation therapy. He completed his PhD in Mathematics at the University of Auckland, specializing in probabilistic compression algorithms for inverse problems. Education: B.Sc. Physics & Applied Mathematics (2013, University of Auckland), First Class Honours in Mathematics (2015), PhD Mathematics (2018). Research interests include inverse problems, Bayesian statistics, CT image reconstruction, and real-time imaging systems. Current projects involve optimizing CT acquisition geometries, motion-compensated 4D imaging, and anatomical motion estimation. His contributions have led to clinical trials reducing radiation dose and scan times. He advises two PhD students and collaborates on grants like the Quantum CT project. Grants: 'Quantum CT for Cancer Diagnosis' (2024), 'Functional Imaging in Lung Cancer' (2024). His work bridges mathematical theory with clinical applications in oncology and interventional radiology.

Frank Rudziczمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Healthcare
• +۱۲ مورد دیگر

Dr. Frank Rudzicz is an Associate Professor in the Faculty of Computer Science at Dalhousie University. His research lies at the intersection of artificial intelligence, natural language processing, and healthcare, with a focus on developing machine learning systems that improve clinical decision-making, patient outcomes, and accessibility in medicine. He holds a BSc from Concordia University (2004), an MEng from McGill University (2006), and a PhD from the University of Toronto (2011). His research interests include Natural Language Processing, Machine Learning, Healthcare, Speech Technologies, Explainable AI, and Fairness in ML. Dr. Rudzicz's recent publications span a wide range of topics, including Alzheimer's detection through speech analysis, surgical outcome prediction, mental health monitoring, privacy in AI, and the application of large language models in clinical settings. His work consistently emphasizes ethical AI, patient privacy, and real-world clinical integration. He has received several awards, including a Best Paper award at EMNLP 2020, a Best Student Paper award at ICASSP 2021, and the ISCA Best Student Paper award in 2013. His research has been published in top-tier journals such as Nature Scientific Reports , JAMA Network Open , IEEE Access , and Frontiers in Human Neuroscience , as well as leading conferences including NeurIPS, ACL, ICML, and Interspeech. Dr. Rudzicz supervises a dynamic research group working on AI for health, with active projects in voice-based diagnostics, ambient clinical documentation, explainable AI for surgery, and wearable-based monitoring for chronic diseases. He collaborates widely across disciplines, including with clinicians, neuroscientists, ethicists, and public health experts. He is also involved in major initiatives such as the Genetics Navigator study and Bridge2AI-Voice, aiming to build ethically sourced, diverse biomedical datasets. His lab actively explores the societal implications of AI in healthcare, including fairness, trust, and resistance to malicious fine-tuning.

Heather Culbertsonمشاهده پروفایل

استادیار

• Haptics
• Robotics
• Virtual Reality
• +۳ مورد دیگر

Dr. Heather Culbertson is an Assistant Professor in the Department of Computer Science at the University of Southern California, leading the HaRVI (Haptics Robotics and Virtual Interaction) Laboratory. Her research focuses on designing haptic hardware and algorithms to create intuitive human-robot interactions through touch, emphasizing realism in virtual environments and social connectedness. Key areas include mediated touch, wearable haptic systems, and multisensory integration in VR/AR applications. The lab's work spans robotics, human perception modeling, and cross-disciplinary solutions for healthcare and immersive technologies. Research interests revolve around tactile feedback systems, social robotics, and the psychological impact of haptic interfaces. Recent work explores real-time haptic texture rendering, affective communication via touch, and motion platforms for VR. Culbertson's projects often integrate human factors early in design to ensure usability and immersion. Publications highlight advancements in haptics coding standards, drone-human interaction, and emotion regulation systems. Her contributions bridge engineering and cognitive sciences, addressing challenges in wearable tech, surgical training simulations, and assistive robotics. The HaRVI Lab collaborates across disciplines to advance tactile interfaces for virtual reality, social robotics, and medical applications.

Kevin C. Zhouمشاهده پروفایل

استادیار

• Computational Imaging
• Biomedical Engineering
• Optical Systems
• +۳ مورد دیگر

Kevin C. Zhou is an Assistant Professor in the Department of Biomedical Engineering at the University of Michigan. His research focuses on developing high-performance computational optical imaging systems with unprecedented spatiotemporal throughput, integrating advanced optical instrumentation with machine learning-driven algorithms to analyze big data in biology and medicine. His lab specializes in creating imaging systems capable of capturing high-resolution, high-speed, and high-dimensional datasets. Dr. Zhou holds a Ph.D. in Biomedical Engineering from Duke University (NSF GRFP Fellow) and a B.S. in Biomedical Engineering from Yale University (Barry Goldwater Scholar). Prior to joining U-M, he was a Schmidt Science Fellow and postdoctoral researcher at UC Berkeley. Key research areas include: High-throughput microscopy (gigapixel-scale systems) 3D tomographic imaging Light field and Fourier-based imaging modalities Machine learning for image reconstruction and analysis Biomedical applications in cellular/molecular imaging His recent work has advanced technologies like multi-camera array microscopes (MCAM/MCAS) and Fourier light field mesoscopes, achieving video-rate 3D imaging of freely moving organisms. These innovations enable applications in digital cytopathology, behavioral tracking, and high-content biological studies. Notable awards include the NSF Graduate Research Fellowship and Barry Goldwater Scholarship. His research has been featured in top journals and conferences with a focus on advancing optical imaging hardware and computational pipelines.

Levent Burak Karaمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Computational Design
• +۱۲ مورد دیگر

Levent Burak Kara is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Robotics Institute. He is a leading researcher in AI-driven computational design, additive manufacturing, and intelligent engineering systems, leading the Visual Design and Engineering Lab (VDEL) at CMU. Education: B.S., Mechanical Engineering, Middle East Technical University (1998) M.S., Mechanical Engineering, Carnegie Mellon University (2000) Ph.D., Mechanical Engineering, Carnegie Mellon University (2005) His research focuses on integrating machine learning, optimization, and geometric modeling to revolutionize engineering design and manufacturing. Key areas include topology optimization, CAD intelligence, digital twins, generative design, bioengineering, and electronic design automation. His work enables automation of traditionally labor-intensive design processes using deep learning and reinforcement learning. His recent publications reveal a strong trend toward physics-informed surrogate modeling, real-time simulation, manufacturability prediction, and AI-driven automation in mechanical, biomedical, and electronic systems. These works frequently appear in top journals such as Journal of Mechanical Design and Journal of Applied Mechanics , and at premier conferences like NeurIPS and DAC. Scientific Awards: National Science Foundation CAREER Award ASME Design Automation Society Young Investigator Award Google AI for Social Good Impact Scholar Kara advises several Ph.D. students and has secured significant funding from federal agencies such as the NSF and the U.S. Army Research Laboratory, as well as collaborations with industrial leaders including Cadence Design Systems and NVIDIA. His research is also supported by CMU’s NextManufacturing Center and the Critical Technology Initiative. He is actively involved in developing intelligent design systems that leverage AI to automate product design, optimize manufacturing processes, and improve medical diagnostics, particularly in oral cancer screening and organ preservation. His lab, VDEL, is a hub for innovation in AI-enabled engineering.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +۵ مورد دیگر

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

Massimo Mischiمشاهده پروفایل

استاد

• Biomedical Signal Processing
• Diagnostic Imaging
• Ultrasound Technology
• +۴ مورد دیگر

Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.

• Medical Imaging
• Radiation Detectors
• Biomedical Engineering
• +۳ مورد دیگر

Mats Danielsson is a Professor at KTH Royal Institute of Technology, leading the Medical Imaging research group within the Department of Particle Astrophysics and Medical Imaging. He has coordinated major projects like the ERC Advanced Grant for the Si3 project (starting 2024) and the EIC Pathfinder's 1MICRON project (starting 2025). His work focuses on advancing photon-counting detectors, X-ray technologies, and medical imaging systems. Notable recognitions include the 2024 KTH Innovation Award and the 2022 Hans Wigzell Science Prize. Danielsson has co-founded companies such as Sectra Mamea AB and C-RAD AB, and holds 135 patents with over 150 scientific publications. Education: MSc (1990) and PhD (1996) from KTH, followed by postdoctoral research at Lawrence Berkeley National Lab (1996–1998). He joined KTH in 1999, where he has held his current professorship since then. His research spans medical imaging, detector innovation, and radiation physics applications in healthcare. Research Interests: Development of high-resolution CT detectors, photon-counting technologies, compact X-ray sources, and AI-driven image processing. His recent work emphasizes minimizing radiation exposure while enhancing diagnostic precision through novel detector designs and machine learning algorithms. Key Projects: ERC Si3 project (3D detector for nuclear medicine), EIC 1MICRON (micrometer-scale imaging), and MedTechLabs collaboration with Karolinska Institutet. He has pioneered innovations such as MicroDose mammography and advanced photon-counting spectral CT systems. Awards: KTH Innovation Award (2024), Hans Wigzell Prize (2022), IVA membership (2017), Polhem finalist (2014), and INGVAR Award (2004). Advising & Grants: Over 150 scientific publications, 135 patents, and leadership in multi-institutional projects. Teaches courses on medical imaging and modern physics at KTH. Labs/Teams: Director of the Medical Imaging Group at KTH, co-founder of MedTechLabs, and collaborator across academia and industry in medical imaging innovation.

• Medical Statistics
• Biostatistics
• Epidemiology
• +۳ مورد دیگر

Ruth Keogh is a Professor of Biostatistics and Epidemiology at the London School of Hygiene & Tropical Medicine (LSHTM), affiliated with the Medical Statistics Department within the Faculty of Epidemiology and Population Health. She is Co-Director of the Centre for Data and Statistical Science for Health (DASH) and serves as Departmental Research Degrees Coordinator. Her academic career has spanned roles from Lecturer (2012–2015) to Associate Professor (2015–2019) before attaining her current rank in 2019. Keogh holds advanced degrees including a DPhil in Medical Statistics/Epidemiology (University of Oxford, 2007), MSc in Applied Statistics (Oxford, 2003), and BSc in Mathematics and Statistics (University of Edinburgh, 2002). Her research focuses on causal inference, clinical trial emulation using real-world data, and applications in cystic fibrosis, infectious diseases, and public health. She leads projects on lung function trajectories, vaccine efficacy, and healthcare policy analysis. Her work integrates biostatistical methods with epidemiological studies, emphasizing rigorous analysis of observational data to inform clinical decisions. Notable areas include evaluating antibiotic treatments for cystic fibrosis patients, assessing diagnostic test accuracy for dengue and leptospirosis, and modeling vaccine effectiveness during the COVID-19 pandemic. She teaches courses in survival analysis, electronic health records, and health data science at LSHTM. Keogh has held leadership roles in the International Biometric Society and the STRATOS Initiative, and she has delivered keynote addresses at international conferences on trial emulation and biostatistical methods. Her contributions bridge methodological innovation and practical health challenges, with over 190 publications and active engagement in global health research networks.

Septimiu E. Salcudeanمشاهده پروفایل

استاد

• Medical Robotics
• Medical Imaging
• Biomedical Engineering
• +۴ مورد دیگر

Septimiu E. Salcudean is a Professor at the University of British Columbia's Department of Electrical and Computer Engineering, holding the C.A. Laszlo Chair in Biomedical Engineering and a Canada Research Chair. His research focuses on medical robotics, image guidance systems, and ultrasound elastography. He has contributed to advancements in haptic interfaces, teleoperation, and needle insertion modeling. Education: B.Eng and M.Eng from McGill University (1979-1981), Ph.D. from UC Berkeley (1986). He has held positions at IBM T.J. Watson Research Center and was a Killam Research Fellow at ONERA in France. His work spans robotics, biomedical engineering, and surgical systems. Research interests include medical robotics, real-time imaging, and surgical navigation. Notable projects involve ultrasound-guided surgery, vibro-elastography for tissue characterization, and haptic feedback systems. His lab, the Robotics and Control Laboratory (RCL), develops technologies like the da Vinci surgical system integration with ultrasound imaging. Awards include the NSERC Synergy Award, IEEE Fellowship, and UBC Killam Research Prize. He has advised over 30 graduate students and published extensively in robotics and biomedical journals.

Cooper Harshbargerمشاهده پروفایل

مدرس

• Biomechanics
• Medical Technology
• Acoustofluidics
• +۳ مورد دیگر

Dr. Cooper Harshbarger is a Lecturer at the Department of Health Sciences and Technology at ETH Zurich , Switzerland. His research bridges biomechanics and acoustofluidics, focusing on spinal surgery and microscale cell manipulation technologies. Email: cooper.harshbarger@hest.ethz.ch Research Interests : Dr. Harshbarger specializes in biomechanical analysis of spinal structures and acoustofluidic device development . His work explores: Biomechanics of the lumbar spine and osteoligamentous complexes Acoustically-driven microfluidic systems for medical diagnostics Cell focusing/trapping technologies using sharp-edge acoustofluidics Scientific Contributions : Recent publications highlight his dual expertise in spinal fusion biomechanics and microscale fluid control , with applications in cancer diagnostics and cell manipulation. Key technologies include BAW-based systems and programmable acoustofluidic chips.