Tim Dallas is an Associate Dean of the Graduate School and Professor of Electrical and Computer Engineering at Texas Tech University's Whitacre College of Engineering. His roles include overseeing graduate fellowship programs and developing innovative MEMS-based educational tools. Dr. Dallas is renowned for co-creating the Solar-Powered Digital Classroom-in-a-Box, deployed in off-the-grid African regions using pico projectors. Co-founded Class on a Chip, Inc. (2008) for commercializing micro-experimental devices Established the Technology Start-up Lab (2014) in partnership with business classes Principal Investigator for NSF-REU, CCLI, and S-STEM grants His research spans renewable energy systems, biometric authentication, and interdisciplinary learning. Dr. Dallas has secured funding from Keck and Welch Foundations for MEMS-based education technologies and served as Associate Editor for IEEE Transactions on Education. He is a Senior Member of IEEE and affiliated with ASEE and SPIE.
Alan Mantooth is a Distinguished Professor holding the Twenty-First Century Research Leadership Chair in Engineering within the Department of Electrical Engineering at the University of Arkansas, Fayetteville. He serves as Director of the National Center for Reliable Electric Power Transmission (NCREPT), Executive Director for GRAPES (NSF I/UCRC) and SEEDS (DoE Center), and Deputy Director of the NSF Engineering Research Center for Power Optimization of Electro-Thermal Systems (POETS). His educational background includes: B.S. in Electrical Engineering, University of Arkansas M.S. in Electrical Engineering, University of Arkansas Ph.D. in Electrical Engineering, Georgia Institute of Technology Dr. Mantooth's research centers on analog/mixed-signal IC design, power electronics CAD, and semiconductor device modeling with emphasis on harsh-environment applications. His pioneering work in silicon carbide (SiC) and gallium nitride (GaN) power systems has enabled high-temperature operation for electric vehicles and renewable energy infrastructure, significantly advancing reliability in extreme conditions. His 2025 publications reveal strong trends toward AI-driven power electronics (e.g., SolarFormer++ for PV profiling), wide-bandgap device modeling (β-Ga2O3, SiC), and innovative packaging solutions. Key themes include reliability engineering for extreme environments, multi-physics optimization, and explainable AI for safety-critical power systems. Major scientific recognition includes: IEEE Fellow (2009) for power electronic device modeling Three R&D 100 Awards (2009, 2014, 2016) for SiC power modules IEEE Power Electronics Society Technical Achievement Award (2019) Multiple university teaching/research awards including SEC Faculty Achievement Award (2015) As an exceptional mentor (UA Outstanding Mentor 2006-2008), he co-founded Lynguent and Ozark Integrated Circuits. His centers NCREPT, GRAPES, and SEEDS have secured major funding from NSF, DoE, and industry partners, supporting over 350 refereed publications and numerous patents. Current research focuses on AI-enhanced power electronics, recyclable packaging, and next-generation wide-bandgap device characterization. He leads the NCREPT test facility and multi-institutional teams developing grid-connected power electronic systems, secure energy delivery architectures, and thermal management solutions for high-power-density applications, with direct impact on electric transportation and renewable energy integration.
Dr. Yew Weng Kean is an Assistant Professor in the Department of Electrical Engineering at Heriot-Watt University Malaysia, part of the School of Engineering & Physical Sciences. He holds a Ph.D. in Electrical Engineering from Universiti Tenaga Nasional, where his doctoral work focused on "Design of an AC-coupled stand-alone hybrid renewable energy system with an improved control strategy". His research expertise encompasses microgrids, renewable energy systems, smart grids, and AI-driven solutions for energy management. He actively contributes to interdisciplinary projects involving material science, computer vision, and sustainable technologies. His research interests span microgrid optimization, stand-alone hybrid systems, solar PV integration, energy storage technologies, and artificial intelligence applications in energy sectors. He has authored over 24 peer-reviewed publications, with recent work focusing on defect detection in wind turbine blades, advanced control mechanisms for multi-agent systems, and sustainable bio-hydrogen production. Dr. Yew’s articles highlight trends in combining AI with renewable energy systems, such as deep learning models for fault diagnosis in photovoltaic arrays and novel approaches to wind turbine blade inspection via aerial imagery. His work also addresses challenges in material science, including heat treatment effects on aluminum alloys and acoustic properties of natural fibers. He currently supervises research in energy systems, smart grids, and sustainable materials, and collaborates on global energy education initiatives. His affiliations include roles in university-led sustainability projects and contributions to IEEE-related conferences.
Dong Chen is an Associate Professor in the Department of Computer Science at the Colorado School of Mines. His research focuses on building data-driven experimental systems in Cyber-Physical Systems (CPS), IoT, Embedded AI, and Embodied AI, with applications in smart devices, homes, cities, and renewable energy systems. He leads the Next Generation Cyber-Physical Systems Laboratory (CPSLab), emphasizing open-source systems and datasets. Dr. Chen holds PhDs in Electrical and Computer Engineering (2018, University of Massachusetts Amherst) and Computer Science (2014, Northeastern University). His work addresses security, privacy, sustainability, and efficiency in smart environments. Notable contributions include SolarFinder, SolarTrader, PrivacyGuard, and VoiceAttack, which tackle challenges in IoT privacy, energy trading, and adversarial attacks. He received the NSF CAREER Award (2023) and is a member of Sigma Xi, ACM, AAAI, and IEEE. His research spans system design, AI applications, and cross-cutting domains like solar energy modeling and edge computing. Current projects include AgileDART (edge stream processing) and SolarDetector (satellite-based PV array identification). Advising and collaborations: Dr. Chen seeks PhD and undergraduate students with strong CS/EE backgrounds. His lab focuses on CPS/IoT security, energy systems, and AI-driven solutions. He has published extensively on topics ranging from smart grid optimization to adversarial machine learning.
Kartik Ariyur is a Lecturer in the Department of Mechanical Engineering at Purdue University, based remotely. His research focuses on autonomous systems, control systems, sensor technology, and energy systems. His work spans applications in robotics, navigation, and environmental sustainability. Key projects include improving UAV navigation accuracy, developing LiDAR-based traffic monitoring systems, and optimizing wireless networks through adaptive control techniques. Education details are not explicitly listed, but his publications suggest expertise in control systems, robotics, and interdisciplinary engineering. His research interests emphasize practical applications of advanced control theory in real-world systems, including autonomous vehicles and renewable energy systems. Recent publications highlight contributions to geolocation using celestial and magnetic sensing, multi-object tracking with LiDAR, and adaptive control algorithms for hypersonic vehicles. While no specific awards are listed, his extensive publication record reflects active engagement in cutting-edge engineering research. Advising and grants: No formal advisees are listed, but his research collaborations likely involve graduate students and interdisciplinary teams. His work aligns with initiatives in smart infrastructure, autonomous systems, and sustainable energy. No specific grants are mentioned, but his projects suggest funding from sources like the USDOT Regional University Transportation Center. Research activities include contributions to labs focused on autonomous systems, sensor networks, and control systems engineering. His work often integrates hardware and software solutions for real-world challenges in transportation and environmental monitoring.
Tamas Kerekes is an Associate Professor at AAU Energy, part of the Faculty of Engineering and Science at Aalborg University. His work focuses on power electronics, photovoltaic systems, and grid integration. He has extensive teaching experience in MSc courses such as Control of Electrical Drives and Converters, Grid Interactive PV Inverters, and PhD/Industrial courses including Photovoltaic Power Systems and Power Electronics for Renewable Energy Sources. Education: He holds a PhD in Electrical Engineering (Analysis and Modeling of Transformerless Photovoltaic Inverter Systems) from Aalborg University (2005–2008). Research Interests: His expertise spans photovoltaic systems, energy storage, and power electronics for renewable integration. He leads and participates in projects like TilePlus (solar roof tiles), ECoGrif (grid-friendly power converters), and MMC Advanced Control with AI-based Grid Stability Assessment. His work emphasizes condition monitoring, decentralized algorithms, and cost-effective energy management strategies. Projects & Grants: He has been involved in 15+ projects funded by Innovation Fund Denmark, European Commission, and ERASMUS+. Notable contributions include the development of solar tile solutions, hybrid energy storage systems, and grid-friendly converter technologies. Labs/Teams: Leads the TilePlus project team for solar energy collection and collaborates on advanced control systems for microgrids and power converters. His research group focuses on experimental validation and real-world implementation of renewable energy solutions.
Dr. Yuanjing Lin is an Assistant Professor at the School of Microelectronics, Southern University of Science and Technology. Her research centers on nanostructured materials and fabrication techniques for printable/wearable electrochemical sensors and energy storage devices, with applications in self-powered systems, health/environmental monitoring, and intelligent robotics. Ph.D., Electronic and Computer Engineering, Hong Kong University of Science and Technology (2014–2018) Visiting Research Student, UC Berkeley (2018) B.Eng., Electronic Science and Technology, Nankai University (2010–2014) Her work bridges flexible electronics, self-powered sensing, and digital healthcare. She has contributed to over 50 publications in top journals like Nature , Nature Nanotechnology , and Science Advances , focusing on wearable biosensors, textile electronics, and energy storage systems. Articles highlight advancements in printable photonic materials, sweat-activated micro-batteries, and self-powered sensing systems, with trends in flexible micro/nano electronics, biomedical applications, and sustainable energy solutions. IAAM Fellow (2025) Nano Letters Early Career Board (2025) Nanoscale Emerging Investigators (2024) SUSTech Excellent Teaching Award (2023) iCanX Summit Best Paper Award (2022) Dr. Lin actively recruits graduate/postdoctoral researchers in sensors, flexible electronics, and biomedical engineering. She serves as Associate Editor for Frontiers in Nanotechnology and editorial board member for Nano Letters , Biosensors , and FlexMat .
Juan Antonio Leñero Bardallo is a Professor at the University of Seville, Faculty of Physics, Department of Electronics and Electromagnetism. His research focuses on bio-inspired microelectronics, event-driven vision sensors, and CMOS integration techniques. Research Group: MICROELECTRÓNICA ANALÓGICA Y DE SEÑAL MIXTA Key Projects: SAMANTA2 (robotic vision), CAVIAR (event-based vision), VULCANO (event-driven imaging) His work spans asynchronous image sensors, thermography for medical diagnostics, stacked diodes for energy harvesting, and neuromorphic engineering. Recent publications highlight low-power sun sensors, self-powered imaging systems, and thermographic applications in dermatology. He has contributed to books on analog electronics and radiation detection. Patents include solar position sensors and electron energy detectors for scanning electron microscopy. His teaching subjects cover experimental techniques, integrated sensor design, and bio-inspired algorithms.
Prof. Dr. Osman Kukrer is a full-time faculty member at Eastern Mediterranean University (EMU), Faculty of Engineering, Department of Electrical and Electronics Engineering. He has been actively supervising graduate students in power electronics, control systems, and renewable energy integration since the 1990s. His research spans advanced power conversion topologies, including quasi-Z-source inverters multilevel converters active power filters grid-connected systems adaptive beamforming algorithms electric vehicle grid integration Notable contributions include the EMU Publication Citation Award (2017) and extensive supervision of 41 graduate theses, with research interests aligning with modern energy systems and signal processing techniques.
Xiangyu Chen is a Lecturer at the Department of Civil, Environmental and Geomatic Engineering, ETH Zürich. He is affiliated with the Luftqualität u. Partikeltechnolog (Air Quality and Particle Technology) research group. His contact information includes the email xiangchen@ethz.ch and is located at HIF D 27.1, Laura-Hezner-Weg 7, 8093 Zürich, Switzerland. His research focuses on nanotechnology and materials science applied to environmental engineering, biomedical diagnostics, and energy systems. Key areas include: Development of advanced sensors for air quality and biomedical applications Catalytic material design for energy efficiency Biomedical nanomaterials for targeted drug delivery and imaging Xiangyu Chen’s recent publications (2021–2024) highlight innovations in nanoparticle-based technologies, including 3D metal-organic frameworks for energy systems, deformable organosilica nanoparticles for MRI contrast agents, and real-time in vivo imaging techniques for glioma targeting. His work bridges theoretical material science with practical sensor and medical applications. No scientific awards or grants are explicitly mentioned. He mentors students within his teaching role but no specific advisees are listed. His affiliation with the Air Quality and Particle Technology group aligns with environmental nanotechnology research.
Peifen Zhu is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri College of Engineering. She previously served as an Assistant Professor at the University of Tulsa's Department of Physics and Engineering Physics. Her research focuses on photonics, optoelectronic devices, and semiconductor nanostructures for energy efficiency and renewable energy applications. She has received prestigious awards, including the NSF CAREER Award and the Zelimir Schmidt Award for Outstanding Researcher. Education: Ph.D. in Electrical Engineering from Lehigh University (2015). Research interests include solid-state lighting, solar cells, thermoelectricity, and photocatalytic CO₂ reduction. Her lab emphasizes interdisciplinary approaches, welcoming students from Physics, Materials Science, and Chemical Engineering. Key applications include perovskites, quantum dots, and metal-organic frameworks. Notable contributions include 3D-printed lead-free perovskite-based LEDs and advancements in material stability. She actively explores reducing environmental impacts through cost-effective manufacturing and sustainable optoelectronic materials. Awards: NSF CAREER Award (2020), Zelimir Schmidt Award (2022) Labs: Semiconductor Device Laboratories in Naka and Lafferre Halls Future Work: Developing lead-free alternatives and scalable lighting solutions
C. Kyle Renshaw is a Professor of Optics and Photonics at the University of Central Florida (UCF), affiliated with the Department of Electrical Engineering (ECE) within the College of Engineering and Computer Science (CECS). He holds a PhD and MS from the University of Michigan and an undergraduate degree from Cornell University. His research focuses on organic optoelectronics, thin-film semiconductors, sensor arrays, photovoltaics, and imaging systems, particularly in applications like flexible electronics and optoelectronic devices. Dr. Renshaw leads the Thin-Film Optoelectronics (TFO) Group, which develops materials and fabrication techniques for large-area devices such as solar cells, displays, and sensors. His work spans hybrid metasurface-refractive optics, drone-based imaging systems, and multispectral imaging technologies. Notable contributions include advancements in infrared imaging, free-space optical communications, and sensor optimization for geolocation. His recent research highlights include experimental comparisons of active imaging modes, Gaussian decomposition modeling for hybrid lenses, and evaluation of Doppler wind lidar for aviation safety. Dr. Renshaw has been recognized with the 2018 AFRL Summer Faculty Fellowship. His work bridges fundamental optics research with practical applications in defense, environmental monitoring, and aerospace systems.
Associate Professor Rifai Chai is a faculty member in the Department of Biomedical Engineering at the School of Engineering, Swinburne University of Technology. He serves as the Academic Director (Partnerships), reflecting his leadership in academic-industry collaboration. His research focuses on the intersection of biomedical engineering and artificial intelligence, with applications in brain-computer interfaces, medical technologies, robotics, and embedded systems. University: Swinburne University of Technology School: School of Engineering Department: Biomedical Engineering Position: Associate Professor Email: rchai@swin.edu.au His educational and professional background includes over a decade of experience in product development in hardware, firmware, and software design in Indonesia and Australia from 2000 to 2011. His research interests are extensive and include: Artificial Intelligence and Machine Learning Brain-Computer Interfaces Medical Device Design Assistive Technology (e.g., smart wheelchairs, exoskeletons) Cognitive Fatigue and Workload Monitoring Back Pain Assessment and Rehabilitation Embedded Systems EEG and Physiological Signal Processing Rifai Chai's recent publications demonstrate a strong focus on AI-driven healthcare solutions. His work spans advanced computational intelligence in medical imaging (e.g., lung cancer and thyroid cancer detection), EEG-based systems for driver fatigue and emotion classification, rehabilitation technologies using exoskeletons, and cybersecurity in industrial IoT. He employs deep learning, hybrid models (e.g., MLP-BiLSTM), and advanced signal processing techniques to solve real-world biomedical problems. His research consistently targets practical, non-invasive, and real-time applications in clinical and industrial settings. His scientific contributions include numerous high-impact publications in journals such as IEEE Access, Sensors, and Medical & Biological Engineering & Computing, as well as book chapters with Elsevier and Springer. He has secured multiple research grants from industry partners and the Australian Research Council, supporting projects in breast electromagnetic scanning, solar-powered charging poles, and haptically-enabled motion simulation. Rifai Chai actively supervises PhD and Master’s students, with current HDR projects covering areas such as brain-computer interfaces for prosthetics, cognitive workload monitoring, distracted driving detection, and AI in medical imaging. He leads a multidisciplinary research team working at the forefront of biomedical innovation. His lab integrates AI, robotics, and physiological sensing to develop technologies that improve health outcomes and human performance.
Svetlana Neretina is a Professor in the Department of Aerospace and Mechanical Engineering and a Concurrent Professor in the Department of Chemistry & Biochemistry at the University of Notre Dame, where she has been on faculty since 2022. She previously served as an Associate Professor at Notre Dame (2016–2022) and Assistant Professor at Temple University (2009–2016). Her research focuses on the synthesis and fabrication of noble metal nanostructures for applications in catalysis, sensing, and energy. Key interests include plasmonics, nanofabrication techniques such as nanoimprint lithography and dynamic templating, photocatalysis for green chemical synthesis, hydrogen generation, and the development of in situ monitoring tools for scalable manufacturing. Her work bridges materials science, chemistry, and mechanical engineering. Her recent publications demonstrate a strong trend in advanced nanomaterial design, including core-satellite assemblies, epitaxially aligned arrays, and functional oxide nanoshells. These works span high-impact journals like ACS Nano , Nanoscale , and Journal of Physical Chemistry C , emphasizing precision fabrication and real-world applicability in energy and sensing. NSF CAREER Award (2011) ACS Pride Merck Graduate Student Award (mentored student, 2025) Multiple Outstanding Graduate Student Teacher Awards (mentored students, 2020–2023) NDIIF Best Publication Image Award (mentored student, 2023) Regional and State Science Fair Awards for high school interns (2020, 2023) Dr. Neretina actively mentors a large group of PhD students and undergraduate researchers, many of whom have gone on to successful careers in academia and industry. Her lab, the Nanomaterial Fabrication Research Laboratory, has secured ongoing funding to support graduate researchers and develop new instrumentation. She emphasizes scalable, manufacturable approaches to nanomaterial synthesis, aligning research with industrial needs. The lab frequently collaborates with external groups, such as Professor Eric Borguet at Temple University, on plasmonic sensing applications. The Nanomaterial Fabrication Research Laboratory develops and applies innovative techniques like dynamic templating and hybrid nanoimprint templating to fabricate periodic arrays of complex nanostructures. The lab is equipped with custom-built instrumentation and supports interdisciplinary research at the intersection of materials, chemistry, and engineering.
Ying Fu is a Professor at Halmstad University's School of Information Technology, where he leads research in applied electromagnetics and photophysics. He belongs to the 'Photonics, Electronics, and Nanotechnology' research group and teaches undergraduate physics courses (FY4006 - Physics 1: Mechanics and Waves, FY4007 - Physics 2: Thermodynamics and Modern Physics) and graduate courses (EL8003 - Semiconductor Devices, EL8010 - Applied Electromagnetics). His research focuses on developing novel metamaterials and nanobiophotonic systems for applications spanning photodetection, solar energy conversion, biomedical sensing, and communications across visible to microwave spectra. Methodologies combine multi-scale theoretical modeling (quantum chemistry, solid-state physics, FDTD, machine learning) with experimental synthesis and characterization of quantum dots (CdSe-CdS/ZnS, ZnO, 3C-SiC), graphene, and metallic microstructures. Publication analysis reveals consistent focus on quantum nanostructures, with recent work (2021-2025) emphasizing infrared photodetector design, graphene metasurfaces, and memristive devices. Earlier contributions (2010-2018) established foundational work in quantum dot solar cells, nanocrystal photophysics, and semiconductor device engineering. His 230+ publications demonstrate interdisciplinary integration of materials science, photonics, and electronic engineering. He leads the 'Photonics, Electronics, and Nanotechnology' research team at Halmstad University, where experimental and computational facilities support investigations in nanomaterial synthesis, optical characterization, and device prototyping.
