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نمایش ۷۳۶-۷۵۰ از ۱٬۴۳۳ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Carlos Miguel da Costa Fernandes is an Assistant Researcher specializing in evolutionary computation and swarm intelligence. His work focuses on developing bio-inspired algorithms for optimization problems.
Mirko Kovac is Professor at Imperial College London's Faculty of Engineering and heads the Laboratory of Sustainability Robotics at Empa and EPFL. His research focuses on aerial robotics for distributed sensing and autonomous manufacturing in natural environments, with expertise in robot design and multi-modal mobility. His research interests include bio-inspired aerial systems, robot-assisted construction, environmental monitoring, and multi-modal locomotion. Key innovations include aerial additive manufacturing systems and amphibious robots for ecological assessment. Research publications demonstrate strong focus on robotics applications in construction, environmental monitoring, and advanced manufacturing. Recent work explores aerial-aquatic systems, soft robotics, and sustainable material deposition techniques. Awards include multiple best paper recognitions for contributions to robotics and aerial systems. Leads the Aerial Robotics Laboratory and collaborates internationally with institutions including Harvard, EPFL, and ETH Zurich. Current projects focus on biodegradable robotics and swarm manufacturing systems.
Dr Giovanni Ansaloni is Senior Scientist and Lecturer at EPFL's Embedded Systems Laboratory. His research focuses on energy-efficient computing architectures including reconfigurable systems, near-memory processing, and hardware accelerators for edge AI and biomedical applications. He develops frameworks for deploying machine learning models on resource-constrained devices, specializing in hardware-software co-design for embedded systems. Recent work explores RISC-V based accelerators, in-memory computing architectures, and optimization techniques for health monitoring applications. His teaching covers embedded systems design and applications, bridging theoretical concepts with practical implementation challenges in low-power computing platforms.
استادیار
Sharmistha Bhadra is an Assistant Professor at McGill University, specializing in wearable electronics, biomedical sensors, and flexible optoelectronics. Her research focuses on developing innovative sensor systems for health monitoring, including intraoral wearables, flexible organic photodetectors, and wireless biomedical devices. She has contributed to advancements in biodegradable batteries, motion artifact reduction techniques, and low-power sensor interfaces. Her work integrates materials science, circuit design, and biomedical applications, with notable projects like smart mouthguards for electrooculogram monitoring, printed RFID tags for food quality sensing, and flexible power management systems. Bhadra's research emphasizes practical implementations of sensor technologies in real-world medical and environmental contexts. Key areas of innovation include: 1) Wearable health monitoring systems (e.g., wristbands for vital signs), 2) Printed and flexible electronics for biomedical applications, 3) Organic photodetectors for ambient light sensing, and 4) Passive wireless sensing technologies. Her publications span journals like IEEE Transactions on Biomedical Circuits and Systems, demonstrating interdisciplinary contributions to both hardware and algorithmic aspects of sensor systems.
Professor Bin Yang is a faculty member at the University of Chester, holding the position of Professor of Electromagnetics and Measurements since 2023. Previously, he served as Associate Professor of Terahertz Engineering (2019–2023) and Senior Lecturer (2015–2019). He earned his BEng from Beijing University of Posts and Telecommunications (2001), followed by MSc and PhD in Electronic Engineering from Queen Mary University of London (2004 and 2008, respectively). His research focuses on microwave/terahertz systems for industrial applications, material physics for energy storage and biomedical devices, and electromagnetic measurements on solid-state materials. He has published over 60 peer-reviewed articles, including in Nature Communications and Nano Energy , with an H-index of 24 and ~2600 citations. He has supervised 11 successful PhD students and secured significant research funding as Principal Investigator/Co-Investigator. Research interests span terahertz spectroscopy for material characterization, nanofiber membranes for environmental and biomedical uses (e.g., oil-water separation, drug delivery), and biomedical sensor systems for sleep disorder monitoring. His work integrates advanced manufacturing techniques like centrifugal spinning with material science innovations. Recent publications highlight advancements in piezoelectric ceramics, terahertz-based material analysis, and bio-inspired nanomaterials. He teaches courses at undergraduate and postgraduate levels, including electromagnetic fields, signal processing, and IoT systems.
استادیار
Ann Lui is an Assistant Professor at the School of the Art Institute of Chicago (SAIC), with an affiliation at the Massachusetts Institute of Technology (MIT) within the School of Architecture + Planning and the Art, Culture, and Technology Program. Her research focuses on advanced photonics, materials science, and interdisciplinary applications at the intersection of art and technology. She holds an SMARCHS ’15 degree, likely from MIT’s architecture program. Dr. Lui’s work emphasizes heterogeneous integration of photonic materials, optical phase change materials, and innovative fabrication techniques such as two-photon polymerization. Her research addresses challenges in optical component reliability, low-loss coupling, and sustainable packaging solutions for high-density optical systems. She also explores metasurface-enabled additive manufacturing and bio-inspired assembly methods using DNA origami. Her recent publications highlight advancements in silicon photonics, meta-optical projectors, and failure mechanisms in chalcogenide materials. These studies contribute to next-generation optical communication, sensing, and energy-efficient systems. While no awards or grants are explicitly listed, her prolific output indicates active engagement with industry and academic collaborators. Lui’s affiliations bridge SAIC’s art and design programs with MIT’s engineering and technology initiatives, reflecting a unique interdisciplinary approach to material innovation and applied optics.
Joaquin Martinez Tambella is a staff researcher affiliated with the Institute for Bioengineering of Catalonia (IBEC) , specifically contributing to the Nanoprobes and Nanoswitches research group. His work spans interdisciplinary fields at the intersection of bioengineering, nanotechnology, and biomedical research, focusing on both clinical applications and advanced biomaterials development. Research Interests: His research interests include Nanobioengineering for biomedical applications Development of modular bioinks for 3D printing Signal processing in biomedical systems Mechanisms of bacterial gene regulation Protein phase transitions in disease contexts Smart nano-biodevices for targeted therapeutics Publication Trends: His recent articles highlight expertise in translational research, combining clinical hepatology with bioengineering innovations. Notable contributions include studies on TIPS (Transjugular Intrahepatic Portosystemic Shunt) efficacy in liver failure management and the design of sol-gel polymerized hybrid hydrogels for regenerative therapies. Collaborations: He collaborates extensively with multidisciplinary teams across IBEC, hospitals, and industry partners, emphasizing societal impact through technological transfer. His work involves cutting-edge projects such as CHEMTUBIO (enzyme-based therapeutics) and Fibrosens (sensor devices for muscular dystrophy).
پژوهشگر
Shuqin Chen is a researcher at the Institute for Bioengineering of Catalonia (IBEC), specializing in the Smart Nano-Bio-Devices group. Her work focuses on self-propelled nanomotors and micromotors for biomedical applications, including drug delivery systems, biosensing, and cancer targeting. Affiliation: Institute for Bioengineering of Catalonia (IBEC) Department: Smart Nano-Bio-Devices Current research explores: Swarming intelligence in nanomotors Enzymatic propulsion mechanisms Theranostic integration of nanodevices Biodegradable hydrogel electronics Recent publications highlight collective dynamics of nanomotors in chemical gradients and biomedical applications of self-propelled systems. Research trends indicate strong focus on nanotechnology for diagnostics, environmental remediation, and targeted therapies. Key collaborative networks include partnerships with clinical institutions and industrial stakeholders to advance translational bioengineering projects.
Mark A. Cappelli is a Professor of Mechanical Engineering at Stanford University and Co-Director of the Engineering Physics Program. He holds a B.Sc. in Physics from McGill University (1980), and M.A.Sc. and Ph.D. in Aerospace Sciences from the University of Toronto (1983, 1987). His research focuses on applied plasma physics, with applications in space propulsion, aerodynamics, medicine, materials synthesis, and fusion. He is actively involved in plasma electromagnetics, topological edge states, and plasma metamaterials. Education: Ph.D., University of Toronto, Aerospace Science and Engineering (1987) M.A.Sc., University of Toronto, Aerospace Sciences (1983) B.Sc., McGill University, Physics (1980) Research Interests: Professor Cappelli explores plasma dynamics in diverse contexts, including: Plasma-based propulsion systems and electric thrusters Non-equilibrium plasma chemistry for carbon capture and water treatment Electromagnetic wave manipulation using plasma metamaterials Topological surface states in magnetized plasmas Inverted corona fusion targets for neutron generation Coherent plasma instabilities and diagnostic techniques Grants & Advising: His research is supported by grants from NASA, DOE, and industry partnerships. He advises graduate students in plasma physics and engineering physics, focusing on experimental and computational plasma dynamics. Labs & Teams: Cappelli leads the Plasma Dynamics Laboratory at Stanford, collaborating with interdisciplinary teams in aerospace engineering, materials science, and environmental engineering to advance plasma technologies.
پژوهشگر
Piotr Łuczak is a Researcher at the Institute of Applied Computer Science, Faculty of Electrical, Electronic, Computer and Control Engineering, Lodz University of Technology. His work bridges computer engineering, machine learning, and biomedical applications. Research spans VLSI systems for radar-based health monitoring, thermal imaging for industrial control, hyperdimensional computing frameworks, and neuromorphic approaches. Recent publications demonstrate strong interdisciplinary focus on hardware-efficient AI implementations. Article analysis shows consistent evolution in: (1) Radar-based biomedical sensing with novel signal processing; (2) Thermal imaging for industrial automation; (3) Hybrid AI models combining neural networks with symbolic methods; (4) Neuromorphic computing for edge devices; (5) Optimization techniques for efficient neural architectures; (6) Human-machine interaction systems.
Dr. Jeremy Holleman is an Associate Professor and Program Coordinator of Electrical Engineering at the University of North Carolina at Charlotte. He directs the assessment efforts within the Electrical and Computer Engineering department. His research focuses on low-power analog/mixed-signal circuits, biomedical interface design, neuromorphic computation, and machine learning hardware for resource-constrained systems. He holds a Ph.D. (2009) and M.S. (2006) from the University of Washington and a B.S. (1997) from Georgia Institute of Technology. Dr. Holleman's work emphasizes energy-efficient computing architectures and hardware implementations of machine learning, including contributions to MLPerf Power benchmarks and TinyML standards. His academic background includes over 20 years of experience in analog circuit design, neuromorphic systems, and biomedical signal processing. Notable projects include a 1 Tera-OPS/Watt analog deep learning engine and ultra-low-power neural amplifiers for bio-potential recording. He has published extensively across IEEE journals and conferences, with over 50 peer-reviewed articles. His research has been applied in medical implants, wireless neural interfaces, and energy-harvesting systems. Current initiatives include advancing analog deep learning architectures and sustainable AI hardware optimization. Dr. Holleman’s lab collaborates on hardware-software co-design for embedded machine learning and neuromorphic systems.
پژوهشگر
Dario Prandi is a Researcher at the Laboratoire des Signaux et Systèmes (L2S) within CentraleSupélec, located in Gif-sur-Yvette, France. His work bridges mathematical analysis, control theory, and neuroscience, with a focus on geometric models of vision and auditory processing. He holds a PhD from École Polytechnique (2013) and has authored numerous high-impact publications in journals like SIAM and IEEE conferences. Research interests span sub-Riemannian geometry, neural field equations, and mathematical neuroscience. Notable contributions include cortical-inspired models explaining visual illusions (e.g., MacKay and Poggendorff effects), sound reconstruction via bio-inspired geometric frameworks, and the application of control theory to image processing and neural dynamics. His work often combines advanced mathematical techniques with applications in biomedical engineering and artificial perception. Recent activities include developing homogeneous observers for cortical activity models and analyzing decay rates in nonlinear systems. He collaborates extensively with institutions like Inria and the University of Paris-Saclay, contributing to transversal research axes in energy, Industry 4.0, and health technologies. Labs/Teams: Member of L2S's research groups Modélisation et Estimation, Problèmes Inverses, and the Automatique et Systèmes department. His research aligns with interdisciplinary projects in geometric science of information and hypoelliptic diffusion processes.
پژوهشگر
Mengqi Shen is a Postdoctoral Research Scientist at the Data Science Institute, Columbia University. She collaborates with Professor Yading Yuan and clinicians Dr. Dawn Hershman and Dr. Meghna Trivedi to advance data science applications in cancer treatment and patient care. Her research focuses on explainable machine learning, healthcare monitoring systems, and leveraging large public health datasets. Education: Ph.D. in Industrial and Systems Engineering (Virginia Tech, 2024) Bachelor’s and Master’s in Engineering Mechanics (Dalian University of Technology, direct-entry top student) Research Interests: Data-driven decision-making in healthcare Machine learning for clinical workflows Public health surveillance systems Bio-inspired robotics (prior work) Collaborations: Active partnerships with Tumor Board clinicians to integrate machine learning into cancer treatment reviews. Her work emphasizes translational research bridging data science and clinical practice.
پژوهشگر ارشد
Mohammadmahdi Faraji is a Research Fellow at the International Iberian Nanotechnology Laboratory (INL), where he joined the Integrated Micro and Nanotechnologies Group in April 2021. His work focuses on designing and developing digital electronic systems for MEMS controllers, including precise temperature controllers, gas sensor setups using pyroelectric crystals, and customized drivers for inkjet print heads. Dr. Faraji received his PhD in Digital Systems from Sharif University of Technology, Tehran, Iran in 2020. His doctoral research proposed a distributed sound source localization system using acoustic sensor nodes and a fuzzy fusion algorithm for real-time outdoor applications. He also holds an MSc in Electrical Engineering from Amirkabir University of Technology (2013), where he designed a distributed acoustic source localizer based on wireless sensor networks. His research spans several key areas: MEMS and sensor systems design Digital signal processing and embedded systems FPGA implementation for real-time control Distributed sensor networks for acoustic localization Flexible printed electronics and nanomaterials for sensors Recent publications (2015-2022) demonstrate a progression from acoustic source localization using spiking neural networks to advanced materials for force sensing and printed electronics. His work bridges electrical engineering, materials science, and computational neuroscience. No scientific awards or fellowships are mentioned in the provided text. Dr. Faraji is a member of the Piteira Research Group at INL, contributing to projects in the Integrated Micro and Nanotechnologies Group. His current research involves developing MEMS controllers and sensor systems for diverse applications.
Miguel Salichs Sánchez-Caballero is a Full Professor at the University Carlos III of Madrid , where he serves as Director of the Master's Degree in Robotics and Automation. He is affiliated with the Robotics Lab research group within the Pedro Juan de Lastanosa Institute of Technology Development and Innovation . Department of Systems Engineering and Automation Specializes in Robotics, Human-Robot Interaction, and Biologically Inspired Systems Principal investigator on multiple robotic projects, including MENIR and Robots sociales para estimulación física, cognitiva y afectiva de mayores Supervised numerous theses on social robotics and human-robot interaction Holds a patent for a Robot para la inspección de palas de aerogeneradores His research focuses on social robotics , particularly for elderly assistance and cognitive stimulation. Key areas include biologically inspired decision-making systems , emotion recognition , human-robot emotional bonding , and adaptive behavior modeling . He works extensively with the MINI and Maggie social robots. Recent publications demonstrate strong trends in neuroendocrine-inspired robot behavior , biologically driven attention architectures , and advanced decision-making systems for social robots. The work often combines machine learning with biological modeling to create more natural human-robot interactions. As Director of the Master's program in Robotics and Automation, he plays a key role in shaping graduate education in these fields. His research has received funding from multiple European Commission and Spanish government agencies including the State Research Agency (AEI) and Ministry of Science and Innovation.
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