جست‌وجوی استاد و پژوهشگر

Euisik Yoonمشاهده پروفایل

استاد

• Bio-MEMS
• Microfluidics
• Bio-Nanotechnology
• +۶ مورد دیگر

Euisik Yoon is a **Professor of Electrical Engineering & Computer Science** at the **University of Michigan**'s **College of Engineering**. His research focuses on **Bio-MEMS, Microfluidics, Neural Engineering, and Cancer Treatment Technologies**, with a lab dedicated to developing advanced microsystems for neuroscience and biomedical applications. He leads the **Yoon Lab**, which innovates in neural probes, optogenetic interfaces, and single-cell analysis platforms. Key achievements include the **Monroe-Brown Foundation Research Excellence Award (2023)** and the **Best Paper Award at IEEE BIOCAS 2022**. His work spans **neural recording systems**, **microLED-based optoelectrodes**, and **high-throughput cancer cell analysis** techniques like **Hydro-Seq** and **MiniSTAR**. Collaborations with clinicians and engineers have produced breakthroughs in **brain-machine interfaces**, **prostate cancer diagnostics**, and **metastasis research**. Notable projects include **self-assembled origami neural probes**, **ultra-compliant carbon nanotube devices**, and **scalable optogenetic tools** for studying neural networks in vivo. His lab also develops **3D-printed electrophysiology systems** and **low-power biomedical sensors**. Key Awards: Monroe-Brown Award, PCF Challenge Award, Nature Communications Publications Research Themes: Neural interfaces, cancer diagnostics, optogenetics, microfluidics Lab Innovations: Yoon Lab designs bio-inspired sensors, neural probes, and cancer analysis platforms

Gerd von Cöllnمشاهده پروفایل

استاد

• Energy-Efficient Systems
• Embedded Systems
• Cyber-Physical Systems
• +۵ مورد دیگر

Prof. Gerd von Cölln is a Professor of Computer Architecture at the School of Technology, Electrical Engineering and Computer Science, University of Applied Sciences Emden/Leer. His primary focus is on energy-efficient and autonomous systems, particularly in embedded and cyber-physical systems. He leads research in energy-autonomous sensors, low-power electronics, and IoT applications. Education details are not explicitly provided in the text, but his academic role suggests advanced qualifications in electrical engineering or computer science. His research projects include Sichere Offshore-Operationen (SOOP), Energieautarke Sensorsysteme (ID3AS), and LoRaWAN-based sensors (ELVIS), demonstrating expertise in industrial automation, sensor networks, and energy harvesting. Publications emphasize sensor design, wireless communication protocols, and optimization algorithms for complex environments. While no awards are listed, his extensive project portfolio highlights contributions to applied engineering research. Advising details are unavailable, but his role implies supervision of technical projects involving students and industry partners. Prof. von Cölln collaborates on labs and teams focused on maritime automation, industrial IoT, and embedded systems, with projects addressing challenges like harsh environmental conditions and energy sustainability.

• Embedded Systems
• IoT Security
• Digital System Design
• +۳ مورد دیگر

Paulino Ruiz de Clavijo Vázquez is a Professor in the Department of Electronic Technology at the University of Seville. His primary research focuses on embedded systems, IoT security, digital system design, FPGA implementation, and hardware security. He leads and collaborates on numerous research projects, including advanced IoT boot systems, secure embedded communication, and high-precision timing synchronization for IoT devices. Key projects include the IRIS secure boot framework for IoT and the E-LUKS hardware encryption solution. His work spans both theoretical contributions (e.g., novel trigonometric computation algorithms) and applied hardware-software co-design (e.g., NanoFS file system). He has advised doctoral theses such as 'LILA: Low-level IoT Lightweight Applications.' His research also involves FPGA-based systems for real-time applications, including time servers and FFT modules. Projects like HAVOC (hardware audio codec) and HardTIME (high-precision timing) highlight his focus on practical hardware implementations. He has contributed to over 50 peer-reviewed publications, conference presentations, and patents related to embedded systems, digital circuit design, and IoT security solutions.

Hannes Freyمشاهده پروفایل

استاد

• Wireless Networked Systems
• Mobile Robotics
• Sensor Networks
• +۲ مورد دیگر

Hannes Frey is Professor and Head of the Computer Networks Research Group at the University of Koblenz and Landau. His research focuses on the controllability of complex dynamically networked systems including sensor networks, mobile autonomous robot teams, and connected vehicles. The group investigates fundamental theoretical questions and system-level practical issues, with emphasis on transferring theoretical results into practice through prototype implementations. Research interests include: Connectivity and percolation in wireless networked systems Local topology control under graph structure assumptions Cooperative distributed control for wirelessly networked mobile robots Reliable ultra-low latency communication for autonomous platforms Software Defined Networking for IoT systems The group maintains the UniKoRN laboratory for practical research in wireless communication and mobile distributed robotics, supporting research internships and student projects.

Luiz ANET NETOمشاهده پروفایل

استاد

• Optical Communications
• Telecommunications Networks
• Fiber Optics
• +۷ مورد دیگر

Luiz ANET NETO is a Professor in the Département Optique at IMT Atlantique, a leading technological university within the Institut Mines-Télécom network. His research focuses on advanced optical communications, telecommunications networks, and network architecture innovations, particularly in areas like 5G integration, passive optical networks (PON), and software-defined networking (SDN). He has contributed extensively to optimizing high-speed data transmission systems, including work on wavelength-division multiplexing (WDM), cost-effective transceivers, and machine learning-driven network modeling. His projects often bridge theoretical advancements with practical implementations, addressing challenges in optical access networks, fiber optics, and mobile network convergence. Recent efforts emphasize reconfigurable architectures for bidirectional access networks and the integration of SDN for enhanced network flexibility and security. Key areas of research include: High-speed optical transmission systems (up to 200 Gbps) Optimizing PON technologies for 5G fronthaul/backhaul Machine learning applications in fiber optics and network modeling SDN-enabled network slicing for 5G environments His publications highlight trends in ultra-high-speed PONs, low-complexity decoding algorithms, and the synergy between optical and wireless systems. Collaborations often involve industry partners to ensure practical relevance, such as developing cost-effective 50G ONU solutions or analyzing real-time performance of optical access platforms. Despite no explicitly listed awards or students, his contributions are reflected in numerous peer-reviewed journals and conference proceedings.

Michele Magnoمشاهده پروفایل

مدرس ارشد

• Smart Sensing
• Low-Power Machine Learning
• Wireless Sensor Networks
• +۴ مورد دیگر

Michele Magno is a Senior Lecturer and Privatdozent at ETH Zürich's Department of Information Technology and Electrical Engineering (D-ITET), leading the D-ITET Center for Project-based Learning (pbl.ee.ethz.ch). He holds a PhD in Electronic Engineering from the University of Bologna (2010) and has held visiting roles at institutions like the University of Nice and Mid Sweden University. His research focuses on low-power systems, wearable devices, energy harvesting, and IoT applications. Magno has authored over 350 peer-reviewed papers, with a Google H-index of 49. Notable awards include the 2024 Best Paper Award at ECCV and multiple best poster/demo recognitions at IEEE conferences. His industrial collaborations include projects with STMicroelectronics, Texas Instruments, and Logitech. Teaching contributions include courses on embedded systems, FPGA programming, and machine learning on microcontrollers. Magno's innovations span smart sensors for wind turbines, bio-medical monitoring, and autonomous racing systems, with patents in touch communication and energy-neutral devices. Recent work emphasizes ultra-low-power solutions for AI-integrated wearables, energy-efficient IoT nodes, and real-time embedded vision systems. His labs and teams pioneer technologies like TinyssimoRadar for in-ear gesture recognition and WakeMod for ultra-low-power IoT connectivity.

• Wireless Communications
• Deep Learning
• Signal Processing
• +۷ مورد دیگر

Thien Huynh-The is a Professor in the Department of Electrical Engineering at Chungnam National University's College of Engineering, where they lead research in wireless communications, deep learning applications, and IoT systems. With over 150 publications spanning from 2014 to 2025, their work demonstrates sustained academic productivity with significant contributions to 5G/6G networks, spectrum sensing, and federated learning architectures. Research interests focus on the intersection of deep learning and wireless communications, particularly in automatic modulation classification, semantic segmentation for remote sensing, and energy-efficient communication protocols. Their innovative approaches include developing specialized CNN architectures like SRNet for spectrum sensing and CosPoint Transformer for 3D semantic segmentation, addressing critical challenges in 5G/6G systems and metaverse infrastructure. Recent work explores STAR-RIS-aided networks, waveform classification for integrated radar-communication systems, and privacy-preserving federated learning for healthcare applications. Analysis of publication trends reveals increasing focus on metaverse technologies and 6G communications since 2022, with significant contributions to IEEE Communications Surveys & Tutorials and IEEE Internet of Things Journal. Key research areas include federated learning optimization, channel estimation techniques using attention networks, and semantic communication frameworks for edge-assisted metaverse applications. Collaborative research spans multiple institutions with frequent co-authorship with Dong-Seong Kim, Quoc-Viet Pham, and Won-Joo Hwang. Current projects address critical challenges in wireless power transfer, spectrum efficiency, and computational resource allocation in next-generation networks.

• Wireless Sensor Networks
• Internet of Things (IoT)
• 6G Communication Systems
• +۳ مورد دیگر

Yannick Le Moullec is a researcher affiliated with Tallinn University of Technology, specializing in wireless communication technologies, Internet of Things (IoT), and 6G network optimization. His work focuses on energy-efficient systems, device-to-device communication, UAV swarms, and hybrid machine learning models for microfluidic imaging. He has contributed to NB-IoT, RIS-based communication, and federated learning frameworks. Education : Not explicitly mentioned Research Trends : His recent publications emphasize 6G networks, device-to-device discovery, UAV coordination, and edge computing. He explores synergies between reinforcement learning and stochastic resource allocation. Grant Activity : No specific grants listed Labs & Collaborations : Collaborates with teams across Estonia, France, and international institutions on IoT and embedded systems, particularly in healthcare and emergency communication contexts.

• Wireless Communication
• Internet of Things (IoT)
• Network Protocols
• +۴ مورد دیگر

Jong-Deok Kim is an active researcher in wireless communication and IoT systems, with frequent collaborations on publications spanning dynamic channel bonding, network optimization, and low-power protocols. His work addresses challenges in Wi-Fi, LoRa, and millimeter-wave networks, focusing on throughput, latency, and reliability. Research Focus: Wireless networks, edge computing, and blockchain for IoT. Key Topics: Channel allocation, federated learning, and error compensation methods. His recent publications highlight trends in adaptive algorithms for dense networks, hybrid positioning systems, and federated learning applications. Awards and grants are not explicitly mentioned in the provided data.

Irtaza Shahidمشاهده پروفایل

پژوهشگر

• Secure and Private Speech Communication
• Generative AI and Speech/Audio Models
• Deepfake and Misinformation Detection
• +۳ مورد دیگر

Irtaza Shahid is a Ph.D. candidate in Computer Science at the University of Maryland, College Park, and a Researcher in the Networking, Mobile Computing, and Autonomous Sensing Lab (iCoSMoS) under Prof. Nirupam Roy. He is also a Founding Deep Learning Engineer at Hearvana.ai, a stealth AI startup under the AI2 Incubator. Ph.D. in Computer Science (University of Maryland, College Park) MS in Computer Science (University of Maryland, College Park) BS in Electrical Engineering (Lahore University of Management Sciences, Pakistan) His research spans Human-Centric Acoustics , focusing on Speech Privacy , Deepfake Detection , and Earable-Based Health Sensing . He has published in top venues like USENIX Security, ACM MobiSys, and IEEE ICASSP. Recent publications highlight Secure Speech Communication (USENIX Security 2025), UWB Localization (NSDI 2025), and Privacy Frameworks for Extended Reality (HotMobile 2025). These works emphasize Edge AI , Low-Power Acoustic Systems , and Signal Integrity . Scientific Awards: Student Travel Grant (USENIX Security 2025), Student Seed Funding (Maryland Cybersecurity Center 2023), Dean's Fellowship (University of Maryland 2020), and multiple Dean's Honor List Awards (LUMS 2016-2020) His projects include VoiceSecure (tamper-proof speech systems), DPOAE Estimation (health sensing via earbuds), and ThermWare (side-channel defense for IoT devices). He has contributed to Audio Engineering Society conferences and collaborated with industry partners like Nokia Bell Labs.

• Communications
• Networking
• Signal & Image Processing
• +۵ مورد دیگر

Mung Chiang is the Roscoe H. George Distinguished Professor of Electrical and Computer Engineering and President of Purdue University . He holds a PhD from Stanford University (2003) in Electrical Engineering, following earlier degrees from the same institution. His research focuses on optimizing networks and systems, including federated learning, edge computing, and 6G technologies. He leads projects on fog networking, smart data pricing, and social learning networks. Key research areas include network optimization , edge AI inference , and cooperative federated learning . Recent work addresses challenges in dynamic client management, hybrid terrestrial-satellite networks, and energy-efficient D2D systems. His publications emphasize practical solutions for heterogeneous environments and wireless network dynamics. Dr. Chiang has contributed to systems like Coded Edge Computing and Model Predictive Control (MPC) frameworks. He explores the interplay between connectivity and machine learning, with applications in autonomous vehicles and IoT. His work spans theoretical advancements and real-world implementations, including protocols for wireless system discovery and control. Current research trends include 6G innovations, resilient cyberphysical systems, and adaptive learning frameworks for dynamic networks.

• Integrated Circuit Design
• Analog Circuit Design
• CAD for Integrated Circuits
• +۷ مورد دیگر

Günhan Dündar is a Professor at the Department of Electrical and Electronics Engineering, Boğaziçi University. His primary research focuses on integrated circuit design with an emphasis on analog circuits, CAD tools for IC design, and biomedical sensor systems. He specializes in low-power and radiation-hardened analog circuits, RF front-ends, and machine learning applications in analog design. Key projects include embedded ocular pressure sensors in contact lenses, super-regenerative receivers for biomedical implants, and yield-aware analog circuit synthesis tools using AI. His work spans from nanoscale CMOS processes (65nm/40nm) to MEMS sensor systems for medical applications. He has published extensively on topics like SAR ADCs, IR-UWB transmitters, and multi-objective optimization frameworks. His design tools (e.g., DATA-IP, Radispice) address challenges in analog IP development and radiation effects mitigation. His research bridges theoretical circuit design with practical biomedical and aerospace applications.

Jukka Pekolaمشاهده پروفایل

استاد

• Quantum Technology
• Mesoscopic Physics
• Superconductivity
• +۴ مورد دیگر

Jukka Pekola is a Professor at Aalto University's School of Science, holding positions in the Department of Applied Physics, the Centre of Excellence in Quantum Technology (QTF), and the Quantum Phenomena and Devices group. He earned a Doctoral degree in Engineering and Technology from Helsinki University of Technology (1984) and a Master's degree (1982) from the same institution. His research focuses on quantum thermodynamics, nanoscale superconductivity, and mesoscopic physics, with contributions to quantum refrigeration, superconducting circuits, and cryogenic measurement techniques. He leads multiple EU and Academy of Finland-funded projects, including TcQTD (2024–2027) and QNet (2024–2027). Pekola has received prestigious awards such as the Academy Professor title (2014–2018) and the Simon Memorial Prize (2020). His research explores thermalization in quantum systems, Josephson junction dynamics, and quantum heat transport. Over 470 publications and 31 active projects highlight his impact. Notable contributions include bolometric detection of Josephson radiation and ultra-sensitive calorimetry of quantum phase slips. He actively collaborates globally, presenting invited talks on topics like quantum thermodynamics and nano-thermometry. Pekola's work contributes to UN Sustainable Development Goals through advancements in low-temperature physics and quantum technology. His lab focuses on developing quantum sensors and understanding nanoscale energy transfer mechanisms. He supervises research leading to 26 theses and chairs the Finnish National Quantum Institute (InstituteQ).

Simon Baleمشاهده پروفایل

مدرس ارشد

• Radio Frequency Engineering
• Electromagnetic Compatibility (EMC)
• Atomic Clocks and Oscillators
• +۳ مورد دیگر

Dr. Simon Bale is a Senior Lecturer and 4th year engineering project coordinator at the University of York’s School of Physics, Engineering & Technology. He holds a PhD in radio frequency electronics and microwave engineering (2012) from the same institution. His research focuses on oscillators/atomic clocks, electromagnetic compatibility (EMC), shielding, and bio-inspired optimization methods. He is a co-investigator on major projects such as the EPSRC-funded “Compact Quantum Clocks For Precise And Autonomous Position Navigation And Timing” and the EU’s “European Doctoral Network for Safe and Sustainable Electromagnetic Shielding Solutions for Mobility.” Teaching responsibilities include courses on electrical circuits, AC machines, power electronics, computer architectures, and embedded systems for FPGAs. His academic contributions span over 30 publications in top-tier journals and conferences, emphasizing practical applications in EMC testing, oscillator design, and evolutionary computation. He actively collaborates with industry partners like QinetiQ and Keysight, translating research into real-world solutions. Awards include Fellow of the Higher Education Academy (FHEA). His work bridges theoretical innovation and industrial needs, with a focus on optimizing electronic systems through multi-objective approaches. Ongoing projects explore ultra-low phase noise oscillators, shielding effectiveness measurement methodologies, and AI-driven circuit design optimization.

• Quantum Electronics
• Laser Physics
• Photonics
• +۳ مورد دیگر

Dr. Justinas Pupeikis is a Researcher affiliated with the Institute of Quantum Electronics at ETH Zürich. His work focuses on advanced laser systems, including dual-comb lasers, THz spectroscopy, and optical parametric oscillators. He specializes in developing high-precision optical tools for applications in sensing, imaging, and material characterization. His research integrates cutting-edge technologies like free-running solid-state lasers and supercontinuum sources to achieve real-time, high-resolution measurements. Key technical contributions include innovations in dual-comb LiDAR for 3D profiling, ultra-low noise GHz lasers, and mid-infrared spectroscopy systems. Pupeikis' work emphasizes practical applications such as industrial micromachining, biomedical monitoring, and environmental sensing. His publications highlight advancements in laser stability, noise mitigation, and spatiotemporal encoding for microscopy and ranging. His research portfolio spans over a decade, with notable contributions to ultrafast optics, nonlinear photonics, and high-power laser systems. Collaborative efforts with ETH's experimental physics groups have led to breakthroughs in attosecond science and water-window radiation generation. Current projects aim to enhance dual-comb technologies for industrial and scientific applications.