Dr. Alex Stumpf is a Lecturer in the Department of Engineering at La Trobe University, specializing in electronic engineering and automation. He leads research in robotics and sensor technology applications for infrastructure maintenance, including sewer profiling robots and concrete condition assessment systems. His work has received the 2017 National AIIA iAwards for innovation in active RFID tracking devices. Education: BEng(Hons) from Monash University PhD in Electric Drives and Motor Control from La Trobe University Research focuses on automation solutions for civil infrastructure challenges, combining robotics with sensor technology. Key projects include sewer maintenance robots and remote water quality monitoring systems. Recent publications emphasize sensor integration and structural assessment techniques. Grants and Collaborations: Robotic Based Sewer Pipe Condition Assessment (SmartCrete CRC, 2024–2027) Power Supply Module Project 2 (Open Oceans Pty Ltd, 2023) Cover meter integration into 3PR+ (South East Water Corporation, 2022–2023) Labs/Groups: Active member of the RAMPS laboratory group and the Centre for Technology Infusion.
Alpay DORUK is a Lecturer and the Head of the Cyber Security Department at the Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University. Previously, he served as a Lecturer at Tekirdag Namik Kemal University (2011–2020) and a Research Assistant at Izmir Institute of High Technology (1999–2011). His expertise spans Information Security, IoT, and Embedded Systems, with a focus on ontology engineering, machine learning applications, and sensor networks. Research highlights include developing ontology-based frameworks for IoT sensors and web services, designing wheelchair control systems using image processing, and analyzing superconductor properties via SEM image statistics. He has supervised over a dozen academic projects and one Master’s thesis on facial movement tracking using image processing. Active in academic administration, he coordinated Erasmus and Farabi programs and led departmental initiatives as Department Head. His refereeing roles include peer review for journals like Turkish Journal of Electrical Engineering and conferences such as ICECENG. He has authored/co-authored two books on cybersecurity and computer engineering, and contributed to international projects like the Sayısal Kontrol Sistemleri software development (2006–2010). Recent work emphasizes IoT device monitoring, blockchain-inspired data structures, and machine learning for automotive efficiency analysis. His teaching spans operating systems, software engineering, and agile development, reflecting his blend of theoretical and applied expertise.
Danijela Efnusheva is an Assistant Professor at the Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, Macedonia. She leads the Computer Technologies and Engineering Lab since 2020 and has held academic positions since 2009. Her expertise spans computer engineering, network security, FPGA design, and machine learning applications. Education: Ph.D. in Technical Sciences (2017), Master of Electrical Engineering (2010), and Bachelor's in Informatics (2008), all from FEEIT, Skopje. Research focuses on FPGA-based hardware architectures, network security solutions, IoT systems, and machine learning applications in healthcare and finance. Key projects include the UbiLAB remote laboratory framework and FPGA implementations for network packet processing. Publications emphasize network security, embedded systems, and machine learning, with contributions to conferences like ETAI and Applied Innovations in IT. She coordinates projects such as the OBD cloud platform and has expertise in remote lab infrastructure and IoT monitoring systems.
Richard Kavanagh is a Senior Lecturer at University College Cork (UCC) in the School of Electrical & Electronic Engineering, directing the Mechatronics Research Laboratory. He holds a PhD from UCC and is a Chartered Engineer listed in Marquis Who's Who in Science and Engineering. His research focuses on sensor design, advanced signal processing, quantization effects analysis, servosystem control, and VR-based mechatronics education. He has held roles including Senior Research Scientist at PEI Technologies and Senior Project Engineer at SPS Laboratories. Education: BEng (Electrical) 1984, MEngSc 1985, PhD 1998 – all from UCC. Professional affiliations include Senior Member of IEEE (1994-1999) and membership in ASEE and IEI. Research interests emphasize theoretical and practical advancements in digital signal processing for quantized signals, nonuniform sampling, and mechatronics visualization. His work includes novel algorithms for velocity measurement, FIR filter design for quantized signals, and compliant mechanism synthesis. Publications span over three decades, with key contributions in IEEE Transactions, ASME, and international conferences. He serves as Associate Editor for IEEE Signal Processing Letters and has contributed to projects like the Blue City initiative addressing urban hydrology and sea level rise in Cork. Teaching includes modules on Industrial Automation and Robotics. His lab develops test systems for complex industrial processes and mechatronic visualization tools.
Waleed Meleis is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University and serves as Vice Provost for Graduate Education. He holds an MS and PhD from the University of Michigan and a BSE from Princeton University. His primary research focuses on combinatorial optimization, machine learning, assistive technology, and large-scale social experimentation platforms like Volunteer Science. He pioneered the Enabling Engineering student group, which designs assistive devices for individuals with disabilities, supported by over $350K in external funding. His leadership roles include Interim Vice Provost for Oakland Campus and Associate Dean for Graduate Education, driving significant enrollment growth and program development. Notable awards include multiple Martin W. Essigmann Teaching Awards and the Eta Kappa Nu Professor of the Year Award. His work bridges technical innovation with societal impact, particularly in healthcare and education. Education: PhD, Computer Science and Engineering, University of Michigan, 1996 MS, Computer Science and Engineering, University of Michigan, 1992 BSE, Electrical Engineering, Princeton University, 1990 Research: Combines algorithm design for engineering problems (e.g., cloud computing, spectrum management), social science experimentation platforms, and assistive technology development for rehabilitation. Leadership: Vice Provost for Graduate Education since 2023 Interim Vice Provost and Academic Lead for Oakland Campus (2023–2024) Associate Dean for Graduate Education (2020–2022) Awards: Recognized for teaching excellence and innovation in education across multiple years, including the 2010 Eta Kappa Nu Professor of the Year Award. Publications: Over 50 peer-reviewed papers in areas spanning reinforcement learning, distributed systems, and biomedical engineering. Grants: Secured funding from NSF, Army Research Lab, and private foundations for projects including Volunteer Science and Enabling Engineering initiatives. His interdisciplinary Dialogue of Civilizations course explores scientific revolutions, blending historical and computational perspectives. Enabling Engineering has delivered 60+ projects with clinical partners, emphasizing inclusive engineering education.
Ritske Jong is a Professor in Experimental Psychology at the Faculty of Behavioural and Social Sciences. His research utilizes electroencephalography (EEG) to explore cognitive mechanisms underlying attention, task-switching, and time perception. He investigates neural correlates of performance variability and decision-making under cognitive constraints. Research Focus: Jong's work spans attentional bias, temporal processing, and neurocognitive modeling. Key themes include EEG signatures of time perception, resit exam effects on learning investment, and implicit temporal regularities. His lab employs behavioral experiments and neuroimaging to dissect cognitive control mechanisms. Publication Trends: Recent articles (2017–2022) cluster in three domains: 1) EEG-informed temporal cognition studies, 2) attentional processing in learning environments, and 3) computational modeling of cognitive tasks. Cross-disciplinary collaborations extend to healthcare technology and educational psychology.
Adrian Wills is an Associate Professor in the School of Engineering (Mechatronics) at the University of Newcastle, Australia. He leads the Mechatronics Engineering program and holds academic appointments since July 2015. His research focuses on Bayesian estimation, system identification, and control engineering, with applications in robotics and mechatronics. Wills has collaborated with institutions globally, including Linköping University, Uppsala University, and the University of British Columbia. He earned his B.E. (Elec.) and Ph.D. from the University of Newcastle in 1999 and 2003, respectively. Teaching expertise includes delivering advanced courses in estimation and optimization within the Mechatronics Engineering program. Administrative roles include program convenor for Mechatronics Engineering. Research highlights include contributions to state-space models, nonlinear system identification, and model predictive control. His work bridges theoretical advancements with practical applications in engineering systems and healthcare. Key collaborations involve Professors Lennart Ljung, Thomas Schön, and Bhushan Gopaluni, among others. His technical contributions span MATLAB toolboxes (e.g., UNIT), FPGA/ASIC implementations for control systems, and interdisciplinary projects in strain measurement using neutron diffraction.
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.
Dr. Rohit Dua is an Associate Teaching Professor at Missouri University of Science and Technology (Missouri S&T), where he teaches in the Cooperative Engineering Program with Missouri State University. He holds a PhD and MS in Electrical Engineering from Missouri S&T and a BE in Electronics & Telecommunications from the University of Pune, India. Previously, he served as an Assistant Professor at New York Institute of Technology. His office is located at Missouri State University’s Springfield campus. Research Focus: Dr. Dua specializes in Smart Embedded Sensing Systems, Artificial Neural Networks, Optoelectronic Sensors, and their applications in biomedical/energy engineering. He actively integrates engineering education innovation into his research, developing experiential learning tools for K-12 and undergraduate students. Awards & Honors: 2023 ASEE Midwest Section Outstanding Service Award 2015 ASEE Zone III Conference: 1st Place Student Poster 2014 Missouri S&T Experiential Learning Award 2014 ASEE Midwest Section: 3rd Place Undergraduate Poster 2007 NYIT Faculty Scholars Award Educational Initiatives: He leads experiential projects including the Embedded Systems Club, FPGA-based synthesizers, K-12 logic laboratories, and microprocessor design tools. He received grants for student projects (e.g., OURE grants) and developed courses like Fun With Electronics . He frequently chairs ASEE Midwest Conference programs.
Dilan Senaratne is a Lecturer in the School of Electrical Engineering and Computer Science at Oregon State University, part of the College of Engineering. He joined the faculty in 2023 after completing his Ph.D. in Electrical and Computer Engineering with a minor in Artificial Intelligence at the same institution (2023), following an M.S. (2020) and B.Sc. (Honors, University of Moratuwa, Sri Lanka, 2015). His teaching portfolio includes courses on electrical fundamentals, power system analysis, protection, and smart grid technologies (ENGR 201, ECE 433/533, ECE 536, ECE 437/537). His research focuses on power system resilience, PMU data analysis, hardware-in-the-loop testing, and AI-driven solutions for energy infrastructure. He has authored publications addressing parameter correction algorithms, fault detection systems, and PMU-based event classification. Notable technical contributions include spatio-temporal analysis of PMU data for unsupervised event detection (2021) and sparse regression techniques for power network parameterization (2019). His early work included foundational contributions to 40Gbps Ethernet PCS implementation (2015). No awards or grants are explicitly listed in the provided materials. His research interests bridge electrical engineering fundamentals with modern analytical techniques, emphasizing grid stability, protection systems, and smart grid innovation. Current academic activities include advancing hardware-software co-design methods for power system testing environments.
Rajit Manohar is the John C. Malone Professor of Electrical & Computer Engineering at Yale University, with appointments in Applied & Computational Mathematics and Computer Science. He is a core member of the interdisciplinary Computer Systems Lab (CSL), which bridges ECE and CS departments. His research focuses on asynchronous VLSI design, neuromorphic computing, and hardware-software co-design. Education: Manohar holds a B.S., M.S., and Ph.D. from the California Institute of Technology. His academic career spans over two decades, with notable contributions to asynchronous circuit theory and neuromorphic engineering. Research Interests: Manohar's work emphasizes energy-efficient asynchronous architectures, concurrency control, and biologically inspired computing. He explores topics like formal methods for circuit verification, cognitive systems, and dynamic sensor networks. His lab develops tools like Fluid (asynchronous synthesis) and Neurobench (neuromorphic benchmarking). Publications: Recent work includes advancements in asynchronous logic synthesis (Maelstrom), neuromorphic frameworks (Neurobench), and scalable brain-computer interfaces (SCALO). His research often intersects NSF-funded projects in energy-aware computing and neuromorphic systems. Awards: Inaugural Misha Mahowald Prize (2025), MIT TR35 (2000s), IBM Goldberg Award (2023) Grants & Labs: Manohar leads NSF-supported initiatives in carbon-aware networking and neuromorphic hardware. The Computer Systems Lab collaborates across disciplines to advance sustainable computing and neuro-inspired architectures.
Dr. Charles James Gillan is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, part of the Faculty of Engineering and Physical Sciences. His research focuses on high-performance computing (HPC), heterogeneous accelerators (FPGAs and GPUs), and their applications in diverse fields such as clinical physiology, electromagnetic fields, and image analysis. He collaborates extensively with the QUB Medical School on data analytics and machine learning for ICU patient monitoring. Gillan has led multiple projects, including an InterTrade Ireland-recognized Fusion project with CreVinn Ltd, which transferred FPGA programming knowledge to industry. His work spans academic and industrial partnerships, emphasizing innovation in computing systems and real-world problem-solving. His research interests include KTP projects, EPSRC funding, and H2020 initiatives. He has contributed to high-impact projects like the HPC-NI center and handheld olfactory detection systems. Awards include an InterTrade Ireland award for his Fusion project. Gillan has also engaged in outreach, training graduates in OpenCL programming and fostering industry-academia collaboration. Publications highlight advancements in neural networks for blood pressure prediction, exascale computing algorithms, and AI-driven healthcare solutions. His work bridges theoretical computing and practical applications, with a focus on edge computing architectures and transparency in food systems.
Dr. José Manuel Claver Iborra is a Full Professor at the Department of Computer Science, School of Engineering (ETSE-UV), University of Valencia. He holds a PhD in Computer Science (Parallel and Distributed Computing program) from the Technical University of Valencia and an MSc in Physics (specialized in Electronics and Computer Science) from the University of Valencia. As an IEEE Senior Member, he focuses on cloud computing, video coding, parallel/distributed systems, reconfigurable computing, and network protocols for real-time applications. Current Research: Cloud-based video encoding, GPU acceleration for DNA analysis, FPGA-based network protocols, and indoor localization systems Academic Leadership: Coordinator of the UV-Tirant node in the Spanish Supercomputing Network (RES) His recent publications analyze GPU-based motion estimation, heterogeneous computing for video standards (H.264/AV1), and QoS scheduling algorithms. He supervises PhD and Master's theses on sensor networks, FPGA programming platforms, and parallel applications. Scientific Awards IEEE Senior Member He has directed funded projects on cloud infrastructure, distributed video processing, and reconfigurable systems since the 1990s.
Dr. Janusz Mikołajczyk is a Lecturer at the Institute of Optoelectronics, Warsaw University of Technology. His research focuses on optoelectronic systems, photodetectors, and laser-based sensing technologies. He specializes in infrared communication systems, gas detection using quantum cascade lasers, and advanced noise measurement techniques for photodetectors. His work spans applications in free-space optics, environmental monitoring, and military communication systems. With 155 publications and 7 research projects, he has contributed significantly to fields like cavity-enhanced spectroscopy, optoelectronic sensor development, and high-speed data transmission. His h-index of 20 (WoS) reflects his impactful research in optoelectronics and materials science. Key areas of exploration include THz radiation detectors, ultraviolet photodetectors, and hybrid communication systems combining optical and radio technologies. He has designed innovative detection modules and noise analysis systems, enhancing the reliability of optoelectronic devices in harsh environments.
Assoc. Prof. Dr. Firat Aydemir holds a position as Associate Professor at the Department of Computer Engineering, Faculty of Engineering, Dumlupınar University. He completed his bachelor's in Electrical-Electronic Engineering from Gazi University (2001-2005), a non-thesis master's in Electrical Engineering from the University of Rochester (2007-2009), and a PhD in Electrical-Electronics from Dumlupınar University (2012-2017). His academic career includes roles such as Department Head (2024–present), Deputy Director of Research and Application Centers (2020–2024), and head of multiple academic committees. His research focuses on IoT, embedded systems, sensor technologies, and AI applications in healthcare and industrial automation. Notable projects include developing a lung cancer diagnosis system via breath analysis, license plate recognition using deep learning, and IoT-based smart systems for education continuity during pandemics. He has authored over 24 peer-reviewed publications and holds an award for the 5th LED Competition (2014). Aydemir teaches courses on microcontrollers, embedded systems, circuit theories, and IoT applications. His work spans academic leadership, grant coordination, and interdisciplinary research collaborations.
