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Chetan Singh ThakurView profile

Associate Professor

• Neuromorphic VLSI Systems
• Neuromorphic Sensors and their Applications
• Machine Learning for Edge Computing
• +4 more

Associate Professor Chetan Singh Thakur holds a primary appointment at the Indian Institute of Science (IISc), Bangalore since 2017 and serves as an Adjunct Researcher at Western Sydney University's International Centre for Neuromorphic Systems (ICNS). He earned his PhD in neuromorphic engineering from Western Sydney University in 2016 under Professor André van Schaik, followed by a research fellowship at Johns Hopkins University with Professors Ralph Etienne-Cummings and Ernst Niebur. His academic background includes: PhD in Neuromorphic Engineering, Western Sydney University, 2016 Research Fellow, Johns Hopkins University, 2016-2017 Dr. Thakur's pioneering work focuses on translating brain computing principles into intelligent hardware systems , with core expertise in neuromorphic VLSI design, edge computing applications, and computational neuroscience. His research integrates mixed-signal circuit engineering with machine learning to develop brain-inspired processors for real-world applications. His significant contributions have been recognized through: Young Investigator Award from Pratiksha Trust Early Career Research Award by Science and Engineering Research Board - India Inspire Faculty Award for brain-inspired computing by Department of Science and Technology - India Dr. Thakur secured competitive national research funding through his award-winning proposals and leverages six years of industrial experience as a Senior Integrated Circuit Design Engineer at Texas Instruments Singapore. His current work bridges academic research and practical VLSI system development through collaborations with ICNS and IISc Bangalore.

Bo ZhaoView profile

Assistant Professor

• Thermal photonics
• Plasmonics
• Nonreciprocal thermal radiation
• +4 more

Dr. Bo Zhao is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Houston . He leads the Thermal PhotoniX (TPX) Lab , focusing on theoretical and experimental research in thermal photonics, plasmonics, and nonreciprocal thermal radiation. His work addresses global challenges in energy conversion, thermal management, and photonics for sustainable technologies. Education: Ph.D. in Mechanical Engineering from Georgia Institute of Technology. Research Highlights : Nonreciprocal thermal emitters for energy harvesting and photonic systems Solar thermophotovoltaics and advanced radiative cooling Weyl semimetals for topological optoelectronics Experimental validation of Kirchhoff’s law violations Awards & Recognition : NSF CAREER Award (2025) 2023 Elsevier/JQSRT Raymond Viskanta Young Scientist Award NSF I-CORPS Award (2024) University of Houston’s 50-in-5 Scholar (2022) Advising & Grants : Advises over 10 graduate students including Sina, Bardia, and Yasmine Funded by NSF, DOE, and UH’s SEED Program Patent applications on nonreciprocal solar harvesting TPX Lab collaborates with institutions like Georgia Tech, Stanford, and Caltech to advance thermal photonics through interdisciplinary research.

Simone OrcioniView profile

Associate Professor

• Sensor Systems
• Biomedical Engineering
• Signal Processing
• +5 more

Prof. Simone Orcioni is an Associate Professor at the Department of Information Engineering, Università Politecnica delle Marche. His research focuses on sensor systems, biomedical engineering, nonlinear signal processing, and embedded systems. He leads projects in structural health monitoring, battery management, and telemedicine solutions. Orcioni's work integrates hardware design, algorithm development, and data analytics to address challenges in infrastructure maintenance, healthcare, and sustainable energy. Education: Not explicitly listed, but his role as an associate professor implies advanced academic credentials in electrical or biomedical engineering. Research interests include wearable sensors for healthcare monitoring, IoT-enabled environmental systems, and stochastic modeling of nonlinear processes. He collaborates on interdisciplinary projects involving robotics, circular economy, and smart infrastructure. His publications span journals and conferences in signal processing, biomedical engineering, and electronics. Notable areas include electrochemical impedance spectroscopy, sleep monitoring systems, and low-cost sensor networks. Orcioni's work emphasizes practical applications, such as non-invasive vital sign detection and sustainable battery recycling processes. Awards: None explicitly mentioned. Grants and collaborations are implied through his research projects but not detailed in the text. He contributes to academic governance via his teaching and administrative roles at the university. Labs/Teams: Affiliated with the Department of Information Engineering's research groups focused on embedded systems, biomedical instrumentation, and nonlinear signal analysis. Collaborates with industry partners on projects like smart EV charging systems and telemedicine platforms.

Chen-Ching LiuView profile

Professor

• Power Systems
• Cybersecurity
• Electricity Markets
• +5 more

Chen-Ching Liu is the American Electric Power Professor and Director of the Power and Energy Center at Virginia Tech's Bradley Department of Electrical and Computer Engineering. He holds a Ph.D. from UC Berkeley and has held academic roles at institutions such as Washington State University (2011-2017), University of Washington (1983-2005), and University College Dublin (2008-2015). His research focuses on power systems, cybersecurity, resilience engineering, and renewable energy integration. Education : Ph.D., Electrical Engineering, UC Berkeley (1983) M.S., National Taiwan University (1978) B.S., National Taiwan University (1976) Research Interests : Cybersecurity of power systems Smart grid resilience and restoration Electricity market mechanisms Renewable energy integration Advanced control systems for microgrids Key Awards : Member, National Academy of Engineering (2020) IEEE Fellow (1993) Outstanding Power Engineering Educator Award (2004) Doctor Honoris Causa, Polytechnic University of Bucharest (2013) Grants & Projects : Directed the WSU Energy Systems Innovation Center (2012–2017) Lead researcher on cyber-physical system security and microgrid resilience Contributed to CIGRE defense plans against extreme contingencies Labs & Teams : Director of Virginia Tech’s Power and Energy Center Developed cyber-distribution system testbeds for education and research Collaborates with industry partners on smart grid and cybersecurity initiatives

Piet DemeesterView profile

Professor

• Optical Communication Networks
• Wireless Communication Systems
• Networked Intelligence
• +3 more

Piet Demeester is a Full Professor at the Faculty of Engineering and Architecture, Ghent University, and serves as Director of the IDLab-Department (imec/UGent/UA). His research spans optical and wireless communication networks, networked intelligence, and electromagnetic field exposure analysis. Key affiliations: Ghent University, University of Antwerp, imec Labs: IDLab (350+ researchers focusing on optical/wireless networks, cloud infrastructures, AI for robotics) His work includes foundational contributions to ultra-high-capacity wireless networking under the ERC Advanced Grant "ATTO." Scientific awards include IEEE Fellowship (2009). Publications demonstrate technical leadership in 5G/6G architectures, analog radio-over-fiber systems, and human EMF exposure modeling. Major research themes Optical/Wireless Network Integration Millimeter-Wave Communication Exposure Assessment Methodologies Photonic Antenna Systems Notable collaborations include leadership in European testbed federations like Fed4fire and co-development of standards for networked intelligence.

• 3D Integrated Circuits
• Hardware Security
• AI Accelerators
• +4 more

Krishnendu Chakrabarty is the Fulton Professor of Microelectronics in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU). He also serves as CTO of the SWAP Hub for the Department of Defense Microelectronics Commons and Director of the ASU Center for Semiconductor Microelectronics (ACME). Previously, he was the John Cocke Distinguished Professor and Chair of Electrical and Computer Engineering at Duke University. Education: B.Tech from IIT Kharagpur (1990), M.S.E. and Ph.D. from the University of Michigan (1992, 1995). His research focuses on 3D integrated circuits, hardware security, AI accelerators, and microfluidic biochips. He has authored 27 books, 930 peer-reviewed papers, and holds 24 patents. His work has been supported by NSF, DARPA, NIH, and industry partners like Intel and NVIDIA. Key awards include NSF CAREER Award, IEEE Technical Achievement Awards, Humboldt Research Award, and Distinguished Alumnus from IIT Kharagpur. He advises 44 PhD graduates and collaborates with industry leaders such as Synopsys and Cisco. His leadership roles include Editor-in-Chief of IEEE Transactions and Fellowships in ACM, IEEE, and AAAS. Research highlights include pioneering test methodologies for 3D ICs, developing AI-driven biochip solutions, and securing hardware against cyber-physical threats. His labs and teams focus on advancing semiconductor technology and healthcare applications through interdisciplinary innovation.

Magnus KarlssonView profile

Academic

• Communication Electronics
• Microwave Technology
• Internet of Things (IoT)
• +5 more

Magnus Karlsson is a Senior Associate Professor at Linköping University's Department of Science and Technology (ITN), within the Physics, Electronics and Mathematics division. He holds a Master of Science (2002) and a PhD (2008) in Communication Electronics from Linköping University's Norrköping campus. His research focuses on communication electronics, microwave technology for industrial heating, IoT-driven building energy optimization, and electromagnetic compatibility (EMC). He leads projects involving digital twins for historic building preservation, energy forecasting, and cloud-based environmental monitoring systems. Teaching includes four master's courses in Electronics and Systems Design: circuit board design, RF electronics, antenna theory, and EMC. He chairs the master's program planning group and serves on the Program Board for Electrical Engineering, Physics, and Mathematics. His electromagnetic compatibility laboratory at Norrköping campus supports research on antenna experimentation and EMC standards compliance. Recent work emphasizes IoT integration with historic structures and AI-enhanced energy efficiency systems.

Samuel Simon ArayaView profile

Associate Professor

• Fuel Cell Technology
• Renewable Energy Systems
• Electrochemical Systems
• +3 more

Samuel Simon Araya is an Associate Professor at Aalborg University's Faculty of Engineering and Science, specializing in Thermal Engineering. His research focuses on Proton-Exchange Membrane Fuel Cells (PEMFC), High-Temperature PEM Fuel Cells (HT-PEMFC), and Electrolysis technologies. He leads projects like 'Data-driven Diagnosis for High Temperature PEM Fuel Cells' and 'HySTrAm: Hydrogen Storage and Transport using Ammonia.' Key areas include fault diagnosis via Electrochemical Impedance Spectroscopy (EIS), CFD modeling of electrolysis cells, and sustainable energy systems. He supervises PhD students in fuel cell durability, power-to-fuel systems, and green ammonia production. His work aligns with UN SDGs for clean energy and climate action. Notable collaborations involve developing hydrogen storage solutions and optimizing PEM electrolyzers. His recent publications address multi-objective optimization of energy systems, CFD analysis of multiphase flows, and online fault detection methods. Araya has contributed to over 84 research outputs, including journal articles, conference papers, and reviews. His research bridges theoretical models with practical applications in green hydrogen production, fuel cell performance, and electrochemical systems.

• Digital Signal Processing (DSP)
• Field-Programmable Gate Arrays (FPGA)
• Machine Learning Hardware Acceleration
• +13 more

Gian Carlo Cardarilli is a researcher specializing in digital hardware design and machine learning acceleration. His work focuses on FPGA implementations, Residue Number System (RNS) architectures, and reconfigurable computing for applications in wireless communication, edge AI, and fault-tolerant systems. Key collaborations with institutions like IEEE and ACM through publications. Active in translating theoretical algorithms into practical hardware solutions for real-time systems. Research interests include: Optimizing deep learning models for heterogeneous platforms. Developing radiation-hardened memory systems. Creating energy-efficient signal processing architectures. Advancing reconfigurable functional units for embedded processors. His article analyses span fields like Quantum Cellular Automata , Variable Fractional Delay Filters , and RNS-Based Position Estimation , reflecting a trend toward adaptive, low-power, and domain-specific hardware.

• Parkinson's Disease
• Neurodegenerative Disorders
• Gait Analysis
• +7 more

Professor Alison Yarnall is a neurology researcher at Newcastle University, specializing in Parkinson's disease, cognitive impairment, and neurodegenerative disorders. Her work focuses on gait analysis, wearable sensor technologies, and clinical outcomes in neurodegenerative conditions. She leads the Mobilise-D consortium and collaborates on studies like the Exenatide-PD3 clinical trial. Her research addresses delirium detection, cholinergic dysfunction, and motor symptom management in Parkinson's patients. She has pioneered real-world gait monitoring and validated digital health tools for medication adherence. Her multidisciplinary approach integrates engineering, neuroscience, and clinical practice to improve diagnostic accuracy and therapeutic interventions. Affiliations: Newcastle University (Neurology focus) Key projects: Mobilise-D, ICICLE-PD cohort studies Research emphases: Wearable sensors, Parkinson's biomarkers, cognitive decline prediction Her research interests include the interplay between cholinergic systems and postural control, the role of digital mobility outcomes in clinical trials, and the neuroimaging correlates of cognitive impairment. She has published extensively on gait analysis, delirium in Parkinson's patients, and the application of machine learning in neurological monitoring. Notable contributions include developing energy-based indices for motor state assessment and advancing Delphi-method protocols for patient-centered digital health design. Her work bridges clinical practice and technological innovation, aiming to improve patient outcomes through precise monitoring and early intervention strategies.

• Neuromorphic Engineering
• Compute-in-Memory Architectures
• Dynamic Vision Sensors
• +4 more

Rajkumar Kubendran is an Assistant Professor at the University of Pittsburgh's Department of Electrical and Computer Engineering within the Swanson School of Engineering. His research focuses on neuromorphic engineering, low-power analog circuits, and biomedical hardware design. He holds a PhD from the University of California San Diego (2014–2020), an MS from Purdue University (2009–2012), and a B.Tech from the National Institute of Technology (2004–2008). His work includes prototypes like dynamic vision sensors (DVS) and in-memory compute architectures, with applications in event-driven computer vision and medical devices. Research interests span brain-machine interfaces, compute-in-memory systems, and neuromorphic computing for robotics and biomedical applications. Notable projects include retina-inspired cameras, custom AI hardware, and programmable stimulators for neural interfaces. His team emphasizes energy-efficient architectures and bio-inspired designs, with recent publications in areas like event-based sensorimotor control and neuromorphic benchmarking frameworks. Professional experience includes internships at Intel, IMEC Belgium, MaxLinear, and Qualcomm. He is an IEEE Senior Member. Though no awards are explicitly listed, his contributions to neuromorphic systems reflect significant technical impact. Current work integrates hardware-software co-design for scalable neuromorphic systems and biomedical device startups.

Erika CoviView profile

Assistant Professor

• Neuromorphic Engineering
• Electronic Engineering
• Materials Science
• +3 more

Erika Covi is an Assistant Professor at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bio-inspired Circuits & Systems group within the Zernike Institute for Advanced Materials. Her research focuses on neuromorphic engineering, leveraging emerging materials like ferroelectric and memristive devices to design bio-inspired circuits and systems. Key areas include ferroelectric tunnel junctions (FTJs), spiking neurons, and neuromorphic edge computing. She collaborates on compact modeling for efficient circuit simulations and explores applications in energy-efficient neural networks. Her work integrates interdisciplinary approaches from materials science, electrical engineering, and computational neuroscience. Research interests span device physics of ferroelectric materials, analog neuromorphic hardware, and neuromorphic computing architectures. She has contributed to studies on coincidence detection in spiking neurons using ferroelectric polarization and tunable synaptic working memory with memristive devices. Current projects emphasize bridging device-level innovations with system-level neuromorphic applications, aiming to advance bio-inspired computing technologies.

• Hyperdimensional Computing
• Edge AI
• Neural Network Acceleration
• +3 more

Tajana Rosing is a Professor at the University of California, San Diego, specializing in hyperdimensional computing, neural network acceleration, and edge AI systems. Her work bridges hardware-software co-design for IoT, biomedical applications, and security-enhanced computing. University: University of California, San Diego Research Focus: Hyperdimensional Computing, Edge AI, IoT Systems, Neural Acceleration, Secure Machine Learning Her recent publications focus on energy-efficient neural network acceleration (e.g., Processing-in-Memory architectures), few-shot learning for edge devices, and hyperdimensional methods for sensor data and biomedical applications. She explores robustness against adversarial attacks and federated learning frameworks. Key trends include hyperdimensional computing for multimodal sensor fusion, transformer optimization via hardware-software co-design, and privacy-preserving edge AI. Collaborations often involve co-authors like Xiaofan Yu, Minxuan Zhou, and Onat Güngör. Her work impacts domains such as healthcare (glucose prediction, ECG analysis), cybersecurity (intrusion detection), and bioinformatics (mass spectrometry, viral sequence analysis).

Balder ten CateView profile

Associate Professor

• Logic in computer science
• Data management
• Knowledge representation
• +5 more

Balder ten Cate is an Associate Professor at the University of Amsterdam, where he leads the Theoretical Computer Science research unit within the Institute for Logic, Language and Computation (ILLC). His academic journey includes previous positions at INRIA, UC Santa Cruz, Stanford, LogicBlox, and Google. He maintains active collaborations across institutions including the University of Bergen (co-advising PhD students) and Tsinghua University. Primary Affiliation: Theoretical Computer Science (TCS) Secondary Affiliation: Mathematical & Computational Logic (MCL) Office: Room L6.38, LAB42, Science Park 900, Amsterdam Dr. ten Cate's research spans diverse applications of logic in computer science and AI, with particular emphasis on data management, knowledge representation, and machine learning. His work bridges theoretical foundations with practical applications, focusing on how logical frameworks can enhance data systems and AI capabilities. He has developed significant contributions in finite model theory, database theory, and computational learning theory, with recent work exploring connections between universal algebra and learning theory. His publication record shows a strong trajectory in theoretical computer science, with recent papers focusing on query algorithms, interpolation in logical fragments, and the learnability of database queries. The research demonstrates consistent contributions at top venues including PODS, ICDT, IJCAI, and ACM Transactions journals. His work on 'Extremal Fitting Problems for Conjunctive Queries' received the ACM PODS 2023 Best Paper Award, while 'SAT-Based PAC Learning of Description Logic Concepts' earned an IJCAI 2023 Distinguished Paper Award. 2024 ETAPS Best Paper Nomination 2023 ACM SIGMOD Research Highlights Award 2023 Alberto Mendelzon Test-of-Time Award ICDT 2012 Best Paper Award 2006 EACSL Ackermann Prize for best dissertation Dr. ten Cate actively supervises PhD and MSc students, with recent theses covering topics like modal formula characterization, conjunctive queries, and temporal logic. He serves on numerous program committees including PODS 2025 and ICALP 2024, and has organized workshops on learning and logic. His current MSCA European Re-Integration Fellowship 'LLAMA: Logic and Learning: an Algebra and Finite Model Theory Approach' (2021-2025) demonstrates ongoing research leadership. He also contributes to academic service through committee memberships including the ASL Committee on Education and the editorial board of the Journal of Logic, Language and Information.

SALİH NACARView profile

Lecturer

• Power Electronics
• PV Systems
• Induction Heating
• +5 more

SALİH NACAR is a Lecturer in the Department of Electrical Engineering at Bandırma Onyedi Eylül University's Faculty of Engineering and Natural Sciences since 2021, and previously held a Lecturer role at Kastamonu University (2011–2021). He currently serves as the Deputy Head of the Department and specializes in power electronics, hydrogen energy systems, and resonant converter technologies. His research focuses on fuzzy logic control, soft switching techniques, and induction heating applications. He has actively contributed to over 11 journal articles and 10 conference papers, with recent work emphasizing hybrid-controlled resonant converters, induction heating systems, and hydrogen production optimization. His academic teaching spans courses in power electronics, electrical engineering fundamentals, and hydrogen energy technologies. Dr. Nacar leads ongoing projects like the design of Class-E resonant inverters and LED drivers, and has advised three master’s theses in advanced power electronics. His research portfolio includes collaborations on digitally controlled DC-DC converters and investigations into resonance-based energy conversion systems for renewable applications. He remains a key figure in advancing energy-efficient power electronics and hydrogen storage solutions.