Find Academic Supervisors

• Computer Engineering
• Microelectronics
• Embedded Systems
• +5 more

Julián Viejo Cortés is an Associate Professor at the University of Seville, affiliated with the Department of Electronic Technology in the School of Computer Engineering. His professional focus revolves around hardware design, embedded systems, and microelectronics, with notable contributions to secure IoT devices, FPGA-based systems, and time synchronization protocols. He has led or participated in multiple research projects such as USECHIP: Chair in Microelectronics and NanoFS: a hardware-oriented file system . Research Interests: - IoT Security and Embedded Systems - FPGA and Hardware Design Methodologies - Time Synchronization Protocols - Low-Power CMOS Circuit Design - Membrane Computing and Formal Systems - System-on-Chip (SoC) Integration His publications emphasize practical hardware solutions, including secure boot mechanisms ( IRIS ), efficient time server cores, and energy-efficient CMOS gate designs. He has directed doctoral research, such as Juan Quirós Carmona's thesis on membrane computing hardware implementations. Grants & Projects: USECHIP: Chair in Microelectronics (TSI-069100-2023-001) Advanced Initiation Systems for IoT (TIN2017-89951-P) Incentive Grants for TIC-204 Research Group (2017–2010) Labs/Teams: Active contributor to the Digital Research and Development group, focusing on innovative embedded systems and FPGA applications.

Cesar Ortega-SanchezView profile

Associate Professor

• Embedded Systems
• Bio-inspired Architectures
• Engineering Education
• +6 more

Associate Professor Cesar Ortega-Sanchez is affiliated with Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS), where he holds the role of Associate Professor since 2005. He has served in leadership roles including Academic Lead of the Engineering Foundation Year (2015-2022), Associate Dean of Teaching and Learning (2013-2014), and Chair of IEEE WA Section (2016-2017). His expertise spans bio-inspired systems, embedded systems, robotics, and engineering education. Education: BEng (Hons) from the Metropolitan Autonomous University (Mexico), MSc from Brunel University (UK), and PhD from the University of York (UK). Specializes in curriculum design, assessment methodologies, and promoting student employability. Mentor of Curtin Robotics Club and IEEE Curtin Student Branch since 2009. Research Interests: Embedded systems, bio-inspired architectures, educational pedagogy, and indigenous content integration in engineering curricula. Over 60 publications in areas like FPGA-based assistive technologies, smart home systems, and energy storage monitoring. Awards include the 2015 Australian Office of Learning and Teaching Citation and M.K. Stott Prize (2000). Teaching roles include leading ELEN1000 (Electrical Systems) and ENGR1000 (Engineering Connections), with a focus on innovative teaching methods like project-based learning (e.g., 'Crazy Machine' lab projects). Active in educational committees at university and national levels.

Janusz A. StarzykView profile

Professor

• Machine Learning
• Neural Networks
• Robotics
• +7 more

Janusz A. Starzyk is a Professor of Electrical Engineering and Computer Science at Ohio University's Russ College of Engineering and Technology, and holds a concurrent professorship at the University of Information Technology and Management in Rzeszów, Poland. He earned his M.Sc. and Ph.D. in Electrical Engineering from Warsaw University of Technology and a habilitation from Silesian University of Technology. His research focuses on embodied intelligence, machine learning, neural networks, and VLSI design, with notable contributions to self-organizing systems and reinforcement learning. Starzyk has supervised 47 M.Sc. and 16 Ph.D. students, and his work spans over 190 peer-reviewed publications. He leads the Embodied Intelligence Lab at Ohio University and collaborates with institutions worldwide, including Nanyang Technological University and the Institute for Artificial Intelligence in Switzerland. His awards include the Best Research Paper Award from Ohio University and nominations for IEEE Fellow. He has secured $3.8 million in research grants, with projects in GPS signal processing, radar target recognition, and machine learning applications. His patents include innovations in object identification systems and self-organizing learning hardware. Starzyk's expertise bridges academia and industry, with roles as a consultant for companies like Magnolia Broadband and Sarnoff Research.

Carlo PatronoView profile

Professor

• Nonsteroidal antiinflammatory drugs
• Antiplatelet drugs
• Clinical pharmacology
• +1 more

Carlo Patrono is a distinguished Professor and Chair of Pharmacology at the Catholic University School of Medicine in Rome, a position he has held since 2007. Previously, he served as Professor of Pharmacology at University of Rome 'La Sapienza' 2nd School of Medicine (2001-2006) and University of Chieti 'G. d'Annunzio' School of Medicine (1991-2001). His academic journey began as Assistant Professor at Catholic University School of Medicine (1972-1982), progressing to Associate Professor (1983-1985). Dr. Patrono earned his M.D. Cum Laude from Catholic University School of Medicine, Rome in 1968, following a B.S. in Arts from Liceo Classico Nazareno in 1962. He completed postdoctoral training at Bronx Veterans Administration Hospital and Mount Sinai School of Medicine, New York (1969-1971). His research focuses on nonsteroidal antiinflammatory drugs , antiplatelet drugs , clinical pharmacology , and arachidonic acid metabolism , with significant contributions to understanding cardiovascular pharmacology and platelet function. His work has particular relevance to aspirin therapy and antithrombotic agents. Dr. Patrono has received numerous prestigious awards including the Grand Prize from Fondation Lefoulon-Delalande (2013), the John Vane Award from University of London (2007), and the International Aspirin® Senior Award from Bayer AG (1998). His scholarly impact is reflected in his editorial roles with major journals including Circulation and Arteriosclerosis, Thrombosis and Vascular Biology. As an active researcher, he serves as Principal Investigator for multiple funded projects including studies on antiplatelet effects of aspirin in diabetes patients, funded by Bayer HealthCare AG. He also contributes to European Commission initiatives like the EICOSANOX program investigating eicosanoids and nitric oxide in cardiovascular diseases. Within his institution, Dr. Patrono chairs the Drug Therapy Committee and serves on the Ethics Committee at Catholic University School of Medicine, Rome. He is also a member of the Board of Directors for the Center for Aging Sciences at G. d'Annunzio University Foundation.

• Wireless Networks
• Telecommunications
• Stochastic Analysis
• +3 more

Udo Schilcher is a researcher affiliated with the University of Klagenfurt’s Institute for Networked and Embedded Systems, part of the Faculty of Technical Sciences. His primary research focuses on wireless networks, telecommunications, and stochastic analysis, with particular emphasis on swarmalator systems, pulse-coupled oscillators, and network performance optimization. He contributes to the Information Technology Curricular Commission, shaping academic standards in his field. His work explores topics like LoRa network energy efficiency, interference dynamics in wireless systems, and self-organizing synchronization mechanisms. Schilcher’s publications span over a decade, addressing theoretical and applied challenges in IoT, network reliability, and adaptive systems. His research often bridges mathematical modeling with real-world applications in communication systems and smart infrastructure. Recent projects involve collaborative efforts on IoT applications, including LoRa network enhancements and cooperative relaying strategies. His interdisciplinary approach combines stochastic processes with engineering principles to address complex network challenges. Schilcher’s contributions to academic curricula and technical research highlight his role as both an educator and innovator in networked systems.

Henryk RichterView profile

Researcher

• Data Compression
• Image and Video Coding
• Real-Time Video Codecs
• +3 more

Dr.-Ing. Henryk Richter is a postdoctoral scientific assistant at the University of Rostock, affiliated with the Communications Engineering research group. His work spans multimedia engineering, focusing on video coding and real-time systems. Education : PhD in Electrical Engineering from University of Rostock (2006), thesis on cross-standard video decoding concepts. Research Interests : Data compression, image/video coding, multistandard video decompression, and real-time signal processing. Publications : 15 most recent articles (2005–2024) highlight advancements in video codecs, biomedical signal processing, and hardware optimization. Contact : henryk.richter@uni-rostock.de

Adrian Virgil CRĂCIUNView profile

Associate Professor

• Electronic circuits analysis and design
• Electronic devices and circuits modeling
• Data acquisition systems
• +7 more

Adrian Virgil CRĂCIUN is an Associate Professor at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Brașov. His research focuses on analog electronics, electronic circuit modeling, and data acquisition systems. He has published extensively on topics like VHDL-based filter design, low-power amplifiers, and FPGA security. His work includes both theoretical contributions and practical implementations in medical electronics and embedded security systems. Education Background: No explicit education details provided in text Research Interests: Dr. CRĂCIUN specializes in electronic circuit analysis and design, with emphasis on analog systems. His work integrates hardware security (PUF-based solutions), low-power medical electronics, and advanced simulation techniques using VHDL. Recent efforts focus on optimizing power consumption in complex integrated circuits and developing robust FPGA identification methods. Grants & Collaborations: No grant information explicitly stated Labs & Teams: Participates in university-based electronics research groups focused on analog circuit design and embedded systems security.

Mihai LucanuView profile

Professor

• Multi-level voltage source inverters
• Pulse duration modulation by space vector modulation
• Power factor correction converters
• +2 more

Mihai Lucanu is a Professor at the Gh. Asachi Technical University of Iasi , serving as Dean of the Faculty of Electronics and Telecommunications. His academic work focuses on advanced power electronics and electromagnetic phenomena. Subjects taught: Industrial Electronics, Power Electronics, Pulse Width Modulation Techniques Research areas: Power Converters, Fuzzy Controllers, Electromagnetic Scattering Research Highlights: His expertise spans power electronics optimization, including soft switching converters , power factor correction , and multi-level inverters . In computational electromagnetics, he specializes in Wave Iterative Process simulations for complex scattering problems. Academic Output: His publications cover topics from high-frequency AC choppers to electromagnetic diffraction analysis, with recent 2025 work on voltage ripple and neural network implementations in 3D semiconductor technology. Contact: mlucanu@etc.tuiasi.ro

• Cloud Computing
• Internet of Things (IoT)
• Semantic Web
• +3 more

Euripides Petrakis is a Professor at the School of Electrical and Computer Engineering of the Technical University of Crete (TUC), serving as Director of the Intelligent Systems Laboratory since 2006. He holds a B.Sc. in Physics from National University of Athens (1985) and a Ph.D. in Computer Science from University of Crete (1993). His research focuses on cloud computing, IoT, semantic web technologies, and image databases. Notable achievements include over 175 publications with a Google Scholar citation count exceeding 4000, attracting €2.5M in EU and Greek Government funding. Education: B.Sc. Physics (1985), Ph.D. Computer Science (1993) Research interests span: - Cloud computing and microservices orchestration - IoT security and interoperability - Semantic web ontologies for service descriptions - Edge computing architectures Recent work emphasizes Kubernetes scheduling optimizations, real-time video processing, and GDPR-compliant IoT frameworks. His group developed systems like TWIST, DeFog, and CLONE, addressing challenges in distributed systems and semantic interoperability. Awards: TUC Excellence Award (2022), AINA 2024 Best Paper Advising over 30 graduate students, Prof. Petrakis has coordinated 15+ research projects. His lab explores next-generation cloud-edge architectures and semantic web of things standards.

• Biomedical Engineering
• Neural Interfaces
• Wearable Technology
• +3 more

Dr. Ian Williams is a Research Fellow in Translational Implantable Devices at the Department of Electrical and Electronic Engineering, Faculty of Engineering at Imperial College London. His affiliations include the Centre for Bio-inspired Technology, Circuits and Systems, and the Neural Interfaces group. He holds a PhD from Imperial College London in Engineering. His research focuses on neural stimulation for providing artificial sensory feedback in prosthetic limbs, aiming to replicate natural proprioceptive and tactile signals. Key areas include implantable neural interfaces, wearable sensors (e.g., in-ear devices), and bidirectional neural communication systems. Applications span clinical neuroprosthetics, chronic disease monitoring (e.g., COPD), and cognitive workload assessment in gaming. Recent work emphasizes multimodal sensing platforms (BioBoard), wireless power solutions for brain-machine interfaces, and programmable neural interface technologies (Neuro-PULP). He has contributed to over 20 peer-reviewed articles since 2013, addressing challenges in electrode durability, real-time data processing, and clinical translation of neural interfaces. His research integrates hardware design, signal processing, and clinical validation to advance next-generation biomedical devices. Current projects include developing in-ear hearables for continuous health monitoring and bidirectional neural prostheses with closed-loop feedback systems.

Tommaso PolonelliView profile

Lecturer

• Embedded systems
• IoT
• Wireless Sensor Networks
• +7 more

Dr. Tommaso Polonelli is a Lecturer and Postdoctoral Researcher at ETH Zürich's Department of Information Technology and Electrical Engineering, affiliated with the Center for Project-Based Learning (PBL). He leads teaching initiatives and research in IoT systems, energy-efficient electronics, and autonomous technologies. His research focuses on energy-efficient systems, smart sensing, and ultra-low power computing, with applications in UAVs, wind turbine monitoring, and wearable devices. He also serves as a Scientific Advisor at RTDT Laboratories AG, an ETH spin-off. Polonelli holds a PhD (2020) and Master’s degree (2017) in Electronic Engineering from the University of Bologna. He has co-authored over 60 publications and received awards such as the Spark Award (2021), KITE Award finalist (2024), and the Certificate of Achievement for National Scientific Qualification (2023). He is an active IEEE member and contributes to both academia and industry through innovations in sensor technology and predictive maintenance. His work emphasizes interdisciplinary collaboration, with projects ranging from structural health monitoring to AI-enhanced systems. Recent efforts include Aerosense—a MEMS-based monitoring system for wind turbines—and ElectraSight, a smart eyewear platform with non-invasive eye tracking.

• High-Voltage Engineering
• Condition Monitoring
• Fault Detection
• +5 more

Chi-Ching Hsu is a researcher at ETH Zurich's High Voltage Engineering department under the Power Systems and High Voltage Lab. Their work focuses on condition monitoring of high-voltage electrical equipment using advanced sensing and machine learning techniques. Key areas include fault diagnostics for circuit breakers, predictive maintenance strategies, and development of edge-sensing platforms for grid infrastructure. Hsu has contributed to experimental studies using vibration and acoustic signals to assess equipment degradation, emphasizing unsupervised learning methods and explainability in AI-driven diagnostics. Education: Doctorate in D-ITET program at ETH Zurich Research interests span electrical grid systems, fault detection methodologies, and the integration of IoT-based solutions for industrial equipment monitoring. Their work bridges mechanical, electrical, and data science disciplines to improve reliability of power transmission components. Publications highlight innovative approaches to transform fault detection into proactive health management systems, with applications in both laboratory setups and real-world grid environments.

• Machine Learning
• Biomedical Engineering
• Human-Computer Interaction
• +4 more

Woojin Kim is a Professor in the Department of Mathematics at Duke University, Durham, NC, USA. His research spans interdisciplinary domains including Machine Learning , Biomedical Engineering , Human-Computer Interaction , and Wireless Sensor Networks . He has made significant contributions to medical imaging analysis , autonomous driving systems , and AI in education , with recent work focusing on fairness evaluation in machine learning and vision-language models for healthcare applications . His publications demonstrate expertise in: AI-driven medical diagnostics (CT scans, MRIs) Exoskeleton and robotic systems Autonomous vehicle transition dynamics Privacy-preserving clinical data processing Memory hardware testing frameworks Knowledge tracing algorithms in education Recent article trends highlight increasing emphasis on AI ethics (fairness evaluation), multimodal models (vision-language), and knowledge graph applications for scientific data organization. Collaborations with interdisciplinary teams across biomedical, engineering, and computer science domains underscore his cross-domain impact.

• Sensor Technology
• Instrumentation and Measurement
• Dielectric Material Characterization
• +4 more

Nicola Donato is a researcher at the University of Messina, Italy, specializing in instrumentation and measurement technologies. His work spans sensor development, dielectric characterization, and biomedical monitoring systems, with significant contributions to microwave-based sensing and neural network modeling for sensor optimization. Research interests include: Design and modeling of resonant sensors for dielectric material analysis Development of wireless biomedical monitoring systems (e.g., EEG-over-BLE architectures) Nanomaterial-based gas and chemical sensors for medical/environmental applications Machine learning techniques for sensor data interpretation and system calibration Publications demonstrate strong emphasis on: Microwave/electrochemical sensor interfaces Thin-film and nanomaterial sensing platforms Embedded systems for healthcare monitoring Hybrid measurement approaches combining RF engineering and machine learning

• 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.