جست‌وجوی استاد و پژوهشگر

Chao Liuمشاهده پروفایل

پژوهشگر

• Surgical Robotics
• Teleoperation
• Haptics
• +۲ مورد دیگر

Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.

Ian Greenhouseمشاهده پروفایل

استادیار

• Motor Control
• Action Stopping
• Neurophysiology
• +۳ مورد دیگر

Ian Greenhouse serves as an Assistant Professor in the Department of Human Physiology within the College of Arts and Sciences at the University of Oregon. He directs the Action Control Laboratory, where he investigates the neurophysiological mechanisms underlying human movement initiation and cancellation using multimodal approaches including electrophysiology, neuroimaging, and brain stimulation. Education: Undergraduate degree in Psychology from Tufts University Ph.D. from the University of California, San Diego Postdoctoral training at the University of California, Berkeley Research Focus: Dr. Greenhouse's work centers on action control neurophysiology , specifically examining motor inhibition processes during response stopping and preparation. His lab employs electromyography (EMG) , transcranial magnetic stimulation (TMS) , and magnetic resonance spectroscopy (MRS) to probe corticospinal excitability in healthy and clinical populations. Key investigations include neural computations for action preparation, biomarkers of stopping failure, and relationships between motor performance and brain chemistry (e.g., GABA). Publication Trends: Analysis of Dr. Greenhouse's 2022-2025 publications reveals intensified focus on subcomponents of response inhibition (pause vs. cancel processes) and neurochemical modulation of motor control. His work increasingly integrates menstrual cycle effects on GABA with action stopping metrics, while maintaining core investigations of corticospinal dynamics during unimanual/bimanual preparation. Recent studies show growing clinical applications in stroke rehabilitation. Scientific Awards: No awards were documented in the source materials. Advising and Research: As laboratory director, Dr. Greenhouse mentors students in the Action Control Laboratory's research program. Although specific grants aren't detailed, his high-output publication record spanning neuroimaging, electrophysiology, and clinical applications suggests sustained external funding for equipment-intensive neuroscience research. Laboratory Operations: The Action Control Laboratory (https://actioncontrollab.uoregon.edu) operates from Gerlinger Hall (Room 348), utilizing TMS-EMG integration, MRS, and behavioral paradigms to study action control. Current projects examine preparatory inhibition in stroke recovery, interhemispheric dynamics during movement preparation, and individual differences in stopping processes using the stop-signal task framework.

• Biomedical Engineering
• Neurorehabilitation Technology
• Biomedical Signal Processing
• +۱۲ مورد دیگر

Professor Dario Farina is Chair in Neurorehabilitation Engineering at the Department of Bioengineering, Faculty of Engineering, Imperial College London. He has previously served as Full Professor at Aalborg University, Denmark, and at the University Medical Center Göttingen, Germany, where he founded and directed the Institute of Neurorehabilitation Systems. His research spans biomedical signal processing, neural control of movement, and neurorehabilitation technology, with extensive contributions to electromyography, motor unit analysis, and neural interfaces. Chair in Neurorehabilitation Engineering, Imperial College London Former Full Professor, Aalborg University and University Medical Center Göttingen Founder and Director, Institute of Neurorehabilitation Systems Key Affiliations: Centre for Neurotechnology, Artificial Intelligence Network, Robotics Forum, Neuromechanics and Rehabilitation Technology His research focuses on biomedical signal processing , neural control of movement , and neurorehabilitation technology . He investigates how neural signals control muscles, develops methods to decode motor unit activity from EMG, and designs neural interfaces for prosthetics and rehabilitation. His work integrates computational modeling, signal processing, and clinical applications to improve bionic systems and neurorehabilitation outcomes. The recent publications (2024–2025) show a strong emphasis on high-density EMG , real-time motor unit decomposition , peripheral and cortical neural interfacing , closed-loop control systems , and AI-driven biosignal analysis . Key themes include decoding spinal and cortical signals, improving prosthetic control, understanding tremor mechanisms, and developing open-source tools for motor unit analysis. The work bridges neuroscience, engineering, and clinical practice. Scientific awards and honors include: Royal Society Wolfson Research Merit Award (2016) IEEE EMBS Early Career Achievement Award (2010) Nightingale Prize for best paper in MBEC (2007) Elected Fellow of EAMBES (2016) Elected Fellow of AIMBE (2012) Professor Farina has advised numerous researchers and students in neuroengineering and rehabilitation technology. He has led major research grants in neural interfaces and neurorehabilitation. He is Editor-in-Chief of the Journal of Electromyography and Kinesiology , an editor for IEEE Transactions on Biomedical Engineering and The Journal of Physiology , and has held editorial roles in multiple journals. He was President of ISEK (2012–2014) and is a Senior Member of IEEE. He leads a research group focused on neuromechanics, neural decoding, and bionic systems. The team develops tools like I-Spin live and MUedit for real-time motor unit identification and contributes to open-source platforms such as NeuroMotion . The lab collaborates internationally on projects involving spinal cord stimulation, prosthetic control, and wearable robotics, aiming to translate neural engineering advances into clinical rehabilitation.

Taskin Padirمشاهده پروفایل

استاد

• Experiential Robotics
• Human-Robot Teaming
• Embodied Artificial Intelligence
• +۴ مورد دیگر

Taskin Padir is a Professor in the Department of Electrical and Computer Engineering at Northeastern University and concurrently serves as an Amazon Scholar. He holds a PhD and MS from Purdue University and a BS from Middle East Technical University. His research focuses on experiential robotics, human-robot teaming, and embodied AI, with leadership roles in the Robotics and Intelligent Vehicles Research Laboratory (RIVeR Lab) and the Institute for Experiential Robotics. Padir has led projects for DARPA, NASA, and industry partners, advancing autonomous systems for extreme environments and human-robot collaboration. Education: PhD, Electrical and Computer Engineering, Purdue University (2004) MS, Electrical and Computer Engineering, Purdue University (1997) BS, Electrical and Electronic Engineering, Middle East Technical University (1993) Research Interests: Shared autonomy and human-in-the-loop robotics Embodied artificial intelligence Human-robot teaming in extreme environments (e.g., space, disaster zones) Collaborative robotics for industrial applications His work bridges robotics, AI, and real-world challenges, with recent projects addressing seafood processing automation, robotic navigation in unstructured terrains, and spectroscopy-based environmental monitoring. Awards: Recipient of the 2024 Faculty Research Team Award, 2023 Impact Award, and 2022 Amazon Scholar distinction. His research has been funded by NSF, DARPA, NASA, and industry collaborators like Amazon Robotics and Intel. Labs: Director of the RIVeR Lab and Institute for Experiential Robotics, fostering interdisciplinary research in autonomous systems and intelligent vehicles. Current projects include CRISP (Co-worker Robots for Seafood Processing) and PROSPECT (robotic spectroscopy tools).

• Signal Processing
• Communications
• Bioimaging
• +۵ مورد دیگر

Amir Asif is a Professor at the Lassonde School of Engineering, York University, and concurrently serves as Vice President, Research and Innovation. His academic leadership roles include Dean of the Gina Cody School of Engineering and Computer Science at Concordia University (2014-2020). He specializes in signal processing, communications, and their applications in healthcare, power grids, and distributed systems. Asif holds a PhD from Carnegie Mellon University and a Harvard certification in executive leadership. Education: PhD, Electrical and Computer Engineering, Carnegie Mellon University (1996) MS, Electrical and Computer Engineering, Carnegie Mellon University (1993) BSc, University of Engineering and Technology Lahore (1990) Harvard Certificate in Leadership for Senior Executives (2018) Research Interests: Asif’s work spans signal processing for medical imaging (e.g., ultrasound elastography), smart grid optimization, and cybersecurity in power systems. His recent publications address hydrogen energy systems, EMG-based gesture recognition, and resilient control frameworks against cyberattacks. Grants & Leadership: He leads NSERC-funded projects on federated learning and resilient algorithms. He chairs the Ontario Council of University Research and serves on TRIUMF Innovations and the Richmond Hill Board of Trade. His grants include SSHRC funding for equity initiatives and NSERC support for distributed signal processing. Teaching & Mentorship: Asif has supervised over a dozen graduate students and taught courses like Digital Communications and Statistical Signal Processing Theory. Notable advisees include Arash Mohammadi (PhD, 2014) and Nick Sajadi (PhD, 2017).

Rikky Mullerمشاهده پروفایل

دانشیار

• Neural Engineering
• Medical Devices
• Low-Power Electronics
• +۶ مورد دیگر

Rikky Muller is an Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, holding the S. Shankar Sastry Professorship in Emerging Technologies. She is Co-director of the Berkeley Wireless Research Center (BWRC), a Core Member of the Center for Neural Engineering and Prostheses (CNEP), and an Investigator at the Chan-Zuckerberg Biohub. Her research focuses on implantable/wearable medical devices, low-power wireless systems, and neurotechnology for neurological applications. Education: PhD (2013), UC Berkeley; BS and M.Eng. (2004), MIT, all in EECS. Prior roles include IC designer at Analog Devices and co-founder of Cortera Neurotechnologies (acquired). Research interests include neural interfaces, closed-loop neuromodulation, and biomedical microelectronics. Notable contributions include Neural Dust (ultrasonic implants), wireless EEG systems, and seizure prediction hardware. Awards: MIT TR35 Innovator, NAE Gilbreth Lectureship, NSF CAREER Award, IEEE SSCS New Frontier Award Grants: Bakar Fellows, Hellman Fellowship, NSF CAREER Labs: Muller Lab (UC Berkeley EECS), Chan-Zuckerberg Biohub collaborations

Omobolanle Ogunseijuمشاهده پروفایل

استادیار

• Workforce Development
• Construction Safety
• Artificial Intelligence
• +۷ مورد دیگر

Omobolanle Ogunseiju is an Assistant Professor in the School of Building Construction at Georgia Institute of Technology . She holds a Ph.D. in Environmental Design and Planning from the Department of Building Construction at Virginia Tech. Education: Ph.D. in Environmental Design and Planning, Virginia Tech Current Role: Assistant Professor, Georgia Tech School of Building Construction Her research focuses on integrating wearable robotics and Artificial Intelligence (via digital twin , cyber-physical systems , and data sensing ) to improve construction workforce safety, health, and well-being . She explores ethical implications of automation in construction, particularly in human-technological dynamics. Key research trends include: Advancing smart communities through robotics and AI Exoskeleton evaluation for ergonomic risk reduction Mixed reality environments for construction education Data analytics for cognitive and physical risk assessment Professional identity development in construction engineering students Industry-academia alignment for sensing technology integration Scientific awards: Outstanding Doctoral Candidate, Myers-Lawson School of Construction Outstanding Doctoral Student, College of Architecture and Urban Studies at Virginia Tech Teaching philosophy emphasizes experiential learning , engagement techniques , and hierarchical assessments . She developed the Construction Cost Management course at Georgia Tech and will lead Construction Technology courses. Previously, she taught Smart Construction , Building Systems Technology , and Wireless Sensing in Construction Management at Virginia Tech.

Heikki Handroosمشاهده پروفایل

استاد

• Mechatronics
• Robotics
• Machine Automation
• +۵ مورد دیگر

Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.

Adrian Chanمشاهده پروفایل

استاد

• Non-invasive sensor systems
• Biomedical signal processing
• Biomedical image processing
• +۳ مورد دیگر

Adrian Chan is a Professor at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. He holds the title of Director of the Research and Education in Accessibility, Design, and Innovation (READi) program. His expertise spans biomedical engineering, signal processing, and accessibility technologies. Education: Ph.D. in Electrical Engineering (University of New Brunswick), M.A.Sc. in Electrical Engineering (University of Toronto), B.A.Sc. in Computer Engineering (University of Waterloo). Research focuses on non-invasive sensors, biomedical signal/image processing, machine learning, and accessibility solutions. Notable projects include the Abilities Living Laboratory and collaborations with healthcare institutions like The Ottawa Hospital. His work addresses challenges in neonatal transport safety, placental imaging for maternal health, and wearable medical devices. Publications highlight advancements in AI-driven ECG analysis, histopathology segmentation, and clinical monitoring systems. Over 150 students have been mentored, with many securing prestigious awards. Awards include the 2024 CMBES Fellowship, 2023 Carleton Research Achievement Award, and 2012 3M Teaching Fellowship. Grants include NSERC CREATE programs and CFI funding for the Abilities Living Laboratory. Leadership roles include interim Assistant Vice-President (Academic), Associate Dean (Graduate Programs), and Shad Valley Program Director. Active in community initiatives like the READi training program and accessibility advocacy.

Panying Rongمشاهده پروفایل

استادیار

• Motor Speech Disorders
• Biomechanics
• Speech Assessment
• +۳ مورد دیگر

Panying Rong, Ph.D. is an Assistant Professor in the Department of Speech-Language-Hearing: Sciences & Disorders at the University of Kansas , within the College of Liberal Arts and Sciences. Her research focuses on the neuromechanical basis of motor speech disorders and the development of quantitative tools for speech assessment. Primary Affiliation: University of Kansas Department: Speech-Language-Hearing: Sciences & Disorders Academic Rank: Assistant Professor Email: prong@ku.edu Research Interests Dr. Rong’s work investigates the biomechanical and neurological mechanisms underlying speech impairments in neurodegenerative diseases like ALS and Parkinson’s. Key areas include: Mechanistic modeling of speech motor control Development of data-driven speech diagnostics Acoustic and kinematic analysis of bulbar disorders Compensatory articulatory strategies in speech pathologies Temporal structuring of speech signals Integration of multimodal assessments for neurological conditions Article Trends Her recent publications emphasize automated, multimodal frameworks for assessing bulbar ALS, neuromechanical biomarkers, and cultural-linguistic influences on speech outcomes. Techniques include EMA, EMG, kinematic modeling, and computational analysis of speech subsystems.

• Textile Engineering
• Smart Textiles
• Electronic Textiles
• +۷ مورد دیگر

André Catarino is an Assistant Professor in the Department of Textile Engineering at the University of Minho, Portugal, and Deputy Director of the 2C2T – Center for Textile Science and Technology since 2022. He is an integrated researcher at the center, with a strong focus on interdisciplinary research at the intersection of textiles, electronics, and materials science. Education: Postgraduate Specialization in Digital Business, University of Porto, Porto Business School (2020–2021) Ph.D. in Textile Engineering, University of Minho (2005) M.Sc. in Textile Engineering, University of Minho (1998) B.Sc. in Electrical and Computer Engineering, University of Porto (1992) Research Interests: André Catarino's research spans a wide range of domains, including smart and electronic textiles , wearable sensor systems , materials engineering , and functional textiles for health and sports . His recent work also delves into digital marketing and the application of artificial intelligence in textile systems. His expertise encompasses electronics, instrumentation, programming, fabric manufacturing, and textile characterization. He has led or participated in over 25 national and international research projects , including EU-funded initiatives like BE@T, GreenAuto, and Fashion Alive. His work has resulted in 4 Portuguese patents and 1 European patent , alongside numerous prototypes and technology transfers. Publications and Impact: With over 115 scientific publications , including journal articles, book chapters, and conference proceedings, his research output is both broad and impactful. His recent publications focus on smart vests for posture monitoring, textile-based EMG electrodes, and consumer behavior in fashion marketing. Student Supervision: He has supervised or co-supervised more than 45 master’s and doctoral dissertations , covering topics from wearable health monitoring systems to sustainable fashion design and digital marketing strategies. Labs and Teams: As Deputy Director of the 2C2T – Center for Textile Science and Technology , he leads a multidisciplinary team of researchers and engineers. The center is a hub for innovation in textile science, with a strong emphasis on integrating electronics, sustainability, and human-centered design into textile applications.

Lee M. Millerمشاهده پروفایل

استاد

• Neuroengineering
• Computational Neuroscience
• Auditory and Speech Processing
• +۴ مورد دیگر

Lee M. Miller is a Professor and Vice Chair of Academic Affairs in the Department of Neurobiology, Physiology and Behavior at the University of California, Davis, affiliated with the Center for Mind and Brain. His research focuses on neuroengineering, computational neuroscience, and neural mechanisms underlying attention, speech processing, and multisensory integration. Research interests include the development of neural prosthetics, decoding of neuromuscular signals for prosthetic control, and understanding how auditory and visual systems interact during speech perception and attentional processes. His work bridges clinical applications (e.g., cochlear implants) with fundamental neuroscience, leveraging tools like electrophysiological recordings, EEG/MEG, and advanced signal processing techniques. Recent publications highlight innovations in electromyographic speech neuroprosthetics, the topology of neuromuscular signals, and the neural basis of speech-in-noise processing. Miller’s studies emphasize translational potential, such as improving speech synthesis from brain signals and designing haptic feedback systems for motor coordination. His contributions have advanced understanding of neural mechanisms in sensory integration, auditory attention, and the impact of cognitive factors on perception. Miller maintains a lab dedicated to these interdisciplinary efforts, with a focus on both basic science and clinical applications.

Christoph Leitnerمشاهده پروفایل

پژوهشگر ارشد

• Convergent Technologies
• Ultrasonics
• Machine Learning
• +۳ مورد دیگر

Dr. Christoph Leitner is a Research Fellow at ETH Zurich's Integrated Systems Laboratory under Prof. Luca Benini, focusing on biomedical and IoT applications. His work integrates printed piezoelectric transducers and flexible electronics with energy-efficient systems. He holds a PhD in Biomedical Engineering from TU Graz (2022) and has collaborated with institutions like Sant'Anna School of Advanced Studies and KTH Stockholm. Notable achievements include the Josef Krainer Young Researcher Award and Motorik Scholarship. Leitner's research spans ultrasonics, machine learning, and wearable devices, with contributions to muscle-tendon dynamics and real-time biofeedback systems. Education: PhD in Biomedical Engineering, TU Graz (2022), Advisor: Prof. Christian Baumgartner Previous roles: University Assistant (2006–2011) and R&D Engineer at Virtual Vehicle GmbH Research Interests: Convergent technologies merging biomedical engineering and IoT Ultrasound-based monitoring for musculoskeletal systems Energy-efficient embedded systems for wearable applications Collaborations & Awards: Recipient of Josef Krainer Young Researcher Award (2023) and Motorik Scholarship (2018) Active collaborations with University of Zurich, Veterinary University of Vienna, and Queensland University of Technology Labs & Projects: Integrated Systems Laboratory at ETH Zurich Developed a patented ultrasound-transparent tattoo-based SEMG system with Prof. Francesco Greco

Ajita Rattaniمشاهده پروفایل

استادیار

• Biometrics
• Deepfake Detection
• Facial Recognition
• +۶ مورد دیگر

Ajita Rattani is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas, affiliated with Discovery Park. Her research focuses on biometrics, AI fairness, deepfake detection, and machine learning applications in health and security. She holds a Ph.D. in Computer Science and Engineering, with expertise in facial recognition, ocular biometrics, and multimodal authentication systems. Research Interests: Her work addresses algorithmic fairness in facial attribute classification, robustness of biometric systems against adversarial attacks, and developing lightweight models for on-device authentication. She also explores applications of machine learning in health informatics, such as BMI prediction from facial images and analyzing social determinants of health. Publications Trends: Recent work emphasizes bias mitigation in AI systems (e.g., gender/racial fairness), deepfake detection through fusion of audio-visual cues, and advancing ocular biometric recognition under challenging conditions. Notable contributions include frameworks like CodeIT for data-efficient deepfake detection and PatchBMI-Net for lightweight BMI prediction. Advising & Grants: Leads research projects funded by NSF SaTC grants (e.g., probing fairness in ocular biometrics). Active in organizing competitions like VISOB 2.0 for mobile ocular biometrics evaluation. Her lab develops practical solutions for real-world challenges in biometrics and AI ethics. Labs/Teams: Involved in interdisciplinary teams addressing transdisciplinary collaboration challenges and applying AI to disaster detection (wildfires, droughts) using satellite and sensor data fusion.

Shahram Shiraniمشاهده پروفایل

استاد

• Multimedia Communications
• Image/Video Processing
• Medical Image Processing
• +۵ مورد دیگر

Dr. Shahram Shirani is a Professor and holds the L.R. Wilson/Bell Canada Chair in Data Communications in the Department of Electrical & Computer Engineering at McMaster University. He also serves as Acting Chair of the department. His research focuses on multimedia communications, image/video processing, medical imaging, and hardware architectures. He teaches courses like Image Processing (COMPENG 4TN4) and 3D Image Processing and Computer Vision (ECE 736). Shirani earned his B.Sc. from Isfahan University of Technology (1989), M.Sc. from Amirkabir University of Technology (1994), and Ph.D. from the University of British Columbia (2000). His achievements include the Faculty of Engineering Leadership Fellowship (2014–15) and leadership roles in editorial boards for IEEE Transactions on Multimedia and Circuits and Systems for Video Technology. Research interests include video quality assessment, biomedical signal processing, and edge computing for traffic monitoring. His lab develops algorithms for multimedia representation, compression, and hardware implementation. Recent work includes AI-driven medical sound datasets, real-time noise removal in MRI, and efficient CNN pruning techniques. He advises over 15 graduate students and collaborates on projects like the HLS-CMDS dataset and cardiac segmentation reviews. His lab’s contributions span biomedical engineering, autonomous systems, and smart sensor technologies.