جست‌وجوی استاد و پژوهشگر

Arso Vukićevićمشاهده پروفایل

استادیار

• Industrial Engineering
• Artificial Intelligence
• Manufacturing Safety
• +۴ مورد دیگر

Arso Vukićević is an Assistant Professor in the Department of Production Engineering at the Faculty of Engineering, University of Kragujevac. His research focuses on integrating artificial intelligence, deep learning, and robotics into industrial safety, manufacturing processes, and ergonomic systems. Key areas include workplace safety monitoring, waste management automation, and medical device design optimization. He has contributed to over 30 peer-reviewed publications since 2011, emphasizing computational methods in biomechanics, predictive analytics for fracture risk, and Industry 4.0 technologies. His work spans applications like AI-driven personal protective equipment compliance systems, fatigue analysis of coronary stents, and modular lab setups for neuroergonomic studies. Vukićević’s research often bridges engineering and healthcare, such as developing software for coronary artery reconstruction and exploring AI’s role in public building energy management. Notable projects include frameworks for human-robot collaboration in manufacturing, smart warehouse management using machine vision, and evaluating exoskeletons for manual labor safety. His studies frequently employ deep learning, finite element analysis, and IoT sensors to address real-world industrial challenges.

Parag Sawantمشاهده پروفایل

مدرس ارشد

• Occupational Therapy
• Neurorehabilitation
• Cognitive Skills Development
• +۱ مورد دیگر

Parag Sawant is a Senior Lecturer in Occupational Therapy at Health Sciences University's School of Health and Rehabilitation Sciences. A HCPC-registered practitioner with over five years of academic experience, he leads the MSc Occupational Therapy program. His clinical background includes neurorehabilitation specialization and upper-extremity robotics for stroke patients. Research focuses on developing cognitive/metacognitive skills in students and clinicians to reduce cognitive workload. Publications emphasize neurorehabilitation, mental health interventions, and pandemic-related adaptations in occupational therapy practice. Academic credentials include a Master's in Occupational Therapy (Neurosciences) from Maharashtra University of Health Sciences.

Hexu Liuمشاهده پروفایل

دانشیار

• Construction Engineering and Management
• Building Information Modeling (BIM)
• Discrete-Event Simulation
• +۷ مورد دیگر

Hexu Liu is an Associate Professor in the Department of Civil and Construction Engineering at Western Michigan University. His research focuses on integrating emerging technologies like BIM, discrete-event simulation, virtual reality, and AI into construction planning and management. He holds a Ph.D. from the University of Alberta, where he also served as a post-doctoral fellow. Dr. Liu received his bachelor's and master's degrees from Shaanxi, China, and has been recognized with awards such as the Joseph D. Thompson/Zurich Canada Graduate Award and the 2017 Outstanding Reviewer from the Journal of Automation in Construction. His work emphasizes automation in construction through BIM innovations, including semantic quantity take-off and BIM-simulation integration. Research Interests: Building Information Modeling (BIM) and its applications Discrete-event simulation for construction processes AI-driven predictive maintenance and safety monitoring Offsite construction technologies Occupant-centric facility management Recent work highlights include frameworks for highway cost indices during inflation, digital twin-based fire safety systems, and human-robot collaboration in construction. He actively reviews for journals like Automation in Construction and conferences like CRC 2018. Awards and Honors: Joseph D. Thompson/Zurich Canada Graduate Award 2017 Outstanding Reviewer Award (Journal of Automation in Construction) Ernie Tromposch Graduate Scholarship Labs/Teams: Leads the DSC (Data-Driven Sustainable Construction) Lab, focused on advancing smart technologies in construction through interdisciplinary research.

• Stroke Rehabilitation
• Robotics in Healthcare
• Neurorehabilitation
• +۳ مورد دیگر

Nicholas Mark Flynn is a Lecturer at the School of Allied Health within the Faculty of Health Sciences at Australian Catholic University. His research focuses on integrating robotic technologies into stroke rehabilitation, particularly examining clinical implementation challenges and therapist perspectives. Education: PhD in Rehabilitation Science from Australian Catholic University (2022). Research interests center on robot-assisted upper limb therapy for stroke survivors, emphasizing clinical practice sustainability, therapist training needs, and outcomes measurement. His work bridges engineering innovations with clinical workflows in healthcare settings. Publications explore robotic therapy impact on rehabilitation intensity, therapist perceptions, and sustainability in inpatient facilities. His observational studies quantify therapeutic parameters like repetitions and duration post-robotic intervention. No scientific awards explicitly mentioned. Active researcher with 5 peer-reviewed publications between 2019-2025. Labs/Teams: Collaborates with multidisciplinary teams including occupational therapists and physiotherapists in clinical research settings.

• Occupational Therapy
• Rehabilitation Science
• Neurological Conditions
• +۴ مورد دیگر

Elspeth Heather Froude is a Researcher and National Head of School within the School of Allied Health at the Faculty of Health Sciences. Her work focuses on advancing clinical practices in occupational therapy, neurorehabilitation, and pediatric disability care. Key research areas include robotic therapy for stroke survivors, cognitive strategies for neurological conditions, and interventions for children with developmental disorders such as cerebral palsy and fetal alcohol spectrum disorder. Her research emphasizes evidence-based interventions and technology integration in healthcare, with notable contributions to understanding the effectiveness of videofluoroscopic swallowing studies, therapeutic group models for acquired brain injury, and outdoor play accessibility for children with disabilities. She collaborates with multidisciplinary teams to address educational and clinical challenges in speech pathology, occupational therapy training, and vocational outcomes for autistic adults. Publications highlight her expertise in systematic reviews, randomized controlled trials, and instrument development for assessing visual function in children with disabilities. Her work often bridges clinical practice and educational innovation, such as evaluating simulated clinical placements for occupational therapy students and consumer-led mental health teaching methods. Recent trends in her articles emphasize translational research, emphasizing practical applications for improving patient outcomes, therapist training efficiency, and accessibility in healthcare settings. Collaborations span institutions across Australia, reflecting her national leadership role and commitment to advancing allied health sciences.

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

Giovanni Corvini is a Research Fellow at the University of Roma Tre, Department of Industrial, Electromechanical and Mechanical Engineering (DIIEM), working within the Applied Electronics BioLab 3. He received his Ph.D. in Applied Electronics (Biomedical Engineering) in 2024 and has established himself as a researcher in biomedical engineering, artificial intelligence, and robotics. Dr. Corvini's research focuses on the neuromuscular system with the aim of advancing robotic neurorehabilitation for both upper and lower limbs. His expertise includes: Analysis of surface electromyography (sEMG) for muscle fatigue assessment Development of novel metrics for high-density sEMG analysis in the time-space domain Human-robot collaboration systems for rehabilitation EMG-based prediction of movement intentions Biomechanical analysis of human-robot interaction His recent publications (2022-2025) demonstrate a strong focus on the intersection of robotics, biomechanics, and neurorehabilitation. Approximately 60% of his work centers on human-robot collaboration systems for upper limb rehabilitation, 30% focuses on advanced sEMG signal processing techniques, and 10% explores applications in epidemiological modeling and workplace ergonomics. His research shows a clear trajectory toward developing more effective neurorehabilitation technologies through the integration of robotics, signal processing, and biomechanical analysis. Dr. Corvini is actively involved in the HYBR-ID project, which aims to develop an upper limb rehabilitation system integrating exoskeleton assistance and functional electrical stimulation driven by user-tailored synergy-based intention detection. He has also developed Matlab code for high-density sEMG analysis in the time-space domain, which is publicly available. His laboratory work is centered at the Applied Electronics BioLab 3 at Roma Tre University, where he collaborates with researchers including S. Conforto, M. Schmid, D. Bibbo, and S. Ranaldi on various aspects of neurorehabilitation robotics and biomechanical analysis. His research has applications in both clinical rehabilitation settings and workplace ergonomics.

• Biomedical Signal Processing
• Movement Analysis
• Rehabilitation Robotics
• +۲ مورد دیگر

Silvia Conforto is Full Professor of Biomedical Engineering at Roma Tre University, directing the Biomedical Engineering Group. Her research spans signal processing for movement analysis, rehabilitation robotics, and neural interfaces. She leads projects on human-robot collaboration ergonomics and high-density EMG analysis. Recent publications focus on quantitative methods for collaborative robotics safety, prosthetic gait characterization, and quantum-enhanced sensing. Interdisciplinary work bridges biomedical engineering, quantum optics, and ergonomics. Conforto directs the Master in Occupational Health/Safety Risks in Healthcare and leads research on human-robot interaction in industrial settings.

Reza Faieghiمشاهده پروفایل

استادیار

• Robotics
• Machine Learning
• Virtual Reality
• +۶ مورد دیگر

Dr. Reza Faieghi is an Assistant Professor in the Department of Aerospace Engineering at Toronto Metropolitan University and serves as the Director of the Autonomous Vehicles Laboratory. He holds a PhD from the University of Western Ontario, an MSc from Iran University of Science and Technology, and a BSc from Hamedan University of Technology. His research focuses on robotics, machine learning, and virtual reality, with specific applications in uncrewed aerial/ground vehicles, motion control, and human-system interactions. His work integrates advanced control systems with human factors to enhance autonomous systems safety. Current projects include developing intelligent UAV control algorithms, biomechanical modeling for ergonomic design, and VR-based surgical training systems. His research spans aerospace engineering, control theory, biomechanics, and human-computer interaction. Dr. Faieghi teaches courses including Intro to Aerospace Engineering Design, Aerospace Sensors, and Introduction to Machine Learning. He directs the Autonomous Vehicles Laboratory, which focuses on developing intelligent systems for transportation and healthcare applications.

Mark Albertمشاهده پروفایل

دانشیار

• Machine Learning
• Medical AI
• Wearable Technology
• +۳ مورد دیگر

Mark Albert is an Associate Professor in the Department of Computer Science and Engineering at the University of North Texas. He serves as Associate Chair for Graduate Studies, overseeing graduate education programs and academic policies. His research focuses on AI-driven solutions for biomedical applications, wearable technology, and healthcare informatics. Key areas include machine learning for clinical gait analysis, fall risk assessment, and multimodal radiology report generation. Dr. Albert also explores conflict forecasting using large language models and develops assistive technologies for individuals with mobility impairments. His work integrates sensor data analysis, reinforcement learning, and natural language processing to address challenges in rehabilitation engineering, pediatric neurology, and sound exposure monitoring. Notable projects include the Shriners Gait Index, a metric for surgical outcomes in cerebral palsy patients, and AI-organoid systems for biomedical research. He has collaborated on mobile health systems for Parkinson’s disease symptom tracking and wearable spasticity estimation technologies. Dr. Albert’s contributions span 50+ peer-reviewed articles since 2003, with recent emphasis on medical AI applications. He advises graduate students on interdisciplinary projects combining computer science with healthcare, and has developed outreach initiatives like the Brain Geography Mini-Course for neuroscience education.

Ruimin Chenمشاهده پروفایل

استادیار

• Data Analytics
• Statistical Learning
• Uncertainty Quantification
• +۴ مورد دیگر

Ruimin Chen is an Assistant Professor in the Department of Mechanical Engineering at the University of Connecticut (UConn), joining in August 2022. She holds a Ph.D. in Industrial Engineering from The Pennsylvania State University (2021), dual M.S. degrees in Industrial Engineering and Operations Research from the same institution (2018), and a B.S. in Industrial Engineering from Southeast University, China (2016). Her research focuses on data analytics, statistical learning, system identification, and uncertainty quantification, with applications in advanced manufacturing systems, privacy/security, and human-machine teaming. Key areas include quality monitoring in smart manufacturing, additive manufacturing process optimization, and interpretable AI for safety compliance. Her recent work explores federated hyperdimensional computing for distributed quality monitoring, cognitive data fusion in hybrid manufacturing, and brain-inspired computing for melt pool characterization. She also investigates educational strategies integrating Six Sigma principles with hands-on engineering practice. Notable contributions include methodologies for heterogeneous quality characterization in additive manufacturing, causal inference frameworks using Bayesian networks, and ontology-driven process analytics. She emphasizes translational research bridging theoretical computer science with industrial applications.

Farhad Imaniمشاهده پروفایل

استادیار

• Data Analytics
• Machine Learning
• Artificial Intelligence
• +۷ مورد دیگر

Farhad Imani is an Assistant Professor at the University of Connecticut's Department of Mechanical Engineering, part of the School of Engineering. He leads the Intelligent Systems and Control Laboratory (ISCL), focusing on AI-driven advancements in manufacturing systems, robotics, and quality control. His work integrates machine learning, federated learning, and hyperdimensional computing to address challenges in additive manufacturing, privacy preservation, and smart manufacturing processes. Education: He holds a Dual-title Ph.D. in Industrial Engineering and Operations Research from Pennsylvania State University (2020). His research is supported by grants from NSF and CCAT, and he has authored over 50 peer-reviewed articles in top journals and conferences. Research Interests: Core areas include data analytics, machine learning applications in manufacturing, federated learning, privacy-preserving techniques, robotics, and anomaly detection. His lab develops tools for intelligent process monitoring, defect localization, and cooperative robotic systems in advanced manufacturing. Awards: Recipient of the NSF Graduate Research Fellowship Honorable Mention (2024), CCAT Faculty Fellow (2024), and multiple fellowships from Penn State. He serves as an Associate Editor for ASME's Journal of Autonomous Vehicles and Systems (JAVS). Students & Collaborations: Advises PhD and Master's students (e.g., Zhiling Chen, Danny Hoang) and collaborates with institutions like NIST, UC Irvine, and CCAT. His lab actively participates in STEM outreach programs and industry partnerships. Labs/Teams: ISCL focuses on cognitive computing, digital twins, and edge-based learning systems. Recent projects include the Robotics Dataset ScanBot and privacy-preserving frameworks for manufacturing data.

Jungyoon Kimمشاهده پروفایل

دانشیار

• Evidence-Based Practice Implementation
• Cancer Screening in Underserved Populations
• Long-Term Care Organizational Dynamics
• +۲ مورد دیگر

Jungyoon Kim, PhD, is an Associate Professor in the Department of Health Services Research & Administration at the University of Nebraska Medical Center's College of Public Health. As a Full Member and Research Liaison for the Fred & Pamela Buffett Cancer Center's Cancer Prevention and Control Program, she focuses on improving cancer screening access and addressing health disparities. Education : Ph.D. in Health Policy and Administration (2011) from Pennsylvania State University, MHSM (2006) and BHSM (2004) in Health Services Management from KyungHee University Her research centers on evidence-based practice implementation, cancer screening disparities in rural/urban underserved populations, long-term care organizational dynamics, geriatric workforce development, and primary care delivery innovations. She has pioneered community-engaged approaches to colorectal cancer screening in African American and Latino communities. Recent publications demonstrate expertise in implementation science, health equity research, and social determinants of health analysis. Key themes include cost-effectiveness of preventive care, technology-driven care models, and multidisciplinary intervention strategies for rural healthcare systems. Dr. Kim's work bridges public health policy with practical healthcare delivery solutions, focusing particularly on reducing systemic barriers through partnerships and organizational redesign. She previously served as Research and Teaching Assistant at Pennsylvania State University's Department of Health Policy and Administration.

• Robotics
• Artificial Intelligence
• Reinforcement Learning
• +۵ مورد دیگر

Abdeslam Boularias is an Associate Professor in the Department of Computer Science at Rutgers, The State University of New Jersey. His research focuses on robotics, artificial intelligence, and reinforcement learning, with a strong emphasis on robotic manipulation, model-based control, and perception in cluttered environments. He leads research groups in Artificial Intelligence, Intelligent Systems, and Robotics. Key contributions include advancing techniques for dynamic object tracking, sensorimotor learning in unstructured settings, and integrating physics-based reasoning with deep learning. His work has been recognized with prestigious grants such as the NSF CAREER Award and collaborative grants with institutions like Yale University. Grants: NSF NRI Grant (2022), NSF SA&S Grant (2021), NSF CAREER Award (2024) Research Themes: Robotics in clutter, reinforcement learning for manipulation, physics-aware perception, and end-to-end systems for autonomous robots His recent publications emphasize scalable manipulation learning, one-shot imitation, and diffusion models for affordance prediction. He actively contributes to advancing robotic systems that operate reliably in complex real-world scenarios.

Florbela Alexandra Pires Fernandesمشاهده پروفایل

دانشیار

• Optimization
• Nonlinear Programming
• Nonconvex Optimization
• +۶ مورد دیگر

Florbela Alexandra Pires Fernandes serves as an Associate Professor at the Polytechnic Institute of Bragança since 1998, contributing to mathematics education and research. She holds a Bachelor's degree in Mathematics (Education) from the University of Coimbra, a Master's in Applied Mathematics, and a PhD in Sciences (Mathematics) from the University of Minho, establishing a strong foundation in theoretical and applied mathematics. Her educational background includes: Bachelor in Mathematics (Education), University of Coimbra MSc in Applied Mathematics, University of Minho PhD in Sciences (Mathematics), University of Minho Professor Fernandes' research centers on Optimization, specializing in algorithm development for nonlinear and nonconvex problems with mixed variables. Her work bridges theoretical mathematics with industrial applications, extending into machine learning, data analysis, and educational technology through the MathE platform. She actively promotes mathematics education through initiatives like mathematical games for student engagement and inclusive projects such as Eurekit for visually impaired learners. Analysis of her 61 publications (2023-2025) reveals strong interdisciplinary trends: optimization algorithms applied to waste management (hybrid fleet routing), healthcare (LiDAR-based rehabilitation and liver disease diagnosis), retail safety (occupational accident prediction), and educational technology (fuzzy clustering for student categorization in MathE). Her work consistently transforms theoretical algorithms into practical solutions across diverse sectors. She has coordinated or collaborated in multiple funded projects: Eurekit: Inclusive educational games for visually impaired and colorblind students e-nature: Environmental science education initiatives mathE: Intelligent mathematics learning and assessment platform SmilD: Educational technology development FIT4FoF: Workforce upskilling for factories of the future SmartHealth: Robotic systems for upper limb rehabilitation Professor Fernandes leads interdisciplinary teams connecting mathematics with engineering, healthcare, and education. Her MathE platform development involves computer scientists and educators, while SmartHealth collaborations include rehabilitation specialists and robotics engineers, demonstrating her ability to bridge theoretical research with real-world implementation through strategic partnerships.

Kerry Londonمشاهده پروفایل

استاد

• Construction and Design Management
• Building Information Modelling (BIM)
• Sustainable Urban Development
• +۶ مورد دیگر

Professor Kerry London is Deputy Vice-Chancellor Research at Torrens University Australia, overseeing research and innovation strategy. She holds a PhD in Construction Supply Chain Procurement Modelling and has led transformative initiatives across academia and industry. Her career includes roles at the University of South Australia, RMIT University, and Deakin University, where she became Australia’s first female Chair in Construction Management. She is a Fellow of the Chartered Institute of Building and NSW Royal Society of Science, and chairs the Sustainable Infrastructure Institute of Australia. Education: PhD in Construction Supply Chain Procurement Modelling, University of Melbourne (2005) Master of Building Research, University of Newcastle (1997) Bachelor of Architecture, University of Newcastle (1987) Bachelor of Science (Architecture), University of Newcastle (1985) Research Focus: Professor London specializes in supply chain theory, sustainable urban development, technology adoption in construction (e.g., BIM, robotics), and mental health in construction workforces. She has supervised 17 PhD students and authored over 200 peer-reviewed publications. Grants & Projects: Awarded 25 externally funded grants, including Discovery and Linkage projects. Current initiatives include the Reducing Alcohol Consumption and Australian Rental Monitor projects. She leads research on BIM for safety management and off-site manufacturing innovations. Awards & Recognition: Fellow, Chartered Institute of Building Board Chair, Sustainable Infrastructure Institute ARC College of Experts HCA Panel Representative Labs & Teams: Active in the Centre for Healthy Sustainable Development (CHSD) and collaborates internationally on ISO standards and housing resilience frameworks. Her work aligns with UN SDGs for sustainable cities and quality education.