جست‌وجوی استاد و پژوهشگر

Robert J.K. Jacobمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Brain-Computer Interfaces (BCI)
• User Interface Design
• +۵ مورد دیگر

Robert J.K. Jacob is a Professor of Computer Science at Tufts University, affiliated with the School of Engineering's Department of Computer Science. His research focuses on Human-Computer Interaction (HCI), particularly implicit brain-computer interfaces (BCI) using fNIRS and EEG technologies. He has held visiting positions at University College London, Université Paris-Sud, and MIT Media Lab. Education: Ph.D. in Computer Science from Johns Hopkins University. Research Interests : Jacob's work explores novel interaction techniques, adaptive interfaces, and BCI applications. Current projects emphasize real-time fNIRS-based systems for effortless user input, cognitive workload assessment, and neuroadaptive technologies. His lab investigates how brain signals can enhance user interfaces in domains like music learning, gaming, and urban design. Recent Trends in Articles : Recent publications highlight advancements in BCI design, neuroadaptive systems, and interdisciplinary applications of fNIRS. Work spans theoretical frameworks (e.g., NeuroCHI ethics) to practical tools like the Tufts fNIRS dataset. Key themes include improving BCI calibration, exploring AI's role in urban environments, and integrating affective computing into artistic interfaces. Awards : ACM Fellow (2016) ACM CHI Academy Membership (2007) Best Paper Award at CHI 2016 Advising & Grants : Supervised 15+ Ph.D. alumni in HCI and BCI. Served as Vice-President of ACM SIGCHI and co-chair of UIST/CHI conferences. Active in editorial roles for Human-Computer Interaction and ACM Transactions on Computer-Human Interaction . Labs & Teams : Directs the Tufts HCI Lab in the Joyce Cummings Center. Collaborates with interdisciplinary teams on projects like the Marble Track Audio Manipulator and Reality-Based Interaction Framework.

Thomas K. Uchidaمشاهده پروفایل

دانشیار

• Biomechanics
• Dynamical Systems
• Musculoskeletal Modeling
• +۷ مورد دیگر

Thomas K. Uchida is an Associate Professor in the Department of Mechanical Engineering at the University of Ottawa, a position he has held since May 2024. Prior to this promotion, he served as an Assistant Professor at the same institution from October 2018 to May 2024. Before joining the University of Ottawa, Dr. Uchida was an Engineering Research Associate (April 2015-August 2018) and Simbios Distinguished Postdoctoral Fellow (July 2012-April 2015) in the Department of Bioengineering at Stanford University. Dr. Uchida's research focuses on the modeling and simulation of dynamic systems, with particular emphasis on human movement biomechanics. His work spans multiple areas including: Simulation-guided design of assistive devices for improving mobility Modelling musculotendon dynamics and energy expenditure Parameter identification and model reduction methods Impact and contact dynamics Development of computational tools for biomechanical analysis He is a co-author of the book "Biomechanics of Movement: The Science of Sports, Robotics, and Rehabilitation" published by MIT Press, and actively contributes to the development of OpenSim, an open-source software platform for modeling musculoskeletal systems and generating simulations of human and animal movement. His work on OpenSim was featured on the cover of PLoS Computational Biology. Dr. Uchida's recent publications demonstrate strong activity in biomechanics, robotics, and computational modeling. His work bridges engineering principles with biological applications, particularly in understanding human movement mechanics. Key trends include applying machine learning to gait analysis, developing enhanced spine models, analyzing human balance stability with time delays, and advancing musculoskeletal simulation techniques. As an academic advisor, Dr. Uchida currently supervises seven graduate students: Firas Baklouti (expected completion August 2025) Shahin Sharafi Kazem Alambeigi Jiawei Gao Yuzhen Yan Manuel Lucas De Oliveira Blake Scott Miller Dr. Uchida collaborates with research teams focused on biomechanics and movement science. His work with OpenSim places him within an international community of researchers developing computational tools for biomechanical analysis, connecting mechanical engineering with biomedical applications in sports, robotics, and rehabilitation.

Alexander M. Petersenمشاهده پروفایل

دانشیار

• Science of Science
• Complex Systems
• Computational Social Science
• +۷ مورد دیگر

Alexander M. Petersen is an Associate Professor and Graduate Chair in the Management of Complex Systems (MCS) department and the Ernest and Julio Gallo Management of Innovation Sustainability and Technology (MIST) graduate group at the University of California Merced (UCM). He is affiliated with the School of Engineering and serves as a key faculty member driving research and academic programs in complex systems and innovation management. His educational background includes a Ph.D. (2011) and M.A. (2008) from Boston University, and a B.S. (2003) in physics and mathematics from the University of Utah. Prior to joining UC Merced, he was a tenure-track faculty member at the IMT Institute for Advanced Studies Lucca in Italy. Petersen's research focuses on the evolution of large multiscale socio-economic systems by applying concepts and methods from complex systems, statistical physics, management, and innovation science. His work spans Science of Science, Computational Social Science, Complex Systems, Quantitative Finance, and Sports Analytics. He has made significant contributions to understanding research collaboration networks, innovation dynamics, convergence science, and the impact of socio-economic shocks on various systems. His publication record demonstrates a clear trend toward increasingly complex interdisciplinary work, particularly in convergence science and network analysis. His most recent publications (2024-2025) focus on global science structure, disruption metrics, national park systems, and the impact of crises on economic behavior. These works often integrate multiple disciplinary perspectives and leverage large-scale data analysis. NSF award #1738163 for research on convergence science Petersen has advised numerous graduate students, including current PhD student Andrea del Pilar Montaño Ramirez and former students Felber J. Arroyave Bermudez (PhD in Environmental Systems) and Dr. Dong Yang (MCS Postdoctoral Scholar). His research has been supported by competitive grants and has resulted in publications in high-impact journals including Nature Communications, Science Advances, and Research Policy. He is actively involved in developing new academic programs, including upcoming B.A. majors in Management of Innovation, Sustainability & Technology (2025) and Data Science & Analytics (Fall 2024). His lab focuses on complex systems analysis, with current projects examining university digital media networks, disruption metrics in science, and the integration of regional innovation systems. The research group maintains an active presence in the science of science community, regularly presenting at conferences like the Science of Team Science conference (INSciTS).

• Photonics
• Laser Technology
• Machine Learning
• +۵ مورد دیگر

Professor Robert Eason is a leading academic at the University of Southampton, specializing in photonics and laser technology. His research spans interdisciplinary areas combining Machine Learning , Medical Diagnostics , and Microfluidics . Research Interests : Eason focuses on AI-driven laser applications, including deep learning for phototherapy , autonomous laser machining , and low-cost paper-based diagnostic devices . His work bridges photonics with biomedicine and advanced manufacturing. Recent Publications : His 2025 article in Scientific Reports explores AI simulations for psoriasis treatment, while 2024-2022 works address laser-controlled microfluidics, deep learning in microscopy, and reinforcement learning for laser machining. Supervision : He supervises PhD student Georgia Mourkioti in laser-based research projects. External Roles : Eason has served as a speaker at international conferences including the International Symposium on Laser Precision Microfabrication (2018), LAISER (2019), and Deep Learning for Control of Light-Matter Interactions (2022).

• Embedded Systems
• Artificial Neural Networks
• Signal Processing
• +۳ مورد دیگر

Magdalena Szymczyk is a Lecturer in the Department of Biocybernetics and Biomedical Engineering at AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. Her work bridges embedded systems, biomedical signal processing, and geophysical data analysis. Research focuses on energy-efficient sensor networks, neural networks for GPR data classification, and mathematical transforms in signal analysis Expertise in parallel computing, real-time systems, and biomedical engineering applications Her publications (2015–2025) demonstrate a trajectory from parallel neural networks and S-transform/GPR methodologies to recent work on MicroPython in embedded systems. Key themes include energy optimization in distributed architectures and AI-driven signal processing across biomedical and geophysical domains. She has authored works on deterministic chaos in simulations, GPU image processing, and cybersecurity in microcontroller systems. Her current research emphasizes embedded systems security, medical signal diagnostics, and computational methods for geological analysis. She utilizes tools like OpenCL for GPU acceleration and MATLAB for parallel computing implementations.

• Bioinspired materials
• Elastic waves
• Fracture mechanics
• +۳ مورد دیگر

Federico Bosia is Associate Professor at the Department of Applied Science and Technology (DISAT) of Politecnico di Torino, teaching Physics I in Aerospace Engineering. His research focuses on bioinspired materials, elastic wave control, fracture mechanics, and metamaterials, with applications in acoustic engineering and sustainable infrastructure. Current research projects include RAVEN (2024-2028) for atmospheric sensors and AMPHYBIA (2023-2025) on advanced metamaterials. He coordinates the COST Action European Network Bioadhesion (2016-2021) and participates in the Unite! University Alliance (2022-2028). His work spans mechanical and acoustical properties of condensed matter (ERC PE3_2), mechanical engineering (PE8_7), and metamaterials engineering (PE11_13). Recent publications highlight innovations in gradient-index phononic crystals, tunable waveguides, and vibration mitigation systems. Scientific awards include Open Badges Learning to Teach (L2T) and Mentoring Polito Project (M2P) , both issued by Politecnico di Torino in 2023. He supervises PhD students Eloi Perez Compte, Fabio Nistri, and Paolo Han Beoletto, and serves as Associate Editor for Frontiers in Materials since 2017. As Scientific Director , he leads projects like SILENCE (2021-2022) for MRI noise cancellation and BOHEME (2020-2023) under H2020. His lab, the Nonlinear Elasticity and Metamaterials Laboratory (DISAT) , explores nonlinear elasticity and soft matter applications.

• Analog and mixed-signal integrated circuit design
• Computer-aided design (CAD) of electronic circuits
• Design automation (EDA)
• +۵ مورد دیگر

Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.

Ross Koppelمشاهده پروفایل

استاد مدعو

• Healthcare Information Technology
• Medication Errors
• Technology in Society
• +۲ مورد دیگر

Ross Koppel is an Adjunct Professor of Sociology with expertise in healthcare information technology, medication errors, and ethics in social research. His work explores the intersection of technology and societal impacts, focusing on data governance, clinical workflows, and human factors in health IT systems. Research Interests Context-sensitive understanding of medication errors Societal implications of clinical data sharing Ethical challenges in AI and informatics Healthcare cost analysis Scientific Awards Fellow of the American College of Medical Informatics (FACMI)

Fangbao Tianمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Biomechanics
• +۵ مورد دیگر

Associate Professor Fangbao Tian is a distinguished researcher and academic at UNSW Canberra's School of Engineering and Technology, where he also serves as Deputy Head of School for Research since July 2023. Previously, he held positions as Senior Lecturer (2017-2021) and Lecturer (2014-2017) at the same institution after completing postdoctoral research at Vanderbilt University. His academic journey began with a BSc (2006) and PhD (2011) in Theoretical and Applied Mechanics and Engineering Mechanics from the University of Science and Technology of China. Dr. Tian's research focuses on Computational Fluid Dynamics (CFD) tools for complex flows and fluid-structure interaction, with particular emphasis on bio-inspired applications. His work spans modeling laryngeal aerodynamics and vocal-fold vibration, fluid-structure interaction of plates in viscous fluid, fish swimming and insect flight, blood flow dynamics, and non-Newtonian flow phenomena. Recent work has expanded into Martian atmosphere aerodynamics, showing his research's growing interdisciplinary nature. His extensive publication record demonstrates consistent contributions across fluid dynamics, with recent trends showing increasing focus on compressible flows, bio-inspired flight systems, heat transfer applications, and computational methods like Lattice Boltzmann approaches. The research shows strong connections between fundamental fluid mechanics and practical applications in aerospace, biomedical engineering, and environmental systems. UNSW Canberra Goldstar Award 2022 IEEE Outstanding SMCS Chapter Award 2021 Outstanding Volunteer Award 2021 UNSW Canberra Silverstar Award 2018 UNSW Canberra Silverstar Award 2017 Journal of Fluids and Structures Highly Cited Research 2017 ARC DECRA 2016 Dr. Tian actively supervises PhD students across diverse topics including bushfire-enhanced wind loads, bio-inspired flight on Mars, flow control optimization, and fluid-structure interactions in compressible flows. He has secured over $5 million in external funding as Chief Investigator, including significant Australian Research Council projects examining Martian atmosphere aerodynamics, bio-inspired flapping wings, and cardiovascular flow modeling. His editorial roles include Associate Editor for Journal of Fluids and Structures and Scientific Reports, reflecting his standing in the fluid dynamics research community.

• X-ray Imaging
• Computed Tomography
• Medical Imaging
• +۴ مورد دیگر

Nikolai Gustschin is a researcher affiliated with the Chair of Biomedical Physics at the Technical University of Munich (TUM) , associated with the Faculty of Medicine and the Department of Physics . His work focuses on developing advanced imaging techniques for clinical applications. Research Interests: X-ray grating interferometry, dark-field CT, phase contrast imaging, clinical translation of imaging technologies, grating fabrication quality assessment. Recent Publications highlight his contributions to dark-field CT algorithms, vibration modeling for interferometers, and grating fabrication methods. Collaborations with experts in biomedical physics and engineering are central to his work.

• Neuroscience
• Neurobiology
• Visual Neuroscience
• +۳ مورد دیگر

Vincent Bonin is a Senior Lecturer in the Department of Biology at KU Leuven's Faculty of Sciences. He is affiliated with the VIB-KU Leuven Center for Neuro Electronics Research Flanders (NERF) and the KU Leuven Brain Institute (LBI). His research focuses on neural circuits and visual neuroscience, with an emphasis on cortical and subcortical mechanisms of perception and plasticity. Research Interests: Vincent investigates visual coding, cortical connectivity, and brain circuit dynamics. His work spans topics like: Role of non-hierarchical visual pathways in perception Dendritic processing in the superior colliculus Cell type-specific connectivity in layer 2/3 visual cortex Astrocyte-mediated cortical plasticity Development of high-resolution intracortical visual prosthetics Recent Projects: • The contributions of non-hierarchical visual pathways to visual coding and perceptual behavior (2025-2028) • An investigation into cell type-specific connectivity rules in visual cortex (2024-2027) • Short- and long-term circuit mechanisms of motor rehabilitation after spinal cord injury (2024-2027)

Mehmetcan Akbulutمشاهده پروفایل

استاد پژوهشی

• Photonics
• Directed Energy
• Remote Sensing
• +۱۲ مورد دیگر

Mehmetcan Akbulut is an Associate Research Professor at the Wyant College of Optical Sciences , The University of Arizona. His office is located in GCRB 447. Research Focus: Photonics subsystems and systems development with applications in Directed Energy, Remote Sensing, Quantum Optical Networks, Optical Computing, Ultrafast & RF Photonics, and Biophotonics. Key Research Areas: High-energy fiber lasers, coherent beam combining, LIDAR systems, quantum communications, optical computing architectures, and photonic biosensors. Recent publications highlight advancements in injection-locked fiber lasers, SBS suppression techniques, optical Ising machines, and frequency comb applications. His work intersects academic and applied research through collaborations like the Center for Quantum Networks and CIAN projects. The Photonics & Systems Laboratory explores technologies for Directed Energy, wind shear sensing, distributed fiber sensing, and AI-driven biomedical imaging systems.

Maryam Ghahramaniمشاهده پروفایل

مدرس ارشد

• Human Motion Analysis
• Machine Learning
• Rehabilitation Engineering
• +۵ مورد دیگر

Dr. Maryam Ghahramani is a Senior Lecturer in AI & Robotics at the Faculty of Science & Technology, University of Canberra, Australia. She holds a BSc in Electrical Engineering from Shiraz University, Iran, and a PhD in Biometric Gait Analysis from the University of Wollongong, Australia. Biomedical Engineering Researcher Machine Learning Specialist Human Motion Analysis Expert Her research focuses on applying machine learning to human motion analysis for rehabilitation purposes, particularly in three key areas: Parkinson's Disease: Using fNIRS and machine learning for disease detection and motor function assessment Fall Prevention: Analyzing postural sway and risk of falls in older adults Spatial Disorientation: Studying balance in hypoxic aviation environments Recent publications demonstrate her work at the intersection of biomedical engineering, machine learning, and clinical rehabilitation. Current projects include: Young Onset Dementia Detection with 12-week Home-Based Exercise Programs Mild Hypoxia Analysis for Aviation Safety Balancing Mat Performance Evaluation

Ghazal Bargshadyمشاهده پروفایل

مدرس

• Affective Computing
• Artificial Intelligence
• Computer Vision
• +۷ مورد دیگر

Dr. Ghazal Bargshady is a Lecturer at the University of Canberra , with expertise in Affective Computing , Artificial Intelligence , and Healthcare Technology . Her roles include teaching units such as Computer Vision, Data Analytics, and Soft Computing, as well as supervising PhD and Master by Research students in AI-driven projects for healthcare and road safety. Education: She earned her PhD in Artificial Intelligence and Computer Vision from the University of Southern Queensland in 2020. Research Interests: Dr. Bargshady specializes in Computer Vision Deep Learning Biosignal Processing Facial Expression Analysis Human Factors in AI Wearable Sensors Multimodal Data Fusion Brain–Computer Interfaces Her work addresses real-world challenges in pain assessment, depression recognition, and driver safety using cutting-edge AI models. Article Trends: Her recent publications focus on Transformer architectures , fNIRS signal analysis , multimodal pain detection , and depression severity estimation via facial video data. These studies highlight her contributions to AI in healthcare , transportation safety , and biomedical signal processing . Teaching Activities: Dr. Bargshady has lectured units including Programming for Data Science , Computer Vision , and Soft Computing , emphasizing practical AI applications.

Zhandong Liuمشاهده پروفایل

دانشیار

• Bioinformatics
• Big Data analysis
• Machine Learning
• +۵ مورد دیگر

Zhandong Liu is an Associate Professor at Baylor College of Medicine with joint appointments in the Department of Pediatrics and Department of Neurology . He serves as Chief of Computational Sciences at Texas Children's Hospital and co-directs the Quantitative & Computational Biosciences Graduate Program at Baylor. Education: B.S. in Computer Science, Nankai University (2001) M.S. in Computer Science, Wayne State University (2003) Ph.D. in Genomics and Computational Biology, University of Pennsylvania (2010) Dr. Liu's research integrates genomics , machine learning , and bioinformatics to advance understanding of neurological diseases. His work focuses on: Multi-omics data integration for disease mechanism discovery Development of cloud-based CRISPR analysis tools like CRISPRcloud Augmented reality platforms for biomedical data visualization Identification of disease genes through computational models Alternative splicing analysis in cancer and neurodegeneration Single-cell and spatial transcriptomics algorithms His recent publications emphasize Alzheimer's disease , MECP2 syndromes , and computational therapy prediction across multiple domains. Scientific awards include the 2018 Outstanding Service Award from the International Association for Intelligent Biology and Medicine. He has secured major grants from NIH, CPRIT, and NSF for projects including: NSF grant #199977 (2018-2020): Augmented reality therapy platforms CPRIT grant #RP170387 (2016-2019): Network-guided cancer analysis NIH #1R01AG057339 (2017-2022): Alzheimer's disease networks As head of the Liu Lab , he leads teams developing tools like: MARRVEL : Human-model organism gene variant integration CRISPRcloud : Secure CRISPR screen analysis platform CrypSplice : Cryptic splicing detection algorithm