جست‌وجوی استاد و پژوهشگر

András Gyenisمشاهده پروفایل

استادیار

• Quantum Engineering
• Superconductivity
• Quantum Computing
• +۳ مورد دیگر

András Gyenis is an Assistant Professor in the Department of Electrical Engineering at the University of Colorado Boulder, specializing in photonics and quantum engineering. His research focuses on developing hybrid superconducting-semiconducting quantum devices to enhance qubit coherence times. Prior to CU Boulder, he held postdoctoral and visiting positions at Princeton University and the Niels Bohr Institute, focusing on superconducting quantum circuits and topological materials. Education: PhD in Physics (2016, Princeton University), MS/BS in Experimental Condensed Matter Physics (Budapest University of Technology, Hungary). His work bridges quantum material science and quantum information science, emphasizing noise-protected qubit architectures and novel material platforms. Research Interests: Hybrid quantum devices, topological materials, superconducting circuits, coherence time extension, and cryogenic electronics. His lab creates qubits with intrinsic protection mechanisms to counteract environmental noise, advancing scalable quantum computing. Selected Articles: Recent work includes symplectic geometry in quantum circuits (2024), supercurrent reversal in nanowires (2023), and protected qubit designs (2021–2022). These studies explore material integration, dynamical sweet spots, and noise mitigation strategies. Labs/Teams: The Gyenis Lab at CU Boulder develops hybrid qubits and semiconductor-based quantum devices. They seek graduate/undergraduate students for experimental and theoretical contributions.

• Positron Annihilation
• Materials Science
• Condensed Matter Physics
• +۴ مورد دیگر

Paulo Manuel Antunes Mendes Gordo is an Assistant Professor at the University of Coimbra’s Faculty of Science and Technology since 2005. He holds a PhD in Experimental Physics (2005, University of Coimbra) and a Bachelor’s degree in Physics (1988, University of Coimbra). His research focuses on defects in materials, utilizing positron annihilation techniques, and spans fields like condensed matter physics, polymer science, and nuclear medicine. Key research interests include characterizing defects in semiconductors, polymers, and ceramics using advanced spectroscopic methods. He has explored topics such as hydrogen interactions in zirconia, drug delivery systems via polyurethane nanotechnology, and radiation detection instrumentation for medical imaging. His work bridges computational modeling and experimental validation, addressing challenges in material stability and structure-property relationships. Publications trends reflect a strong emphasis on materials science, with contributions to journals like Physical Review B , Journal of Pharmaceutical Sciences , and Physica Scripta . Research often intersects interdisciplinary applications, such as medical imaging devices and polymer-based drug carriers. No scientific awards are explicitly mentioned in the provided information. His career includes prior roles as a junior researcher at the University of Aveiro (1990–1992) and early-career positions at the University of Coimbra (1993–2005). No grants or lab affiliations were detailed in the text, though collaborations with institutions like the University of Aveiro and international teams are evident from co-authorship patterns.

Jeyeon Joمشاهده پروفایل

استادیار

• Wearable Sensors
• Assistive Technology
• Textile Engineering
• +۷ مورد دیگر

Jeyeon Jo is an Assistant Professor in the Department of Textiles, Merchandising and Interiors at the University of Georgia's College of Family and Consumer Sciences. Her research focuses on wearable sensors, assistive technology, and ergonomic design, with an emphasis on sustainable materials and healthcare applications. She holds a Ph.D. in Human Centered Design from Cornell University (2023), an M.S. in Fashion Design (2017), and a B.S. in Clothing and Textiles (2014), both from Seoul National University. **Education:** Ph.D. Human Centered Design, Cornell University (2023) M.S. Fashion Design, Seoul National University (2017) B.S. Clothing and Textiles, Seoul National University (2014) **Research Interests:** Jeyeon develops wearable healthcare solutions using stretchable fiber optics and passive RFID, with a focus on optimizing user comfort and performance. Her work spans assistive technologies, firefighting gear ergonomics, and cross-cultural studies of clothing's sociocultural role. Recent projects include sustainable textile prototyping (LeatherBoard) and gait-monitoring systems (RFInsole). **Awards:** Human Service Studies Graduate Fellowship (Cornell, 2022) Best Brief at ISWC 2021 (2021) Roberta G. & John B. De Vries Graduate Award (Cornell, 2020) **Grants & Advising:** Currently no grants explicitly listed; actively advising students in wearable tech and textile engineering. Editorial roles include Fashion and Textiles (2024–present) and Korean Fashion & Textile Research Journal (2025–2026).

• Biomedical Engineering
• Electrical Impedance Tomography (EIT)
• Medical Device Design
• +۶ مورد دیگر

Professor Alistair McEwan, affiliated with the University of Sydney's School of Biomedical Engineering, specializes in biomedical devices and instrumentation for neurological and cardiovascular diagnostics. As the Cerebral Palsy Chair of Technology and Engineering and Associate Head (External Engagement), he focuses on low-cost medical solutions for resource-limited settings, including neonatal care and stroke detection. His research bridges biophysics and clinical translation, with applications in electrical impedance tomography, wearable sensors, and neuroprosthetics. PhD from University of Oxford Member of the Sydney Nano Institute, Brain and Mind Centre, and Charles Perkins Centre His work explores how tissue electrical properties can enhance understanding of neural signaling and implant design. Clinical collaborators include the Bill & Melinda Gates Foundation for newborn nutrition monitoring. Recent projects involve AI-assisted critical care modeling, bionic devices for stress measurement, and adaptive control systems for neonatal resuscitation equipment.

Sieun Chaeمشاهده پروفایل

استادیار

• Electronic Materials
• Semiconductors
• Neuromorphic Computing
• +۳ مورد دیگر

Sieun Chae is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Oregon State University (OSU), part of the College of Engineering. Her research focuses on the rational design of electronic materials for energy-efficient microelectronics, integrating theoretical and experimental approaches. She holds a B.S. in Materials Science and Engineering from Yonsei University (2015), an M.S. from Seoul National University (2017), and a Ph.D. from the University of Michigan (2022). Prior to her faculty position, she conducted postdoctoral research at Cornell University and worked as a research fellow in South Korea. Her research interests include ultra-wide-band-gap semiconductors, entropy-stabilized oxide memristors for neuromorphic computing, and back-end-of-line compatible semiconductors for 3D integration. Key projects involve developing novel materials for high-power electronics, low-temperature synthesis techniques, and device fabrication to demonstrate state-of-the-art performance. Her group employs first-principles calculations, high-throughput materials informatics, and epitaxial growth methods. Collaborations span computational modeling, materials synthesis, and device engineering to address challenges in power electronics and AI applications. The Chae Lab actively engages undergraduate and graduate students in projects combining theory and experimentation. Publications highlight contributions to semiconductor doping mechanisms, memristor design, and oxide alloy thermodynamics. Advising includes mentoring students in ECE, Materials Science, and Computer Science, with a focus on interdisciplinary research. Lab facilities support thin-film synthesis, materials characterization, and device prototyping.

Hamidreza Mahyarمشاهده پروفایل

استادیار

• Machine Learning
• Network Science
• Natural Language Processing
• +۳ مورد دیگر

Hamidreza Mahyar is an Assistant Professor at the Faculty of Engineering , McMaster University , and an Associate Member of the Computing and Software department. His academic journey includes postdoctoral work at Boston University and TU Wien , and a Ph.D. in Computer Science from Sharif University of Technology . Research Focus: Mahyar's work bridges machine learning and network science , emphasizing graph neural networks for applications in social networks , recommendation systems , drug discovery , and generative AI . His research spans industrial AI (Industry 4.0 projects at Infineon Technologies), biomedical engineering (organoid morphology analysis), and semiconductor manufacturing (wafermap modeling). Scientific Recognition: McMaster Teaching Merit Award (2022) Vector Scholarship in AI (2023) NSERC USRA Award (2022) Google Cloud Platform for Research Award (2018) Best Paper Selection, Complex Networks (2018) Academic Leadership: He mentors PhD students (Taraneh Ghandi) and MSc students (Reza Namazi, Mohammad Khodadad, Ali Shiraei), while leading AI initiatives at Mind Lab 56 and BrainMaven . Former mentees include industry leaders at Google, Accenture, and ETH Zurich.

Prabhakara Akarshمشاهده پروفایل

استادیار

• Wireless Systems
• Cyber-Physical Systems
• Machine Learning for RF
• +۶ مورد دیگر

Akarsh Prabhakara is an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin–Madison, with an additional affiliation in the Department of Electrical and Computer Engineering. He earned his Ph.D. from Carnegie Mellon University in 2024, where he worked under Professors Anthony Rowe and Swarun Kumar. Ph.D., Electrical and Computer Engineering, Carnegie Mellon University, 2024 B.Tech, Electronics and Communication Engineering, National Institute of Technology Karnataka, 2018 His research focuses on building high-fidelity wireless systems for perception and communication, particularly in cyber-physical and robotic applications. He explores machine learning-driven RF systems, novel communication paradigms, wireless-robotics integration, and embedded wireless sensing. His work aims to enable robust perception in challenging environments such as smoke or fog using millimeter wave radar and deep learning. His recent publications in CVPR, ICRA, MobiCom, and ICCV demonstrate a strong trend in using neural methods for radar simulation, super-resolution, and wireless intelligence. Key themes include implicit neural rendering for radar, end-to-end learning for perception, and high-resolution point cloud generation from low-cost sensors. His scientific contributions have been recognized through publications in top-tier venues, though specific awards are not mentioned in the provided text. He is actively involved in mentoring and recruiting students for research in wireless and robotics. He teaches courses such as Intro to Computer Networks and Big Ideas in Wireless: Perception and Communication . He leads research projects like RadarHD, which enables lidar-like perception from mmWave radar, and is developing tools and datasets for community use. His lab emphasizes practical, real-world applications of wireless systems in robotics and autonomous systems.

• Cardiovascular System Modelling
• Biosignal Processing
• Wearable Nanosensors
• +۵ مورد دیگر

Haipeng Liu is an Assistant Professor in the Centre for Intelligent Healthcare at Coventry University. His research focuses on cardiovascular system modeling, biosignal processing, wearable nanosensors, and AI-driven diagnostics. He has supervised over 100 research outputs and holds editorial roles in journals like Frontiers in Physiology and Electronics . His work bridges clinical needs with technological innovation, particularly in healthcare technology and cardiovascular diagnostics. Research Interests: Computational modeling of cardiovascular systems, AI-enhanced diagnostics, wearable sensors, and medical imaging. Key Awards: British Heart Foundation Travel Award (2019), First Prize in National Mathematics Competition (2011). Collaborations: Active in global research networks, including the World Stroke Organization. His recent work emphasizes machine learning applications in cardiology and stroke diagnostics, with publications in Physics of Fluids , European Journal of Radiology , and Frontiers in Genetics . He is a sought-after advisor for PhD students exploring healthcare technology.

Mine Doganمشاهده پروفایل

استادیار

• Environmental Geophysics
• Groundwater Modeling
• Stochastic Hydrology
• +۳ مورد دیگر

Dr. Mine Dogan serves as Assistant Professor of Environmental Geophysics in the Department of Geological and Environmental Sciences at Western Michigan University, with her office located in 1121 Rood Hall (Kalamazoo, MI). She holds a Ph.D. from Michigan State University (2013) and previously held research positions at Clemson University's Department of Environmental Engineering and Earth Sciences. Education: Ph.D., Michigan State University, 2013 Her research integrates geophysics, hydrology, and environmental engineering to investigate subsurface processes using advanced methodologies including drone-based electromagnetic surveys, time-lapse monitoring, and 4D X-ray computed tomography. Key focus areas include tree root hydrology, contaminant transport in groundwater, permafrost characterization, and macropore flow dynamics in heterogeneous soils. Analysis of her recent publications (2018-2024) reveals strong emphasis on unmanned aerial systems for geophysical data acquisition, visualization of fluid transport mechanisms in porous media, and forensic/environmental applications of electromagnetic methods. Recurring themes include the role of biological structures in hydrological processes and innovative approaches to subsurface imaging. Scientific Awards: No awards documented in source material While her advising activities and grant funding remain unspecified in available information, her publication record demonstrates active collaboration across geophysics, hydrology, and environmental engineering disciplines. Laboratory facilities and research team structures are not detailed in the provided texts.

• Oral and Maxillofacial Surgery
• Dental Implants and Bone Grafting
• Maxillofacial Trauma Management
• +۴ مورد دیگر

Michael Johnson is an Adjunct Assistant Professor in the Department of Otolaryngology Surgery at Yale School of Medicine. He serves as Program Director for the Oral and Maxillofacial Surgery Residency Training Program and Associate Chief of Dental Services at Yale-New Haven Hospital. His clinical expertise spans the full scope of oral and maxillofacial surgery, including reconstructive jaw surgery, dental implants, and trauma management. Dr. Johnson holds a DMD from the University of Pittsburgh School of Dental Medicine and a BS in Biology from Eastern Connecticut State University. He is a Diplomate of the American Board of Oral and Maxillofacial Surgery and holds multiple certifications in advanced life support. His research focuses on surgical patient safety, sleep apnea in anesthesia patients, and drug interactions with dental treatments. He has mentored residents in research leading to peer-reviewed publications. Dr. Johnson is a Fellow of the American Association of Oral and Maxillofacial Surgeons and the American College of Surgeons. He has received the Bernard Levine Teacher of the Year Award for his contributions to education, including teaching surgical anatomy and emergency management courses. Professional affiliations include the Connecticut Society of Oral and Maxillofacial Surgeons, American Dental Association, and Shoreline Dental Association. He actively contributes to national lectures on topics such as surgical anatomy, anesthesia safety, and office-based emergency preparedness.

Tingjun Chenمشاهده پروفایل

استادیار

• Wireless Networking
• Millimeter-Wave Networks
• Edge Computing
• +۷ مورد دیگر

Tingjun Chen is the Nortel Networks Assistant Professor in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering, with a secondary appointment in Computer Science. He directs the FuNCtions Lab, focusing on wireless, optical, and quantum networked systems with emphasis on edge computing and energy efficiency. Originally from Tsinghua University (B.S. 2014), he earned M.S. (2018) and Ph.D. (2020) degrees from Columbia University under Gil Zussman. His research spans wireless networking, optical systems, energy-harvesting technologies, and AI-ML integration in communication infrastructure. Recent publications demonstrate expertise in mmWave systems, optical transmission management, and RF in-physics computing, with field trials and testbed deployments in dense urban environments. His work has received multiple top conference paper awards and major grants from NSF, ARO, and industry partners. Key awards include: NSF CAREER Award (2025) IBM Academic Award (2023, 2021) Facebook Fellowship (2019) ACM SIGMOBILE Dissertation Award Runner-up (2021) His lab develops scalable network solutions through projects like: NSF CAREER: Mobile Fronthaul Optimization NSF CC* Integration-Large: Campus RDMA Networking NSF NewSpectrum: Spectrum Monitoring Systems Duke Quantum Network Initiative

• Walking
• Gait Analysis
• Systematic Reviews
• +۵ مورد دیگر

Eva Swinnen is a researcher at the Vrije Universiteit Brussel within the Brubotics Rehabilitation Research Center, focusing on physiotherapy, human physiology, and anatomy. Her work bridges robotics and rehabilitation medicine. Key research areas: Walking (100%), Gait Analysis (86%), Systematic Reviews (59%), Orthotic Devices (51%) Recent Publications (2025): Explore AI applications in stroke rehabilitation, virtual twin technology, and electrotherapy effects on muscle recovery. Notable collaborations include projects with KU Leuven and Radboud University Medical Center. 2022 Kuka Innovation Award Finalist 2019 Phase I & II App Development Competition Winner Supervision: Guided master's theses on topics like Kinect™ system validation, volleyball spike biomechanics, and EMG patterning in motor tasks. Currently involved in EU-funded TARGET consortium initiatives for stroke management.

Yoann Altmannمشاهده پروفایل

استاد

• Statistical signal processing
• Image processing
• Bayesian inverse problems
• +۵ مورد دیگر

Yoann Altmann is Professor in the School of Engineering & Physical Sciences at Heriot-Watt University and a member of the Institute of Sensors, Signals & Systems. Since 2024 he holds the Chair in Electrical, Electronic & Computer Engineering (EECE), directing a research programme that bridges statistical signal processing, computational imaging and quantum & neuromorphic sensing. Education & career: 2010 – Eng. degree (Electrical Engineering), ENSEEIHT, Toulouse, France 2010 – M.Sc. (Signal Processing), National Polytechnic Institute of Toulouse 2013 – Ph.D. (Signal & Communications), IRIT Laboratory, Toulouse 2014-2017 – Post-doctoral Research Fellow, Heriot-Watt University 2017 – Royal Academy of Engineering Research Fellow & Assistant Professor, HWU 2024 – promoted to Professor, School of Engineering & Physical Sciences, HWU Research interests: Prof. Altmann develops mathematical and algorithmic tools for Bayesian inverse problems, with emphasis on single-photon LiDAR, low-illumination imaging, neuromorphic computational sensing, variational inference and sparse reconstruction. His work combines principled statistical modelling with efficient computational schemes to enable imaging in extreme scenarios such as underwater scattering, photon-starved environments, quantum metrology and real-time 3-D scene reconstruction. Publication trends: Across 160 outputs (2011-2025) his recent articles reveal a clear trajectory toward integrating modern machine-learning paradigms—variational autoencoders, diffusion generative models, spiking neural networks—with rigorous physics-based forward models. Applications span quantum parameter estimation, multimode-fiber endoscopy, hyperspectral & Compton imaging, nuclear safeguards and cultural-heritage spectroscopy, demonstrating both methodological breadth and high-impact interdisciplinary deployment. Honours & recognition: Royal Academy of Engineering Research Fellowship – competitively awarded (2017) Grants & datasets: He has generated four open datasets supporting reproducible research in quantum sensing, variational autoencoders, underwater single-photon LiDAR and multispectral fluorescence imaging, reflecting sustained funding and commitment to open science. Continuous peer-review service for IEEE and Elsevier journals since 2013 underlines his standing within the signal-processing community. Labs & teams: He leads the Bayesian Imaging & Sensing Computing (BISC) group ( https://bisc.site.hw.ac.uk ) which hosts post-docs, PhD researchers and international visitors working on statistical machine-learning for imaging, sensing and quantum technologies.

Jordan Cotlerمشاهده پروفایل

استادیار

• Quantum Information
• Quantum Computation
• Quantum Gravity
• +۵ مورد دیگر

Jordan Cotler is an Assistant Professor of Physics at Harvard University, affiliated with the Department of Physics within the Faculty of Arts and Sciences. He holds a BS in physics and mathematics from MIT (2015) and a PhD in physics from Stanford University (2020). Before joining Harvard's faculty, he served as a Junior Fellow at the Harvard Society of Fellows from 2020 to 2024. His research focuses on the intersection of quantum information, computation, and spacetime physics. Key interests include quantum algorithms for analyzing many-body and quantum gravitational systems, information-theoretic frameworks for chaotic dynamics, and non-perturbative methods in quantum cosmology and field theory. Cotler's work has advanced quantum algorithm design for experimental platforms and contributed to understanding black hole microstructure and cosmological spacetimes. He has been recognized with prestigious early-career awards, including his Harvard Society of Fellows Junior Fellowship. His publications span foundational topics such as quantum gravity, holography, computational complexity, and quantum chaos, reflecting a multidisciplinary approach to theoretical physics.

Xi Chenمشاهده پروفایل

استادیار

• AI-Enhanced Optical Imaging
• Quantitative Phase Imaging (QPI)
• Biomedical Imaging
• +۳ مورد دیگر

Xi Chen is an Assistant Professor of Biomedical Engineering at Northwestern University , part of the M McCormick School of Engineering . His research integrates AI with advanced optical imaging techniques to study complex biological systems. Current focuses include quantitative phase imaging (QPI), multiphoton microscopy, and adaptive optics for biomedical applications. Education : Ph.D. in Physics (University of Miami, 201X) B.S. in Applied Physics (Chongqing University, 201X) Postdoc at University of Illinois at Urbana-Champaign NIH K99/R00 Postdoc at Cornell University as a Mong Fellow Research Interests Dr. Chen’s group develops AI-driven optical systems for label-free imaging of live tissues, organoids, and animals. Their innovations include Artificial Confocal Microscopy and Spatial Light Interference Microscopy (SLIM) , enabling high-resolution, quantitative analysis of pathological processes and drug screening. Techniques like Wolf Phase Tomography and adaptive optics enhance imaging depth and resolution in scattering media. Publications Recent work emphasizes integration of machine learning with optical physics to tackle challenges in deep-tissue imaging, phase retrieval, and coherence analysis. Key themes span neural network-driven microscopy, statistical optics of scattering systems, and biomedical diagnostics. Lab & Recruitment His XIQI Lab (Xdeep Intelligent Quantitative Imagine) offers NIH-funded positions for students/postdocs. Visit the lab website for details on open roles and projects in AI-optics convergence.