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Jonathan J. D. McKendryView profile

Research Fellow

• Optical Communications
• Light Emitting Diodes (LEDs)
• Visible Light Communication
• +3 more

Jonathan J. D. McKendry is a Research Fellow at the Institute of Photonics SUPA, University of Strathclyde. He holds an M.S. in Electronics and Electrical Engineering from the University of Glasgow (2006) and a Ph.D. in Physics from the University of Strathclyde (2011). His research focuses on LED-based Visible Light Communications (VLC), particularly leveraging UV-C LEDs for high-speed, secure, and environment-safe data transmission. Key areas include micro-LED arrays, optical modulation techniques, and applications in biomedical传感 and underwater communications. His work spans over 114 peer-reviewed publications and 35 datasets, with notable contributions to UV-C VLC systems achieving up to 150 Mbps over 1 meter. McKendry has received two IEEE Photonics Technology Letters Best Paper Awards (2019, 2022) for pioneering advancements in UV communication and micro-LED technology. He collaborates internationally on projects like Fraunhofer UK Research Limited’s underwater communication studies and EPSRC-funded global engagement initiatives. Current research emphasizes scalable on-chip photonics integration and solar-blind communication systems. McKendry’s activities include invited talks on micro-LED applications and consultancy with Fraunhofer UK. His lab develops cutting-edge devices such as deep UV CMOS-controlled microLED arrays and UV-pumped quantum well systems. Recent breakthroughs include 100-meter UV-C wireless links at gigabit speeds and simultaneous data-display/environment-sensing microLED systems.

Jiyoung KimView profile

Professor

• Nanoelectronics
• Atomic Layer Deposition (ALD)
• Ferroelectric Materials
• +5 more

Professor Jiyoung Kim is a faculty member at The University of Texas at Dallas (UTD) in the Erik Jonsson School of Engineering and Computer Science, Department of Materials Science & Engineering. She holds a Ph.D. in Materials Science and Engineering from the University of Texas at Austin (1994), an M.S. and B.S. in Metallurgical Engineering from Seoul National University (1988, 1986). Her research focuses on nanoelectronics, atomic layer deposition (ALD), ferroelectric materials, and next-generation CMOS technology. Key projects include developing novel ALD applications for high-k gate dielectrics, memory devices, and nano-sensors. She has led grants totaling over $500,000, including NSF-NER and SEMATECH-funded projects. Notable awards include the 2004 Korean Ministry of Science and Technology Outstanding Research Award and 'Who's Who in Science and Engineering' (2000). Her lab collaborates internationally, with recent work on EUV lithography, ferroelectric transistors, and low-thermal-budget materials. Advising over 20 graduate students and postdocs, her team includes recent PhD students like Hyunah Sung and Soham Shirodkar. Research is supported by industry partners such as Samsung and ASM America. Research interests span gate stack engineering, nanostructured materials, and ALD-derived applications. Her team explores ferroelectric Hf0.5Zr0.5O2 capacitors for FRAM, EUV photoresist materials, and 2D semiconductor integration. Recent breakthroughs include low-temperature ferroelectric fabrication and tunable vanadium dioxide devices. The lab's infrastructure includes advanced characterization tools and cleanroom facilities at UTD.

Dongsheng Brian MaView profile

Professor

• Power Management Circuits
• CMOS Technology
• Switched-Capacitor Converters
• +3 more

Prof. Dongsheng Brian Ma is the Erik Jonsson Distinguished Chair in Microelectronics and Associate Professor of Electrical Engineering at the University of Texas at Dallas (UTD). He holds affiliate roles in the Texas Analog Center of Excellence (TxACE) as Executive Committee member and Thrust Leader for Energy Efficiency. Previously, he held faculty positions at the University of Arizona and Louisiana State University, where he pioneered industry-academia collaborations. Ph.D. in Electrical & Electronic Engineering (2003) - Hong Kong University of Science and Technology M.S. in Electronic Science (1998) - Nankai University B.S. in Engineering (1995) - Nankai University His research focuses on advanced power management circuits, CMOS-based sensor systems, energy-efficient analog circuit design, and reconfigurable power converters. Notable innovations include fuel cell power management units and nanometer-scale biomedical sensors. Recent publications emphasize energy harvesting systems, medical imaging sensors, and LED driver optimization. His work appears in top journals like IEEE Journal of Solid-State Circuits and IEEE VLSI Symposium. Recipient of NSF CAREER Award (2009-2014) Won IEEE Midwest Symp. on Circuits & Systems Student Paper Contest (2009) Recipient of Analog Devices Endowed Professorship (2006-2008) Advises graduate students in analog circuit design and energy systems. Leads research teams focused on next-generation power electronics and biomedical sensing technologies.

Saraju P. MohantyView profile

Professor

• Smart Electronic Systems
• Internet of Things (IoT)
• VLSI Design
• +7 more

Dr. Saraju P. Mohanty is a Professor in the Department of Computer Science and Engineering at the University of North Texas (UNT), where he leads the Smart Electronic Systems Laboratory (SESL). He holds honorary and adjunct positions at IIIT-Naya Raipur, MNIT Jaipur, and Oriental University, Indore, in India. Education: Ph.D. in Computer Science and Engineering, University of South Florida (USF), 2003 Masters in Systems Science and Automation (AI), Indian Institute of Science (IISc), 1999 B.E. in Electrical Engineering (Honors), College of Engineering and Technology, Bhubaneswar (OUAT), 1995 Dr. Mohanty's research is centered on Smart Electronic Systems, with a strong focus on IoT, VLSI, hardware security, and healthcare applications. His work integrates machine learning, embedded systems, and nanoelectronics to develop secure and efficient solutions for smart cities, agriculture, and medical devices. He has authored over 550 peer-reviewed publications and five books, including a PROSE Award-winning textbook. His recent publications reflect a growing emphasis on AI-driven solutions for synthetic media detection, smart farming, driver monitoring, and personalized health. These works demonstrate a trend toward intelligent, edge-based systems that leverage sensor data and lightweight AI for real-time decision-making. Scientific Awards and Honors: Fulbright Specialist Award (2021) IEEE Consumer Electronics Society Outstanding Service Award (2020) IEEE-CS-TCVLSI Distinguished Leadership Award (2018) PROSE Award for Best Textbook (2016) Top 2% Scientist globally (PLOS Biology, 2019–2022) Multiple Best Paper and Best Poster Awards UNT Toulouse Scholars Award (2016–2017) President’s Scout Award, India (1988) Dr. Mohanty has supervised 3 postdocs, 18 Ph.D. students, 29 M.S. theses, and over 40 undergraduate research projects. Eleven of his advisees have received outstanding student awards. He has received multiple UNT Provost’s Thank a Teacher and Honors Day recognitions. His research has been funded by NSF, SRC, US Air Force, NIDILRR, and Mission Innovation. He has held key editorial roles, including Editor-in-Chief of IEEE Consumer Electronics Magazine and founding EiC of IEEE VLSI Circuits and Systems Letter. He is actively involved in IEEE leadership and conference organization, serving on steering committees for IEEE-iSES, ISVLSI, and OCIT. Laboratories and Teams: He directs the Smart Electronic Systems Laboratory (SESL) at UNT, which focuses on cutting-edge research in IoT, edge computing, hardware security, and smart healthcare. The lab fosters interdisciplinary collaboration and has produced numerous award-winning student projects and publications.

Miguel Muñoz RojoView profile

Associate Professor

• Nanotechnology
• Nanoscale Thermal Transport
• Energy Conversion
• +8 more

Miguel Muñoz Rojo is an Associate Professor specializing in Thermal Engineering and Nanotechnology. He holds a PhD in Condensed Matter Physics and Nanotechnology from Universidad Autonoma de Madrid (2015), a Master's in Nanoscience and Molecular Nanotechnology (2013), and a Physics degree (2010). His research focuses on Nanoscale thermal transport Thermoelectrics 2D materials Memristive device engineering Atomic Force Microscopy (AFM) Thermal sensors . Recent work includes hybrid 2D-CMOS microchips, VO2-based resistive switching devices, and thermal management systems. His 193 citations for the 2023 Nature publication on memristive applications highlight his impact. Awarded the Leonardo da Vinci's Fellowship at the National Physical Laboratory (2010-2011), he served as examiner for MSc defenses and participated in conferences like the 2020 Device Research Conference. Collaborations span institutions in Spain, the U.S., and the Netherlands.

Don M.J. van ElstView profile

Researcher

• Spectral Sensing
• Near-Infrared Sensors
• Photodetector Engineering
• +4 more

Don M.J. van Elst is a Doctoral Candidate at Eindhoven University of Technology (TU/e) in the photonics and semiconductor nanophysics group (PSN) since November 2020. His research focuses on developing compact near-infrared spectral sensors with practical applications in agriculture, aiming to "put the power of spectral sensing in the hands of farmers" . His primary research areas include spectral sensing, photodetector engineering, resonant cavity design, and semiconductor nanophysics. His work contributes to UN Sustainable Development Goals through resource-efficient agricultural technologies. The fingerprint of his research shows strong expertise in Photodetector Engineering (100%), Resonant Cavity Engineering (89%), and Linewidth/Lithography (75%). His recent publications demonstrate a clear trajectory toward practical sensor applications, with emphasis on optimizing spectral resolution, extending sensor response capabilities, and integrating CMOS technology for field-deployable devices. His 2025 publications in ACS Photonics, ACS Nano, and Sensors journals highlight significant advances in picometer-level precision and material sensing capabilities. He actively contributes to multiple research projects including Fiber sensors for microchemistry (2024-2025), NIR spectral sensing for wearables (2023-2028), Synergia (2020-2027), and the PSN Research Centre for Integrated Nanophotonics (2014-2025). Van Elst completed both his bachelor's and master's degrees in Applied Physics at TU/e, with a master's internship at MIT's Spin Dynamics Laboratory. His graduation thesis was developed at Philips Research on Eindhoven's High Tech Campus.

• Computer Vision
• Machine Learning
• Image Processing
• +5 more

Dr. Xin Lin is a Professor at the School of Computer Science and Technology, University of Science and Technology of China in Hefei. With an extensive publication record spanning computer vision, machine learning, and artificial intelligence, Dr. Lin leads a research group focused on solving challenging problems in image processing, robotics, and wireless communications. His work bridges theoretical advancements with practical applications across healthcare, autonomous systems, and industrial manufacturing. Dr. Lin's research interests encompass computer vision, machine learning, image processing, and artificial intelligence, with particular expertise in image restoration, 3D object detection, and human pose estimation. His laboratory develops innovative approaches to handle multiple image degradations simultaneously and create lightweight, efficient vision systems suitable for real-world deployment. The research demonstrates strong interdisciplinary connections, applying computer vision techniques to medical imaging, satellite communications, and industrial IoT applications. Analysis of Dr. Lin's recent publications reveals a strong focus on multi-task learning approaches that address multiple image degradation problems simultaneously. His work shows increasing sophistication in handling complex real-world scenarios, from low-light conditions to rain interference, while maintaining computational efficiency. The research trajectory demonstrates a clear path from fundamental image processing techniques to practical applications in autonomous driving, healthcare, and industrial systems. Dr. Lin has received recognition for his contributions to the field through numerous publications in top-tier venues including CVPR, IEEE Transactions, and ACL. His work on image restoration, particularly the Dual Degradation Representation framework, has gained significant attention in the computer vision community. Dr. Lin actively supervises graduate students and collaborates with researchers worldwide. His laboratory works on cutting-edge projects involving digital twins for manufacturing, satellite communications, and medical imaging applications. Current research directions include developing more robust and efficient models for real-world deployment scenarios, with particular attention to resource-constrained environments.

• Artificial Vision
• CMOS Technology
• Image Recognition
• +3 more

Diego Cabello Ferrer is a Professor at the University of Santiago de Compostela’s Department of Electronics and Computing under the Faculty of Physics. His research focuses on advanced CMOS technologies, embedded vision systems, energy harvesting, and biomedical devices. He holds a PhD from the same university (1984), specializing in cybernetic systems and microprocessor-based analysis of animal behavior. Education: PhD in Electronics and Computing, University of Santiago de Compostela (1984). His work spans artificial vision algorithms, low-power CMOS sensor design, and micro-energy harvesting systems. Key contributions include vision sensors with in-pixel computation, ultra-low power voltage regulators for biomedical implants, and solar energy harvesting integrated circuits. His research emphasizes real-time image processing, edge computing for embedded systems, and hardware acceleration for neural networks. Publications highlight innovations in CMOS vision sensors for background subtraction, energy-efficient LDO designs, and hyperdimensional computing architectures. His teams have developed perpetual wireless sensor networks for environmental monitoring and Snail pest detection. Current efforts focus on in-memory computing with FeFETs and SRAM-based neural network accelerators. Labs/Teams: Center for Research in Intelligent Technologies (CITIUS). Grants & Collaborations: Projects include iCaveats (embedded vision architectures) and energy harvesting integration in biomedical devices. His work bridges theoretical signal processing with practical hardware implementations, addressing challenges in power efficiency, miniaturization, and real-time performance for embedded vision systems.

• High-Energy Physics Detectors
• Digital System Design (FPGAs)
• Sensor Systems and Networks
• +3 more

Roles & Affiliations: Kyriakis-Bitzaros Efstathios is a Lecturer in the Department of Electrical and Electronic Engineering at the University of West Attica, part of the School of Engineering. He is affiliated with the Electronics and Computer Technologies Laboratory (ECTLab) and teaches courses like Digital System Design and Operating Systems. His office is located at ZB206, Building Z, Ancient Eleonas Campus. Holds a PhD in Electrical Engineering and a Physics degree from the University of Patras (1994 and 1987, respectively). Research Interests: Focuses on high-energy physics detector electronics, FPGA-based digital systems, sensor array interfaces, energy harvesting for microcontrollers, and optoelectronic interconnects. His work includes contributions to the ATLAS experiment at CERN, including the New Small Wheel detector and MicroMegas electronics. Publications Overview: Over 30 publications spanning topics like high-luminosity LHC upgrades, reconfigurable embedded systems, and optoelectronic simulations. Recent work includes advancements in detector electronics for CERN experiments and energy-efficient sensor networks. Labs & Teams: Leads the ECTLab, focusing on electronics and computer technologies. Collaborates on projects like the ATLAS detector upgrades and smart sensor systems.

Anton SirotaView profile

Professor

• Neuroscience
• Neurophysiology
• Learning and Memory
• +5 more

Prof. Anton Sirota is a Professor and Research Group Leader at the LMU Division of Neurobiology and a member of the Bernstein Center for Computational Neuroscience (BCCN Munich). He leads the MSc Neuroscience Examination Committee and is a full member of the Graduate School of Neural and Behavioral Sciences (GSN). His research focuses on mechanisms of information representation and propagation in cortical networks, particularly between the neocortex and hippocampus during learning and sleep. He employs advanced techniques including multichannel electrophysiology, optogenetics, and virtual reality to study neural dynamics in behaving rats. His lab uses graphene-based sensors and multiplexed neural probes for high-resolution brain mapping. Research Interests: Neurophysiological mechanisms of learning and memory consolidation Cortico-hippocampal network dynamics Neural oscillations and their role in information transfer Development of neurotechnologies for brain activity recording (e.g., graphene sensors, SiNAPS probes) Role of respiration in coordinating neural networks Advising: Current advisee Arash Shahidi . Graduated students include Dr. Nicholas Del Grosso , Dr. Andrey Sobolev , Dr. Elena Itzcovich , and Fabián Štoček . Labs/Teams: Active in the Cognitive Neurophysiology Lab , leveraging cutting-edge tools like multishank silicon probes and optogenetic modulation. Collaborates on projects involving virtual reality systems for rodent behavior studies and computational modeling of neural networks.

Rebecca TaylorView profile

Professor

• DNA nanotechnology
• Advanced manufacturing
• Biomechanics
• +12 more

Rebecca Taylor is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering, with courtesy appointments in Biomedical Engineering and Electrical and Computer Engineering. Her research spans DNA nanotechnology, advanced manufacturing, and bio-inspired micro/nanosystems, focusing on integrating self-assembly with top-down microfabrication. 2013 Ph.D. in Mechanical Engineering (minor in Bioengineering), Stanford University 2010 MS in Mechanical Engineering, Stanford University 2001 BS in Mechanical Engineering with Robotics Certificate, Princeton University Her research centers on: (1) DNA nanotechnology for molecular and cellular mechanobiology (AFOSR YIP, NIH R21), (2) bio-inspired materials using gammaPNA (NSF CAREER), and (3) biomanufacturing with DNA robotics. She also develops workforce training tools like voice assistants for skill mastery. Recent publications highlight DNA microswimmers, compliance in colloidal assemblies, and generative design for origami nanostructures. Awards include the NSF CAREER Award and Ansys Career Development Chair. She advises interdisciplinary students and leads the Microsystems and Mechanobiology Lab, collaborating with Biomedical Engineering, Chemistry, and Cardiovascular Medicine teams. NSF CAREER Award Ansys Career Development Chair Lab members include postdocs (Grace Rohaley, Sarah Weintraub), Ph.D. students (Taryn Imamura, Vismaya Walawalkar), and undergraduates (Irene Yap). She teaches courses like Nanoscale Manufacturing Using Structural DNA Nanotechnology and Modern Manufacturing in Steeltown , emphasizing design and automation.

Jun OHTAView profile

Professor

• Smart CMOS Image Sensors
• Biomedical Applications
• Retinal Prosthetic Devices
• +3 more

Dr. Jun OHTA is the Executive Director and Vice President of the Nara Institute of Science and Technology (NAIST), Japan, and a Professor in the Division of Materials Science at NAIST's Graduate School of Science and Technology. He holds B.E., M.E., and Dr. Eng. degrees in applied physics from the University of Tokyo (1981, 1983, 1992). His career includes roles at Mitsubishi Electric Corporation (1983–1992) and a visiting scholar position at the University of Colorado Boulder (1992–1993). His research focuses on smart CMOS image sensors for biomedical applications and retinal prosthetic devices. He has authored a book, numerous book chapters, and over 250 peer-reviewed articles. Dr. Ohta serves on editorial boards of IEEE Sensors Journal, IEEE Trans. BioCAS, and others. He co-chaired the 2019 IEEE BioCAS conference and was an IEEE Distinguished Lecturer (2018–19). Education: B.E. in Applied Physics, University of Tokyo (1981) M.E. in Applied Physics, University of Tokyo (1983) Dr. Eng. in Applied Physics, University of Tokyo (1992) His research emphasizes interdisciplinary applications of materials science and electronics, particularly in biomedical engineering. He actively contributes to technical committees like ISSCC and VLSI Symposium, fostering advancements in sensor technologies and prosthetic devices.

• Biomedical Engineering
• Analytical Chemistry
• Clinical Sciences
• +3 more

Dr. Sally Gowers is a Research Associate in the Department of Bioengineering at Imperial College London's Faculty of Engineering. She specializes in developing advanced biosensors and analytical tools for real-time clinical monitoring and biomedical applications. Her affiliations include the Biomedical Sensors group, the Centre for Antimicrobial Optimisation, and the Ovarian Cancer Tumour Heterogeneity and Bioengineering initiative. Her research focuses on integrating microfluidic, nanotechnology, and electrochemical methods into wearable and implantable devices. Key areas include biosensors for metabolic monitoring (e.g., glucose/lactate), neurochemical analysis in traumatic brain injury, and antibiotic quantification. She has pioneered microneedle-based devices and microdialysis systems for applications ranging from organ transplantation to sports medicine. Recent work emphasizes clinical translation, such as Phase I trials for lactate-monitoring microneedle patches and validation of real-time kidney viability assessment during transplantation. Her innovations bridge engineering and medicine, addressing critical needs in patient monitoring, organ preservation, and antimicrobial resistance. Dr. Gowers collaborates across disciplines, leveraging Imperial’s engineering and clinical expertise. Her lab develops both hardware (e.g., 3D-printed microfluidic devices) and software systems for data analysis, aiming to improve diagnostic accuracy and patient outcomes through continuous, minimally invasive monitoring.

Kip CoonleyView profile

Academic

• Electrical Engineering
• Microelectronics
• Thermoelectric Materials
• +4 more

Kip Coonley, Ph.D., is an Assistant Professor of the Practice at Duke University, holding joint appointments in the Thomas Lord Department of Mechanical Engineering and Materials Science and the Department of Electrical and Computer Engineering. He has been at Duke since completing his Ph.D. there in 2023, following earlier degrees from Bates College (B.S., 1997) and Dartmouth College (M.S., 1999). His work focuses on interdisciplinary engineering education, with emphases on microelectronics, energy harvesting systems, and innovative laboratory curriculum design. He has pioneered hands-on learning initiatives like the BYOE (Build Your Own Electronics) program and contributed to Duke’s ECE curriculum redesign, emphasizing integrated sensing and information processing themes. His research also explores electrostatic oscillators, thermoelectric materials, and RF data link systems. Over 25 years, Dr. Coonley has taught 10+ courses, including foundational labs in electrical fundamentals, signals and systems, and microelectronic devices. His 40+ publications span educational pedagogy, device physics, and engineering systems, with notable contributions to ASEE conferences and IEEE Transactions on Education . He collaborates extensively on NSF-funded curriculum projects and maintains active partnerships with industry for applied research.

Jun-Chau ChienView profile

Assistant Professor

• Biosystems & Computational Biology
• Bioelectronics
• Microfluidics
• +7 more

Jun-Chau Chien is an Assistant Professor of Electrical Engineering and Computer Science at the University of California, Berkeley, and holds the Weber Family Engineering Faculty Fellowship. He is affiliated with the Berkeley Sensor & Actuator Center (BSAC) and the Berkeley Wireless Research Center (BWRC). His research bridges integrated circuits with bio- and quantum technologies, focusing on biosensors, molecular engineering, and mm-wave ICs for biomedical and quantum applications. Education: B.S. and M.S., National Taiwan University Ph.D. in Electrical Engineering, UC Berkeley (2015) Postdoctoral Training, Stanford University (2016–2017) Prior Experience: Research Engineer, Stanford EE (2017–2021) Assistant Professor, National Taiwan University Industrial roles at Xilinx, InvenSense, LifeSignals, and INanobio Research Interests: Analog/mixed-signal IC design for biomedical applications Bioelectronics and implantable/ wearable sensors RF/mm-wave circuits for quantum interfaces and medical imaging CMOS-microfluidics integration for point-of-care diagnostics Advanced calibration techniques for high-frequency devices Awards: 2022 IEEE BioCAS Best Paper Award 2019 IEEE CICC Outstanding Paper Award NSF CAREER Award (2025) MTT-S Graduate Fellowship (2014) Lab & Outreach: Chien Lab focuses on bio-IC convergence and quantum interfaces Develops wearable/implantable biosensors and mm-wave imagers Hosts community outreach programs for junior high/high school students He teaches EE 194 and EE 290 on integrated circuit testing and is actively involved in ISSCC technical committees.