جست‌وجوی استاد و پژوهشگر

• Neurotechnologies
• Neurorehabilitation
• Brain-Computer Interfaces (BCI)
• +۵ مورد دیگر

Professor Aleksandra Vuckovic holds the position of Professor of Neurotechnologies and Rehabilitation in the Department of Biomedical Engineering at the University of Glasgow, within the James Watt School of Engineering. She has been affiliated with the University of Glasgow since 2008 and is also Co-Director of the Scottish Centre for Innovation in Spinal Cord Injury. Her academic background includes an MEng in Engineering Physics and an MSc in Control Systems from the University of Belgrade, followed by a PhD in sensory-motor interaction from Aalborg University (2004). She has held roles at the University of Essex and Aalborg University, and is a Chartered Engineer (IMechE Fellow). Her research focuses on Brain-Computer Interface (BCI) systems for neurorehabilitation, particularly targeting patients with spinal cord injuries. Key areas include developing home-based BCI therapies for neuropathic pain management, combining BCI with functional electrical stimulation (FES), and exploring EEG-based biomarkers for pain prediction. She also investigates neuroplasticity changes and EEG patterns in neuropathic pain conditions. Professor Vuckovic’s work spans over 120 publications, emphasizing BCI applications, EEG analysis, and translational neurotechnology. Her recent studies highlight advancements in spinal cord stimulation effects, neurofeedback success factors, and neuromorphic models for clinical diagnostics. She actively collaborates with institutions like the International Brain Computer Interface Society and serves as an associate editor for journals such as IEEE TNSRE and Frontiers in Neuroergonomics. Her contributions extend to grants and interdisciplinary projects, including the EU-funded CHIST-ERA initiative for BCI translational efforts. She emphasizes patient-centered approaches to BCI design and has pioneered self-managed therapies for chronic pain, recognized by Innovate UK as a Neurotechnology of the Future.

Christian Backمشاهده پروفایل

استاد

• Condensed Matter Physics
• Magnetic Materials
• Spin Dynamics
• +۳ مورد دیگر

Prof. Christian Back is a Full Professor of experimental physics at the Technical University of Munich (TUM), specializing in functional spin systems within the TUM School of Natural Sciences. He holds a PhD from ETH Zurich and has held academic positions at the University of Regensburg and TUM. His research focuses on condensed matter physics, particularly high-quality fabrication of magnetic layered systems and dynamic magnetic property investigations using advanced microscopy and magneto-transport methods. Education: Doctorate: ETH Zurich (1992-1995) Postdoctoral roles: Stanford Linear Accelerator Center (1995-1996), IBM San Jose (1996-1997) Research Assistant: ETH Zurich (1998-2001) Research Interests: Nanostructured magnetic elements, spin dynamics, magnonics, skyrmion-based computing, and interfacial phenomena in magnetic materials. He has pioneered techniques such as Fourier transform imaging of spin vortices and phase-resolved spin wave analysis. Publications Trends: Recent work emphasizes spin wave engineering, strain-mediated computing, and chiral magnetism. Key areas include spin Hall effects, magnonic waveguides, and skyrmion lattice manipulation. Awards: IBM Technical Achievement Award (1997) Swiss National Science Foundation Research Grant (1995) Leadership Roles: Spokesperson for DFG Priority Program 1538 (2011-2017), board member of collaborative research centers 689 and 1277. Labs/Teams: Leads experimental physics research groups at TUM focusing on spin systems and magnonics applications.

• Condensed Matter Physics
• Nanotechnology
• Surface Science
• +۷ مورد دیگر

Dongchen Qi is an Associate Professor in the School of Chemistry & Physics at Queensland University of Technology (QUT), Faculty of Science. He has established himself as a leading researcher in condensed matter physics and materials science, with a focus on creating, understanding, and controlling surfaces and interfaces at the nanoscale to develop next-generation electronic devices. His research spans diamond surface electronics, quantum devices, organic semiconductors, and 2D materials, utilizing advanced synchrotron light techniques to examine critical interface phenomena. Condensed Matter Physics Nanotechnology Surface Science Quantum Technology Diamond Electronics Organic Electronics Professor Qi's research program demonstrates significant evolution from his early work in surface science to his current focus on diamond nanoelectronics and 2D materials. His publication output has grown substantially since 2019, with 28 papers published in 2021 alone, reflecting increasing research impact and collaborative networks. His work bridges fundamental physics with practical device applications, particularly in electronic devices based on emerging materials. Fellow of AIP (FAIP) (2025) Advanced Materials Award recipient (2025) ARC Future Fellowship awardee (2017) Vebleo Fellow (2020) National Honorary Treasurer of AIP (2023-present) Professor Qi actively supervises PhD and Masters students, with current research projects focusing on 2D ferroelectric devices for non-volatile memory and neuromorphic computing, electronic properties of free radical-substituted conjugated polymers, and engineering two-dimensional ferroelectricity by molecular adsorption. He leads multiple Australian Competitive Grants projects and collaborates internationally through the QUT/Max Planck Institute of Colloids and Interfaces Joint Laboratory on Nanocatalysis for Sustainable Chemistry.

• Drug Discovery
• Bioorganic Chemistry
• Nanophotonics
• +۴ مورد دیگر

Professor Andrew Abell is a Professor of Chemistry at the University of Adelaide, leading the School of Physics, Chemistry and Earth Sciences. He holds adjunct roles at the University of Canterbury and Lincoln University. His research focuses on drug discovery, enzyme inhibitors, and nanoscale biophotonics, with notable contributions to antibiotic development and bioorganic chemistry. He co-founded Calpain Therapeutics to commercialize anti-cataract treatments. Education: BSc(Hons) and PhD from the University of Adelaide, followed by a postdoctoral fellowship at the University of Cambridge. He has held professorships at the University of Canterbury and returned to Adelaide in 2007. He directs the Adelaide Node of the ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP) and was Head of the School of Chemistry and Physics. Research interests include small molecule inhibitors of proteases, biotin protein ligase, and surface-immobilized peptides. Key achievements include pioneering non-steroidal inhibitors of steroid 5α-reductase, developing gramicidin S derivatives, and advancing light-activated antimicrobial therapies. Recognition: Adrien Albert Prize (RACI), Alexander R. Matzuk Prize, and Easterfield Medal. He has supervised over 80 PhD students and 50 postdocs, with 100% completion rate.

Juyoung Leemمشاهده پروفایل

استادیار

• Nanoscience and Engineering
• Functional Materials
• Energy Materials
• +۴ مورد دیگر

Juyoung Leem is an Assistant Professor in the Department of Mechanical Engineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. She joined UT Dallas in August 2023 after postdoctoral research at Stanford University (2020–2023). Her academic journey includes a Ph.D. in Mechanical Engineering from the University of Illinois at Urbana-Champaign (2020), and earlier degrees from KAIST (B.S. 2011, M.S. 2013). Leem’s research focuses on nanoscience and engineering, functional hybrid materials, and their applications in energy, sensing, optoelectronics, and bio-interfaces. Her work explores nanoscale phenomena, advanced material synthesis, and micro/nano fabrication techniques. Key projects include designing strain-engineered 2D materials, developing plasmonic sensors, and optimizing energy materials through machine learning. Her publications highlight interdisciplinary advancements, such as tailoring solid fuel properties via covalent interfaces, using ML for soft material design, and analyzing electrochemical systems. She has received prestigious awards including the TomKat Postdoctoral Fellowship and Carbon Journal Prize for her PhD thesis. Leem’s lab emphasizes innovation in nanomaterial applications, with a strong emphasis on translating fundamental research into practical technologies. Her academic contributions span over 20 peer-reviewed articles, reflecting her expertise in materials science, nanotechnology, and interdisciplinary engineering.

• Neuromorphic Computing
• Robotics
• Cognitive Systems
• +۳ مورد دیگر

Prof. Dr. Yulia Sandamirskaya is a faculty member at Zurich University of Applied Sciences (ZHAW) in the School of Life Sciences and Facility Management. She leads the Institute of Computational Life Sciences and is an ORCID-registered researcher with a focus on neuromorphic computing and cognitive systems. Her work bridges computational neuroscience with practical robotics applications. Robotics for dementia care Neuromorphic computing Embodied AI systems Spiking neural networks Industrial force-control systems Human-robot interaction Her recent publications demonstrate expertise in neuromorphic architectures for sensory processing, including visual scene understanding, spectral classification, and real-time control systems. She actively contributes to setting benchmarks in neuromorphic computing and develops practical applications in healthcare robotics. Current projects include RobotCare (service robots for elderly care), Neuromorphic Technology for Embodied AI , and Emerging AI (completed). She collaborates with institutions in Switzerland, UAE, and Italy while working on industrial applications of neuromorphic systems.

Scott Koziolمشاهده پروفایل

دانشیار

• Robotics
• Neuromorphic Engineering
• Embedded Systems
• +۹ مورد دیگر

Dr. Scott Koziol is an Associate Professor and Associate Chair in the Department of Electrical & Computer Engineering at Baylor University, College of Engineering. He is actively leading research and teaching in robotics, embedded systems, and neuromorphic engineering. PhD in Robotics, Georgia Institute of Technology (2013) MS in Mechanical Engineering, Georgia Institute of Technology (2011) MS in Electrical Engineering, Iowa State University (2000) BS in Electrical Engineering, Cedarville University (1998) His research focuses on robotics, neuromorphic engineering, embedded systems, and analog/digital signal processing . He develops bio-inspired algorithms for autonomous navigation and implements them using reconfigurable analog VLSI and Field Programmable Analog Arrays (FPAA). His work integrates machine learning with stochastic computing and explores event-based vision, quantum random number generation, and assistive technologies such as The Reminding Walker device. His recent publications span topics including autonomous path planning, millimeter-wave radar for biomechanics, stochastic neural networks, and quantum workforce development. These works appear in journals like IEEE Access , Entropy , and Quantum Science and Technology , reflecting a multidisciplinary approach that bridges robotics, computing, and biomedical applications. Best Live Demo Award, ISCAS 2010 Outstanding Poster Presentation Award, URSA Scholars Week 2016 Dr. Koziol advises numerous graduate and undergraduate students, including thesis authors in robotics and neuromorphic computing. His research is supported by sponsors such as DARPA, ONR, DOE, and Baylor’s internal programs. He leads the Neuromorphic & Robotic Systems Lab located at the Baylor Research and Innovation Collaborative (BRIC), where his team conducts cutting-edge work in hardware-based neural computation and autonomous systems.

• Nanotechnology
• Materials Science
• Neuromorphic Computing
• +۳ مورد دیگر

Gisya Abdi , an Adjunct Assistant Professor at the Department of Photophysics and Electrochemistry of Semiconductors within the Academic Centre for Materials and Nanotechnology at AGH University of Science and Technology, focuses on advanced materials for neuromorphic computing and environmental applications. Her work spans memristor development, nanomaterials for greenhouse gas adsorption, and artificial photosynthesis systems. University: AGH University of Science and Technology School: Academic Centre for Materials and Nanotechnology Department: Department of Photophysics and Electrochemistry of Semiconductors Email: agisya@agh.edu.pl Research Interests: Design of memristors for neuromorphic data computing and synaptic plasticity Development of nanomaterials for reservoir computing and sensor technologies Study of multiferroic ceramics and unconventional resistive switching mechanisms Application of graphynes and graphene oxide derivatives in environmental science Article Trends: Recent publications highlight memristor-based neuromorphic systems, nanomaterials for energy/environmental applications, and hybrid technologies integrating electrochemical and optical properties. Key areas include physical reservoir computing, diffusive memristors, and adsorbent materials for pollution mitigation.

• Virtual Reality
• Augmented Reality
• Computer Vision
• +۶ مورد دیگر

Prof. Dr. Didier Stricker is a distinguished Professor of Computer Science at Rhineland-Palatinate University of Technology Kaiserslautern-Landau (RPTU) and serves as Scientific Director and Head of the Augmented Reality Research Department at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern. He leads the Augmented Vision Group, which comprises approximately 30 researchers working across various domains of computer vision and augmented reality. His work bridges academic research with industrial applications through collaborations with major companies including Sony, Google, and John Deere. His educational background includes electrical engineering studies at the Polytechnic Institute of Grenoble and the Technical University of Karlsruhe. He earned his doctorate from the Technical University of Darmstadt in 2002 with a dissertation on "Computer Vision-Based Calibration and Tracking Methods for Augmented Reality Applications." Prof. Stricker's research spans virtual and augmented reality, computer vision, human-computer interaction, cognitive interfaces, and on-body sensor networks. His work focuses on developing practical applications that enhance human capabilities through advanced visual computing technologies. He has pioneered approaches in video and sensor analytics, particularly in creating cognitive interfaces that respond intelligently to user needs and environmental contexts. His recent publications reveal a strong emphasis on 3D scene understanding, real-time processing for augmented reality applications, and the integration of large language models with spatial reasoning capabilities. There's a clear trend toward more sophisticated multimodal approaches that combine vision, language, and spatial understanding to create more natural and intuitive human-computer interactions. Among his notable achievements: Innovation Prize of the German Society of Computer Science (2006) Organized the first IEEE & ACM International Symposium on Mixed and Augmented Reality (ISMAR) in 2002 Member of the ISMAR steering committee from 2000-2007 Multiple best paper and demonstration awards at major conferences Several registered patents in tracking and augmented reality technologies Prof. Stricker has supervised numerous PhD and Master's students through his leadership of the Augmented Vision Group. His research is supported by significant funding from both European and national research organizations, as well as through industrial partnerships. He serves as an expert reviewer for various research funding bodies and contributes to the academic community through editorial roles for journals and conferences in VR/AR and computer vision. The Augmented Vision Group under his direction maintains strong connections with industry partners and participates in numerous collaborative research projects including LUMINOUS, SHARESPACE, I-Nergy, BIONIC, and VIDETE. These projects span applications in language-augmented XR systems, social experiences in hybrid spaces, AI for energy systems, personalized body sensor networks, and 4D scene analysis.

Elmar Rückertمشاهده پروفایل

استاد

• Robotics
• Machine Learning
• Industrial Automation
• +۳ مورد دیگر

Elmar Rückert is a Professor at the Chair of Cyber Physical Systems at Karlsruhe Institute of Technology. His work focuses on robotics, machine learning, and industrial automation with applications in environmental science and data-driven systems. Recent activities include invited talks on topics like Bayesian Optimization for control systems and deep learning in robotics. Research interests span tactile robot learning, privacy-aware AI, and sensor fusion for autonomous systems. He has published extensively in venues like IEEE International Conference on Robotics and AAAI Conference on Artificial Intelligence, with a strong emphasis on practical applications in industrial processes and environmental monitoring. Key contributions include the EnvoDat dataset for robotic spatial reasoning and methods for skill disentanglement in RKHS. His collaborative work extends to material science and environmental chemistry through partnerships on technology-critical element analysis.

• Humanoid Robotics
• Biped Locomotion
• Tactile Feedback Control
• +۴ مورد دیگر

Dr. Julio Rogelio Guadarrama Olvera is a researcher and leader of the Humanoid Robotics Group at the Chair of Cognitive Systems, Technical University of Munich (Prof. Gordon Cheng). He holds a Dr.-Ing. (Engineering Doctorate) from TUM, awarded with honors in 2021 for his thesis on humanoid robot whole-body control and biped locomotion. His current role includes postdoctoral research focusing on tactile feedback control, object manipulation, and bipedal locomotion. Education: Bachelor's in Mechatronic Engineering (2011), National Polytechnic Institute, Mexico City Master's in Engineering (2013), Center for Research and Advanced Studies, National Polytechnic Institute, Mexico City PhD in Robotics (2021), Technical University of Munich Research Interests: His work centers on advanced robotics systems, particularly tactile-based control for humanoid robots, bipedal locomotion stability, and human-robot interaction. Key areas include: Development of artificial robot skin for sensory feedback Real-time control algorithms for dynamic environments Ethical and safety frameworks for collaborative robots Applications in healthcare robotics and neuroengineering Teaching: Active in teaching advanced robotics courses such as ' Modelling and Control of Legged Robots ' and ' Practical Course RoboCup@Home ' at TUM. Labs/Teams: Leads the Humanoid Robotics Group within ICS, collaborating with international teams on projects like tactile feedback systems and robot skin technology. Involved in EU and industry-funded robotics initiatives.

• Numerical Methods
• Semiconductor Devices
• Perovskite Photovoltaics
• +۷ مورد دیگر

Patricio Farrell is a Senior Lecturer and Research Group Leader in Applied Mathematics at the Weierstrass Institute Berlin (WIAS). His work bridges mathematical theory and engineering applications, focusing on numerical methods for semiconductor devices, perovskite solar cells, and neuromorphic materials. He leads the 'Methods for Innovative Semiconductor Devices' group at WIAS and serves as Vice Chair of the Committee for Mathematical Modeling, Simulation, and Optimization (KOMSO). Affiliations: WIAS Berlin, Freie Universität Berlin (Privatdozent), Berlin Mathematical School (Mentor) Educations: PhD in Applied Mathematics (University of Oxford), Diplom (University of Hamburg/University of Bath) His research emphasizes structure-preserving numerical methods for drift-diffusion systems, with applications ranging from next-generation semiconductors to photonic crystal lasers. He develops simulation tools like ChargeTransport.jl and contributes to open-source numerical libraries such as VoronoiFVM.jl. Key projects include the ARISE initiative for semiconductor solvers (€1M), Excellence in Photonic Crystal Surface Emitting Lasers (PCSELence), and MATH+ projects on perovskite devices and semiconductor mechanics. Farrell is a scientific ambassador for Brain City Berlin and actively publishes in top journals, emphasizing computational methods for energy transition and material science challenges.

• Spintronics
• Nanoscale Materials
• Spin Logic Devices
• +۷ مورد دیگر

Luqiao Liu is an Associate Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT. He is affiliated with the Research Laboratory of Electronics (RLE) and leads the Spintronic Material and Device Group. His research focuses on spin electronics (spintronics), nanoscale materials, and spin-based devices for low-power computing, non-volatile memory, and microwave applications. His work explores spin-orbit interactions in topological insulators, antiferromagnets, and hybrid systems. Liu holds a BS in Physics from Peking University and a PhD in Applied Physics from Cornell University. Before joining MIT in 2015, he worked at IBM’s T.J. Watson Research Center. Notable awards include the Aravind V. Subramanium T.L. Memorial Award and IBM’s Patent Application Achievement Award. His research group investigates spin-orbitronics, aiming to leverage pure spin currents for energy-efficient devices. Recent work includes magnon-magnon coupling in magnetic garnet bilayers, superparamagnetic tunnel junctions for true randomness, and coherent spin dynamics in antiferromagnetic systems. Collaborations span quantum engineering, hybrid magnonic systems, and neuromorphic computing. Education: PhD in Applied Physics, Cornell University BS in Physics, Peking University Awards: Aravind V. Subramanium T.L. Memorial Award (Cornell) IBM Patent Application Achievement Award Labs/Teams: Spintronic Material and Device Group (MIT)

Bilge Yildizمشاهده پروفایل

استاد

• Materials Science
• Energy Conversion
• Electrochemical Interfaces
• +۷ مورد دیگر

Bilge Yildiz is the Breene M. Kerr (1951) Professor at MIT, holding joint appointments in the Department of Materials Science and Engineering and the Department of Nuclear Science and Engineering within the School of Engineering. Her research focuses on electrochemical interfaces and materials for energy conversion and neuromorphic computing. She earned her BS from Hacettepe University (1999) and PhD from MIT (2003), followed by postdoctoral work at MIT and Argonne National Laboratory before joining MIT's faculty in 2007. Education: BS in Nuclear Engineering (Hacettepe University, 1999), PhD in Nuclear Science and Engineering (MIT, 2003) Research Interests: Electrochemical devices, solid-state batteries, neuromorphic materials, defect chemistry, and corrosion-resistant coatings Labs: Laboratory for Electrochemical Interfaces Her work bridges computation and experimentation to design novel materials for energy-efficient computing and sustainable energy systems. Key contributions include protonic programmable resistors for analog deep learning and voltage-controlled magnetic materials. Awards: Rahmi M. Koç Medal of Science (2022) Fellow, Royal Chemical Society (2022) Fellow, American Physical Society (2021) Ross Coffin Purdy Award (2018) Charles W. Tobias Young Investigator Award (2012)

Jing Sheng CHENمشاهده پروفایل

استاد

• Spintronics
• Magnetic Materials
• Multiferroics
• +۷ مورد دیگر

Professor Jing Sheng CHEN is a distinguished faculty member in the Department of Material Science and Engineering at the National University of Singapore (NUS), College of Engineering. He serves as Principal Investigator leading an experimental materials science research group with state-of-the-art facilities for thin film deposition, nanofabrication, and magnetic characterization. His research has received international recognition including IEEE Fellow status and IEEE Magnetics Society Distinguished Lecturer appointment. Professor Chen's research focuses on cutting-edge areas of spintronics and magnetic materials, with particular emphasis on high anisotropy magnetic materials for hard disk drives, perpendicular anisotropy based magnetic tunnel junctions, Rashba/spin Hall effects, multiferroic materials and devices, and nanostructured magnetic systems. His work bridges fundamental physics with practical applications in next-generation memory and computing technologies. The research group maintains strong international collaborations with institutions across Asia, Europe, and North America. Analysis of recent publications reveals a strong trend toward antiferromagnetic spintronics, topological spin transport phenomena, and the integration of ferroelectric control with spin-orbitronic devices. The group has made significant contributions to understanding chiral antiferromagnetic order, electrical manipulation of topological states, and the development of energy-efficient spin current generation mechanisms. Their work spans fundamental physics discoveries to prototype device demonstrations with potential applications in neuromorphic computing and low-power electronics. IEEE Fellow (2024) IEEE Magnetics Society Distinguished Lecturer (2022) Professor Chen has supervised numerous PhD students, Master's students, and postdoctoral fellows who have gone on to successful careers in academia and industry worldwide. His group has secured substantial research funding supporting advanced facilities including multiple sputtering systems, pulsed laser deposition equipment, and sophisticated magnetic characterization tools. The research program maintains strong industry connections with major data storage and semiconductor companies. The research group operates specialized facilities including multiple sputtering machines (Kurt J. Lesker with 6 targets, AJA International with 7 targets), pulsed laser deposition systems, ion beam etching equipment, and comprehensive magnetic characterization systems including a 9T PPMS, homemade integrated harmonic Hall voltage measurement system, ferromagnetic resonance system, and magneto-optic Kerr effect setup. These facilities support the group's research in thin film growth, nanofabrication, and advanced magnetic property characterization.