جست‌وجوی استاد و پژوهشگر

José M. Azorínمشاهده پروفایل

استاد

• Brain-Machine Interfaces
• Neuro-robotics
• Rehabilitation Robotics
• +۵ مورد دیگر

José M. Azorín is a Full Professor and Director of the Brain-Machine Interface Systems Lab at Miguel Hernández University of Elche (Spain) . He holds a Ph.D. in Robotics (2003) and a M.Sc. in Computer Science (1997). His research focuses on Brain-Machine Interfaces (BMIs), Neuro-robotics, and Rehabilitation Robotics, with over 200 publications and 3 patents. He leads the NSF IUCRC BRAIN UMH Site and serves as a Distinguished Lecturer for the IEEE Systems Council and Core Team member of the IEEE Brain Initiative. Education: PhD in Robotics: Summa Cum Laude (2003), Miguel Hernández University MSc in Computer Science (1997), University of Alicante Research Interests: Azorín pioneers BMI-driven robotic exoskeletons for mobility-impaired individuals. His work integrates EEG-based control systems, neurorehabilitation protocols, and bioinspired robotics. Key areas include lower/upper limb exoskeleton control, sensory-motor decoding, and EU-funded initiatives like the BioMot project. He emphasizes cross-border collaboration through networks like Reasiste and Iberada. Projects & Funding: Over 20 projects since 2000, including Horizon 2020-funded DECODED/REKINE (2021–2022) and Spanish Ministry grants like WALK (2019–2021). His work addresses clinical needs via wearable robots, multimodal interfaces, and low-cost solutions for neurorehabilitation. Awards & Leadership: Best Thesis Award (2003) IEEE Distinguished Lecturer (2013–) Core Team IEEE Brain Initiative Organized major conferences like ICNR and WeRob Grants & Labs: Coordinates the Brain-Machine Interface Lab and secured €10M+ in EU/Spanish funding. His team develops open-source BMI frameworks and collaborates with Imperial College London and University of Houston.

Andrea Bandiniمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer Vision
• Biomedical Signal Processing
• +۶ مورد دیگر

Andrea Bandini is an Assistant Professor at the Interdisciplinary Research Center 'Health Science' at Scuola Superiore Sant'Anna (Pisa, Italy) and an Adjunct Scientist at KITE - Toronto Rehabilitation Institute (Canada). He holds a PhD in Bioengineering (2016) from the University of Bologna and degrees in Biomedical Engineering (2012) and Electronic Engineering (2010) from the University of Florence. Affiliations: Affiliate Researcher at The Biorobotics Institute (Sant'Anna School), Adjunct Professor at the University of Florence (2021–2024). Research Focus: AI-driven tools for remote assessment of neurological disorders, with expertise in computer vision, biomedical signal processing, and rehabilitation engineering. Key Areas: Speech/swallowing analysis, upper limb function assessment, stroke recovery prediction, and telemedicine applications. His work bridges artificial intelligence and clinical practice, developing algorithms for speech impairment detection (e.g., ALS, Parkinson’s), swallowing assessment, and wearable sensors for home-based monitoring. Collaborations include the Steele Swallowing Lab at KITE. Education: PhD in Bioengineering, University of Bologna (2016) MSc in Biomedical Engineering, University of Florence (2012) BSc in Electronic Engineering, University of Florence (2010) Awards: Multiple honors including the 2021 Best Abstract Award (National Spinal Cord Injury Conference), 2020 People’s Choice Award (KITE 3MT), and postdoctoral awards in aging technology (AGE-WELL). Research emphasizes multi-modal approaches, integrating EEG, EMG, and video data to optimize neurological disorder interventions. His lab develops tools for remote clinical assessment, enhancing accessibility to healthcare for neurologically impaired populations.

Miguel Vargas Martinمشاهده پروفایل

استاد

• Computer Security
• Cybersecurity
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Miguel Vargas Martin is a Professor of Computer Science at Ontario Tech University's Faculty of Business and Information Technology. He holds a PhD from Carleton University, a Master's from CINVESTAV del IPN, and a Bachelor's from Universidad Autónoma de Aguascalientes. His research focuses on cybersecurity, authentication systems, machine learning, and human factors in security. Dr. Martin teaches graduate courses such as Cryptography and Secure Communications, and undergraduate courses including Machine Learning and Cryptography, Malware, and Network Security. Education: PhD in Computer Science, Carleton University (2003) Master of Applied Science in Electrical Engineering, CINVESTAV del IPN (1998) Bachelor of Science in Computer Science, Universidad Autónoma de Aguascalientes (1996) Research Interests: Dr. Martin's work addresses cutting-edge topics in computer security and artificial intelligence. His recent studies include improving password security through honeyword generation using machine learning, developing differential privacy visualizations for public understanding, and creating emotion recognition models for companion robots. His cybersecurity frameworks target edge computing and IoT environments, emphasizing practical defenses against modern threats. Key Contributions: Over 25 peer-reviewed articles since 2012 span topics from brain-computer interfaces for password memorability analysis to fusion-based optimization algorithms. His work bridges theoretical advancements with real-world applications in healthcare, transportation systems, and industrial IoT security.

Chuan Luمشاهده پروفایل

مدرس ارشد

• Bioinformatics
• Medical Imaging
• Artificial Intelligence
• +۴ مورد دیگر

Chuan Lu is a Senior Lecturer in Bioinformatics at the Department of Computer Science, Aberystwyth University. He holds a BEng from Tianjin University (China), an MSc from KU Leuven (Belgium), and a PhD from KU Leuven. His research focuses on applying artificial intelligence and computational methods to address challenges in medical imaging, reproductive health, and plant science. He has led multiple projects funded by organizations such as the Engineering and Physical Sciences Research Council and the Welsh European Funding Office. Research interests include AI-driven phenotyping in plants (e.g., Arabidopsis), diagnostic modeling for endometriosis and ectopic pregnancies, and healthcare data integration through knowledge graphs. His work bridges disciplines like bioinformatics, computer science, and medicine, with contributions to clinical decision support systems and open-source biobank management frameworks. Recent publications highlight advancements in EEG signal analysis, AI applications in agricultural phenotyping, and ultrasound-based predictive models for surgical planning. Projects include the 'Miscanthus AI' initiative for sustainable plant breeding and the 'LImBuS' open-source biobank system.

Irina Rishمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Neuroscience
• +۹ مورد دیگر

Irina Rish is a Full Professor at the University of Montreal's Department of Computer Science and Operations Research and a core member of Mila – Quebec AI Institute. She holds the Canada Excellence Research Chair in Autonomous Artificial Intelligence and a CIFAR AI Chair. Her research focuses on machine learning, neural data analysis, and neuroscience-inspired AI. She leads the Autonomous AI Lab and has contributed to projects like the Covi contact-tracing app during the pandemic. Education: MSc and PhD in AI from University of California, Irvine; MSc in Applied Mathematics from Moscow Gubkin Institute. Awards include multiple IBM accolades and prestigious editorial roles (e.g., IEEE TPAMI Associate Editor). Research Interests: Continual Learning, Deep Learning, Sparse Modeling, Reinforcement Learning, Neuroimaging Analysis Affiliations: MILA, CIRCA (Brain and Learning Research Center), Canada Excellence Research Chair Publications span over 120 papers, 64 patents, and books on sparse modeling. Collaborates with industry leaders like IBM, Microsoft, and Samsung. Grants: Leads U.S. Department of Energy’s INCITE project on scalable foundation models. Advises over 30 students in AI and neuroscience-related fields. Labs/Teams: Directs the Autonomous AI Lab at Mila, co-founded Nolano.ai as CSO.

Trung P. Nguyenمشاهده پروفایل

استادیار

• Neurodegenerative diseases
• Alzheimer's disease
• Dementia with Lewy bodies
• +۷ مورد دیگر

Trung P. Nguyen, M.D., Ph.D., is a faculty member in the Department of Neurology at UT Southwestern Medical Center since 2016. His clinical focus includes disorders of cognition and dementias such as Alzheimer’s disease and dementia with Lewy bodies, where he conducts observational and interventional clinical trials. He has received research funding from the Texas Alzheimer’s Research and Care Consortium and the National Institute on Aging. Education: M.D. and Ph.D. in neuroscience from the University of Texas Medical Branch at Galveston Residency: Neurology, Emory University Fellowship: Behavioral neurology and neuropsychiatry, UT Southwestern Medical Center Dr. Nguyen’s research spans neurodegenerative diseases, with a focus on Alzheimer’s disease and dementia with Lewy bodies. His work integrates neuroimaging (e.g., MRI, PET), biomarker discovery (e.g., CSF proteins, plasma phosphorylated-tau), and genetic studies (e.g., polygenic risk scores). He explores the impact of traumatic brain injury on dementia onset and utilizes computational modeling to stage brain aging and pathology. Dr. Nguyen contributes to interdisciplinary research, including collaborations on socially assistive robotics for cognitive decline and population-based neuroimaging studies via the UK Biobank. His publications highlight predictive models for dementia conversion, biomarker validation, and genetic etiology, reflecting a blend of clinical, computational, and translational approaches. He is part of the Cognitive and Behavioral Neurology Section at UT Southwestern, engaging in research that bridges clinical practice, neuroimaging, and molecular biology to address neurodegenerative disease mechanisms and interventions.

FRANCESCO FERRACUTIمشاهده پروفایل

پژوهشگر

• Control Systems
• Robotics
• Brain-Computer Interfaces
• +۶ مورد دیگر

Prof. Francesco Ferracuti is a Researcher at the Department of Information Engineering (Università Politecnica delle Marche, Ancona, Italy). His work focuses on advanced control systems, robotics, brain-computer interfaces, and energy management. Key research themes include fault-tolerant control, autonomous navigation, and human-machine interaction through wearable sensors. Research interests span across: Control Engineering (MIMO systems, PID control, Model Predictive Control) Robotics (mobile robotics, UAVs, smart wheelchairs) Neuroengineering (EEG-based BCI, cognitive workload assessment) Energy Systems (renewable integration, home energy management) Data-Driven Methods (machine learning, system identification) Publications emphasize innovative solutions like EEG-driven obstacle avoidance and thermal stress monitoring for smart wheelchairs, demonstrating interdisciplinary approaches combining robotics with biometrics. His work on fault detection in multirotors and energy optimization algorithms highlights practical applications in both industrial and healthcare domains. Current projects include the E-MOTIVE initiative for mobility solutions via affective computing and BCI. His lab develops cutting-edge algorithms for cyber-physical systems security and predictive maintenance in industrial equipment.

Alaa A. Ahmedمشاهده پروفایل

استاد

• Biomechanics
• Neural Control of Movement
• Motor Learning
• +۴ مورد دیگر

Alaa A. Ahmed is a Professor in the Department of Electrical, Computer, and Energy Engineering at the University of Colorado Boulder, affiliated with the College of Engineering and Applied Science. Her research focuses on the neuroeconomic foundations of sensorimotor decision-making, integrating neuroscience, economics, psychology, and engineering. She holds lab spaces in ECES 142 (office) and ECSL 1B19 (laboratory). Education details not explicitly listed in text Research interests emphasize understanding brain mechanisms behind movement control through interdisciplinary approaches. Notable achievements include receiving prestigious NSF and DARPA awards recognizing her as a rising research star. Her work has been featured in Forbes, Wired, Time, and PBS. No article details provided in text for summary analysis Scientific Awards: - NSF CAREER Award - DARPA Young Faculty Award Advising and grants information not explicitly detailed in provided text. Laboratory website and curriculum vitae available through provided links. Labs/teams: Maintains active research laboratory in ECSL 1B19 focusing on biomechanical and neuroeconomic studies.

Claire Wyartمشاهده پروفایل

دانشیار

• Motor Control
• Neuroscience
• Interoception
• +۳ مورد دیگر

Claire Wyart is an INSERM Director of Research (equivalent to Associate Professor) and Team Leader at the Institut du Cerveau – Paris Brain Institute (ICM). She holds affiliations with INSERM and Sorbonne University. Her research focuses on understanding how sensory inputs are integrated in the spinal cord to control locomotion and posture, leveraging zebrafish models for cutting-edge optical and genetic techniques. Key achievements include discovering spinal CSF-contacting neurons as mechanoreceptors and their role in body axis formation and immune responses. Education & Career: PhD in Biophysics from University of Strasbourg (2003), postdoc at UC Berkeley (2005–2010), leading her own team since 2011. Recognized with awards including the Richard Lounsbery Prize (2022), EMBO membership (2019), and NYSCF Robertson Award (2016). Research Focus: Combines genetics, biophysics, and behavior to study spinal sensory systems. Investigates how CSF-contacting neurons modulate locomotion, posture, and innate immunity. Active in translational projects linking spinal circuits to human conditions like scoliosis. Grants & Collaborations: ERC grants (Starting 2012, Consolidator 2020), HFSP grants, NIH funding. Collaborates with teams at Sorbonne University, Curie Institute, and institutions worldwide. Labs & Outreach: Directs the Spinal Sensory Signaling lab at ICM. Engaged in science education via the ZENITH European training network and public initiatives like art-science installations. Supervises a multidisciplinary team of researchers and engineers.

Robert Scheidtمشاهده پروفایل

استاد

• Human Motor Control
• Rehabilitation Engineering
• Neuroengineering
• +۴ مورد دیگر

Dr. Robert Scheidt is a Professor in the Joint Department of Biomedical Engineering at Marquette University and the Medical College of Wisconsin (MCW), and holds a joint appointment in the MCW Department of Neurology. He earned his B.S. in Electrical Engineering from Marquette University (1989), followed by M.S. and Ph.D. in Biomedical Engineering from Northwestern University (1992, 1998). His research focuses on human motor control, rehabilitation engineering, and sensorimotor adaptation, with applications in stroke recovery and neurorehabilitation. He leads the NeuroMotor Control Laboratory (NMCL), which explores neural mechanisms of movement control and develops assistive technologies for impaired populations. Dr. Scheidt teaches courses such as BIEN 3300 (Signals & Systems for Biomedical Engineering) and BIEN 6600 (Neuromotor Control), emphasizing engineering principles applied to biomedical systems. His recent grants include NIH-funded projects addressing post-stroke arm non-use and kinesthetic feedback interventions. Key publications (2023–2025) investigate vibrotactile feedback training, wearable systems for rehabilitation, and neural mechanisms of motor adaptation. His work bridges clinical and engineering challenges, aiming to improve sensorimotor function through technology and neuroscience insights. Education: Ph.D., Biomedical Engineering, Northwestern University (1998) M.S., Biomedical Engineering, Northwestern University (1992) B.S., Electrical Engineering, Marquette University (1989) Research Themes: Human motor control, rehabilitation robotics, sensorimotor adaptation, wearable technologies, post-stroke recovery. Grants: NIH R21: Addressing arm non-use post-stroke (2022–2024) NICHD R15: Kinesthetic feedback for hemiparetic arm control (2017–2024) Lab: Founder & Co-Director, NeuroMotor Control Laboratory (NMCL).

• Minimally Invasive Surgery
• Robotic Surgery
• Colorectal Surgery
• +۴ مورد دیگر

Dimitrios Ntourakis serves as Associate Professor of General Surgery at the European University Cyprus (EUC) School of Medicine, Department of Medicine, and concurrently as Chief Surgeon of the Minimally Invasive Surgical Clinic at Athens Medical Group since 2015. His career bridges academic medicine with advanced surgical practice across European institutions. Education Postgraduate Doctoral Degree (PhD) in Medicine, National and Kapodistrian University of Athens (2015) University Diploma (DU) of Colorectal and Anal Surgery, University Paris-Diderot – Paris VII (2013) University Diploma (DU) of Hepatobiliary Surgery, University of Paris XI (2012) Inter-University Diploma (DIU) of Ultrasound Techniques, Universities of Paris, Nancy & Strasbourg (2011) University Diploma (DU) of Laparoscopic Surgery, University of Strasbourg (2010) Medical Degree (Ptychion Iatrikis), National and Kapodistrian University of Athens (2002) Research Focus Dr. Ntourakis specializes in minimally invasive surgical innovation , with expertise spanning robotic-assisted procedures , hepatobiliary interventions , and colorectal techniques . His work emphasizes technological integration in surgery, including augmented reality guidance for liver metastases resection and novel approaches to pancreaticoduodenectomy. The PROGRESSS technique for transanal total mesorectal excision represents a key contribution to colorectal surgical methodology. Publication Trends Analysis of his 11 publications (2010-2018) reveals progressive specialization in robotic and image-guided surgery, with increasing focus on complex gastrointestinal oncology applications. Early work centered on laparoscopic cholecystectomy complications and pancreatic resections, evolving toward advanced techniques like pocket endoscopic submucosal dissection and augmented reality-guided metastasectomy. The consistent thread is technological enhancement of surgical precision in hepatobiliary and colorectal domains. Honors & Recognition Scholarship “Arapaki” for medical studies excellence (National & Kapodistrian University of Athens, 1996) 1st prize for “Exploring the brain” at Nicosia Researcher’s Night (Research Promotion Foundation, 2017) Research Leadership As Scientific Coordinator for Ambulatory Surgery at Athens Medical Group and Research Team Member for Digital Enhanced Learning at EUC, he drives clinical innovation. Funded projects include the French Colorectal Liver Metastases Working Group (AFC), Image Guided Surgery protocols, and eProgress protocol development at IRCAD/University of Strasbourg. His editorial service spans eight surgical journals including World Journal of Surgery and Journal of Gastrointestinal Surgery . Academic Infrastructure Dr. Ntourakis leads EUC’s Simulation Program for medical education and chairs the School of Medicine Structure & Function committee. Through the ELPEN research center joint steering committee, he integrates pharmaceutical research with medical training. His IRCAD lab trainer role since 2010 establishes him as a key contributor to European surgical education curricula.

• Neurology
• Music Cognition
• Brain Plasticity
• +۳ مورد دیگر

Professor Thomas Fritz is a Group Leader in the Department of Neurology at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. His research focuses on music-evoked brain plasticity, neurocognition of music, and the application of music in rehabilitation and clinical settings. He holds a Visiting Professorship for Empirical Music Research at Ghent University since 2015. Education includes a diploma thesis on emotion and music at the Max Planck Institute for Neuropsychology, a PhD collaboration at the Max Planck Institute for Human Cognitive and Brain Sciences, and an MFA in interface design and new media. His work bridges neuroscience, musicology, and technology, with a focus on music's impact on emotion, motor control, and cognitive performance. Key research interests include the neural mechanisms underlying music perception, the therapeutic potential of music in rehabilitation (e.g., Jymmin® system), and the cross-cultural and evolutionary origins of music. He has conducted studies on music's effects in diverse populations, including patients with chronic pain, elderly individuals, and those with Parkinson’s disease. Publications emphasize innovative applications of music feedback in exercise and rehabilitation, neuroplasticity induced by musical engagement, and the physiological correlates of musical emotion. His interdisciplinary approach integrates neuroscience, engineering, and clinical practice to advance therapeutic interventions and cognitive enhancement techniques.

Wutthigrai Boonsukمشاهده پروفایل

دانشیار

• CAD/CAM
• Rapid prototyping
• Manufacturing systems
• +۴ مورد دیگر

Wutthigrai Boonsuk is an Associate Professor and EGT Program Coordinator at the School of Technology, Eastern Illinois University. His research focuses on CAD/CAM, robotics, virtual reality, and geographic information systems. He holds advanced degrees from Iowa State University's Department of Industrial and Manufacturing Systems Engineering (PhD 2009, MS 2005) and a Graduate Certificate in Geographic Information Systems (2011). Research interests include: User interface/UX design for smart technologies Manufacturing automation and rapid prototyping Spatial analysis using GIS Immersive video interface evaluation Recent work explores voice-activated smart home systems, autonomous vehicle technologies, and 360-degree video usability. He teaches courses like Robotics & Control Systems and Plant Layout & Material Handling. Advises robotics competition teams as seen in media coverage of national competitions.

Hao Xiongمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Health Informatics
• Medical Imaging
• +۳ مورد دیگر

Hao Xiong is a Research Fellow at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University. He specializes in applying machine learning and artificial intelligence to healthcare challenges, including medical imaging, signal processing, and clinical diagnostics. His work bridges computer science and health informatics, focusing on applications like cough classification, medical prognosis modeling, and automated analysis of clinical interactions. Key research areas include neural networks, acoustic signal analysis, and deep learning for healthcare applications. His systematic reviews and models address issues such as wet/dry cough differentiation, esophageal fistula prognosis, and delirium-dementia correlations. He has contributed to advancements in brain extraction algorithms, logo detection frameworks, and multimodal clinical data analysis. Dr. Xiong has been recognized with prestigious awards, including the IBM Rational Prize in Software Engineering (2010) and Best Student Paper Award (2016). His work emphasizes interdisciplinary collaboration, evidenced by projects involving robotics, epidemiology, and wearable technology for health monitoring. Awards: IBM Rational Prize (2010), Best Student Paper (2016), First Place in Algorithms (2012), Mentoring in Visual Computing (2017/2018) Grants/Projects: Visual Computing and Big Data Analytics (2017-2018), multiple collaborations in healthcare AI His research portfolio includes over 40 peer-reviewed publications, showcasing his impact in health informatics, medical imaging, and machine learning applications.

• Biofilm Mechanics
• Nanomechanics
• Materials Science
• +۳ مورد دیگر

Dr Jinju Chen is a researcher at Newcastle University specializing in interdisciplinary studies at the interface of biofilm mechanics, nanomechanics, and biomedical engineering. Her work integrates experimental and computational approaches to understand microbial behavior, material interactions, and tissue engineering applications. Key research themes include biofilm formation mechanisms, surface engineering for antimicrobial coatings, and mechanosensing in biological systems. Her research combines advanced experimental techniques like atomic force microscopy with computational models such as CFD-DEM for simulating biofilm dynamics. Notable projects include developing slippery liquid-like surfaces to combat biofilm formation and analyzing bacterial cell wall adaptations under mechanical stress. Collaborations span microbiology, materials science, and robotics, with applications in medical devices and environmental biotechnology. Publications highlight achievements in: Designing anti-biofilm surfaces with long-term efficacy Characterizing novel enzymes for herbicide degradation Modeling fibroblast mechanosensing in engineered substrates Developing thermoelectric materials with tunable thermal properties Her work bridges fundamental science and translational engineering, addressing challenges in infection prevention, energy systems, and regenerative medicine.