جست‌وجوی استاد و پژوهشگر

Felipe Martinsمشاهده پروفایل

مدرس ارشد

• Mobile Robot Control
• Educational Robotics
• Robotics Competitions
• +۶ مورد دیگر

Felipe Martins is a Senior Lecturer-Researcher at Hanze University of Applied Sciences, active in both teaching and the Sensors and Smart Systems research group. He holds a PhD in Electrical and Electronic Engineering (2009) and has a background in industrial automation engineering (1999-2003). His work contributes to UN Sustainable Development Goals through educational robotics and automation. PhD: Modeling and Dynamic Compensation of Mobile Robots (Federal University of Espirito Santo) MSc: Control of Induction Generators via Fuzzy Logic BSc: Microcontroller-based Motor Control Research spans mobile robot control , educational robotics , autonomous navigation , and sensor networks . Recent publications focus on LiDAR data processing (2024), reinforcement learning for robotic applications (2022), and machine learning-driven localization (2023). He received Best Paper Awards at OL2A 2023 and WRE 2018. As a part-time teacher at University of Groningen (since 2022) and visiting researcher at CeDRI (2023), he bridges academia and industry. His editorial roles include guest editorships at Automation (MDPI) and Sensors journals. He co-organized RoboCup Junior events (2013-2021) and developed open-source robotics education tools like RoSoS A free simulator (2016).

• System-on-Chip (SoC) Design
• FPGA-Based High-Level Synthesis
• Real-Time Embedded Systems
• +۵ مورد دیگر

Timo Hämäläinen is a Professor of Computer Engineering at Tampere University, leading the Unit of Computing Sciences within the Faculty of Information Technology and Communication Sciences. He is a core member of the System-on-Chip research group and the Computer Engineering Team, actively contributing to the System-on-Chip Hub initiative. His research focuses on System-on-Chip (SoC) design methodologies, FPGA-based high-level synthesis, real-time embedded systems, and open-source hardware-software co-design frameworks like RISC-V and HEVC encoding. He has pioneered work on agile SoC development processes and validation techniques for large-scale hardware systems. Key research areas include: High-level synthesis (HLS) optimization for FPGAs Real-time processor architectures and context-switching latency reduction Formal verification of IP-XACT-compliant SoC designs Resilient RISC-V MPSoC implementations Hardware-accelerated algorithms for signal processing and networking His recent publications (2023-2025) emphasize agile SoC development frameworks, hardware-software co-design for real-time systems, and validation methodologies for large-scale embedded systems. He has contributed to open-source projects like Kvazaar HEVC encoder and the Kactus2 IP-XACT toolchain. Academic advising includes students such as Santéri Mäki-Äijö (formal verification), Arto Oinonen (RISC-V tooling), and Sakari Lahti (processor modeling). His work integrates academic research with industrial collaboration through frameworks like the Fault-slip-Through quality assessment methodology.

Christian K. Karlمشاهده پروفایل

مدرس ارشد

• Civil Engineering Didactics
• Digital Transformation in Construction Education
• Simulation and Gaming for Disaster Management
• +۳ مورد دیگر

Dr. Christian K. Karl, Senior Lecturer in Civil Engineering Didactics at the University of Duisburg-Essen, combines engineering practice with educational innovation. As Head of the Civil Engineering Didactics group and Chair of the VDI 2552 Guidelines Committee, he pioneers simulation games, BIM training frameworks, and AI integration in pedagogy. Lead developer of simulation tools like 'Einsatz in Grimhausen' for disaster management Recipient of the Best Workshop Award at ISAGA 2025 Principal investigator for projects: KI4Edu , DigiTeamsBau , and BIM Kommunal Author of 20+ publications on BIM, AI, and educational games His research focuses on competency-oriented teaching methods, digital transformation in construction, and immersive learning technologies. Recent work explores AI's impact on teacher roles, Smart Home systems, and circular construction practices. Articles highlight trends in simulation games for crisis training, BIM education frameworks, and AI applications for personalized teaching. He emphasizes human-centered technology development and collaborative digital workflows . Scientific recognition includes: Best Workshop Award (ISAGA 2025) Hochschuldidaktische Innovationen (2010) As Chair of the VDI 2552 committee, he shapes national BIM training standards. His leadership in EU Academy platform development and initiatives like 'Personalisierte KI-generierte Podcasts' underscores his commitment to accessible, forward-thinking education.

• Wireless Systems and Networks
• Internet of Things (IoT)
• Digital Twin
• +۹ مورد دیگر

Luciano Bononi is a Full Professor and Deputy Head of the Department of Computer Science and Engineering at the University of Bologna. He holds a PhD in Computer Science (2002) and has been active in academia since 2001, progressing through roles like Researcher, Senior Researcher, Associate Professor (2011), and Full Professor (2020). His research focuses on Wireless Systems, IoT, Digital Twins, Smart Cities, and Mobile Applications , with over 160 peer-reviewed publications and major contributions to EU projects like Arrowhead and IoE. Education: MS (Laurea) in Computer Science, University of Bologna (1997, Summa cum Laude) PhD in Computer Science, University of Bologna (2002) Research Interests: Bononi's work spans Wireless Protocols, IoT Platforms, Digital Twin Integration with AI, Smart Mobility/ Energy Systems, and Edge Computing . He leads the WiLMA Lab and the ALMA-AI CoInnovation Lab , focusing on real-world IoT deployments and smart city solutions. Key Contributions: Coordinated EU projects like Arrowhead (2013-2017) and national initiatives like PNRR-Mobility-Spoke 7 Recipient of 4 Best Paper Awards and top rankings in global scientist databases Editorial roles at 7 journals including Wiley's Wireless Communications and Elsevier's Ad Hoc Networks Organized over 15 international conferences as Chair and participated in 200+ TPC roles Labs & Teams: Directs the WiLMA Lab (Wireless Systems and Mobile Apps) and the ALMA-AI CoInnovation Lab , emphasizing interdisciplinary collaboration between academia and industry.

Ralf Hagemannمشاهده پروفایل

مدرس

• Embedded Systems
• Software Engineering
• Programming Education
• +۵ مورد دیگر

Ralf Hagemann is a Lecturer/Research Associate at Osnabrück University of Applied Sciences, specifically within the Faculty of Engineering and Computer Science . His academic work combines Embedded Systems , Software Engineering , and innovative teaching methods like Problem-Based Learning . He actively develops educational hardware and tools for engineering education. Embedded Systems Board design (STMNucleo32-Baseboard) Problem-oriented curriculum development for computer science students Qt-based visualization frameworks for algorithm training His research spans geometric algorithms (2013 dissertation), digital signal processing (1991 thesis), and domain-specific programming languages (1997 PIPL invention). Recent publications focus on multicultural engineering education and cost-effective product development . As a part-time faculty member , he leads technical workshops and contributes to European Project Semester initiatives. His 1991 Diplomarbeit at Fachhochschule Bielefeld laid foundations for his work in hardware-software integration . He regularly demonstrates his MpC-Bildschirmstellwerk software at international model railway exhibitions (2008-2016) and has published in journals like MIBA digital Extra and Eisenbahn Kurier .

• Audio and Speech Processing
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Serkan KESER is an Associate Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering and Architecture, Ahi Evran University, Turkey. He has been serving as a full-time faculty member since 2018 and previously served as Head of Department from 2018-2021. His educational background includes a PhD in Electrical and Electronics Engineering from Eskişehir Osmangazi University (2009-2018), a Master's degree in the same field from the same institution (2005-2008), and a Bachelor's degree in Electrical and Electronics Engineering from Mustafa Kemal University (1999-2005). Dr. KESER's research focuses on three main areas: Audio and Speech Processing : Including speaker identification, isolated word recognition, and speech coding techniques Signal Processing : With applications in fiber optic sensor systems and acoustic positioning Image Processing : Covering face recognition, image compression, and denoising techniques His recent publications demonstrate a strong trend toward integrating machine learning and deep learning approaches with traditional signal processing methods. He has made significant contributions in applying subspace methods to various domains including speech recognition, image processing, and sensor technologies. His work often bridges theoretical signal processing concepts with practical applications in areas like smart home systems, medical imaging, and environmental monitoring. Dr. KESER has successfully supervised five Master's students to completion, with thesis topics spanning deep learning applications for class attendance systems, photovoltaic systems, speaker identification, brain tumor classification, and speech-controlled robotic arms. He has led four research projects, including development of fiber optic motion sensors, smart home models using Arduino microcontrollers, and science outreach initiatives. His teaching portfolio includes advanced courses in digital image processing, artificial neural networks, digital signal processing, and machine learning at both undergraduate and graduate levels. Dr. KESER's research impact is reflected in his publication metrics: 30 total publications with 117 citations (h-index 5) through the UNIS system, 25 publications with 180 citations (h-index 6) on Google Scholar, and strong representation in Scopus and Web of Science databases.

Ján Drgonaمشاهده پروفایل

دانشیار

• Differentiable programming
• Scientific machine learning
• Dynamical systems
• +۳ مورد دیگر

Ján Drgona is an Associate Professor in the Department of Civil and Systems Engineering at Johns Hopkins University's Whiting School of Engineering and a member of the Ralph S. O'Connor Sustainable Energy Institute (ROSEI). Previously, he served as a Principal Investigator and Research Data Scientist at Pacific Northwest National Laboratory (PNNL) and held a postdoctoral position at KU Leuven in Belgium. Dr. Drgona earned his BSc, MSc, and PhD in control engineering from the Slovak University of Technology. His research centers on differentiable programming and scientific machine learning (SciML) for dynamical systems, optimization, and control, with particular applications to building energy systems and industrial process control. He is the lead developer of the Neuromancer SciML library in PyTorch for solving constrained optimization, physics-informed machine learning, and optimal control problems, which became PNNL's most popular open-source repository within two years of its release. Dr. Drgona's publication record demonstrates a strong focus on bridging machine learning with physical systems and control theory. His recent work spans differentiable predictive control, physics-informed neural networks, optimization algorithms, and applications to energy systems. A recurring theme across his publications is the integration of domain knowledge with data-driven approaches to create more efficient, reliable, and interpretable systems for real-world applications, particularly in sustainable energy and building systems. As an active member of the scientific community, Dr. Drgona regularly serves as a reviewer for prestigious journals including Applied Energy, Automatica, IEEE Control Systems Letters, IEEE Transactions on Control Systems Technology, IEEE Transactions on Industrial Informatics, Control Engineering Practice, Journal of Process Control, Energy and Buildings, Journal of Control Automation and Electrical Systems, and Electric Power Systems Research. Dr. Drgona has been involved in several high-impact projects, including developing AI models that slash HVAC energy costs while predicting them with precision. He has participated in Johns Hopkins' International Energy Summit to accelerate clean technology innovation and has presented at major conferences including ACC 2025 where he co-organized workshops on Physics-Informed Machine Learning in Control and Safe Physics-Informed Machine Learning for Dynamics and Control.

• Biomedical Engineering
• Electronics
• Instrumentation
• +۳ مورد دیگر

Dr. Edward M. O'Brien serves as Professor of Biomedical Engineering in Mercer University's School of Engineering, where he has taught since 1990 after appointments at Iowa State, Clemson, and Texas A&M Universities. His expertise bridges electrical engineering and medical applications with emphasis on practical student training. Education: PhD, Biomedical Engineering, Iowa State University, 1977 MS, Biomedical Engineering, Iowa State University, 1974 BS, Electrical Engineering, Colorado State University, 1971 Research Focus: His work centers on applying electronics, microcontrollers, and sensor systems to biomedical challenges. Key areas include prosthetic design/fitting (particularly through the Mercer-On-Mission Vietnam program), balance rehabilitation devices, and antibacterial nanotechnology. He prioritizes hands-on learning for engineering students across courses in Analog/Digital Electronics, Instrumentation, and Signal Processing. Publication Analysis: Recent work (2014-2023) demonstrates consistent focus on prosthetic innovation in resource-limited settings, with Vietnam-based field studies forming a core theme. Emerging interests include sensory feedback systems for fall prevention and nanoparticle applications, reflecting expanding interdisciplinary scope while maintaining practical engineering solutions for healthcare. Professional Leadership: Dr. O'Brien actively shapes the field through NSF grant reviewing (2009-2022), NCEES certification exam development since 2004, and engineering program evaluation for East Carolina University (2025). His IEEE and Biomedical Engineering Society memberships since 1984 and 2018 respectively underscore sustained professional engagement. Global Impact: The Mercer-On-Mission Prosthetic Program exemplifies his commitment to integrating engineering education with humanitarian service, training students in real-world prosthetic design and fitting while addressing critical healthcare needs in Vietnam.

• Control Theory
• Real-Time Systems
• Embedded Systems
• +۷ مورد دیگر

Anton Cervin is a Senior Lecturer at the Department of Automatic Control, Faculty of Engineering, Lund University. He is currently on leave of duty but remains actively involved in research and supervision. His work spans real-time systems, event-based control, cloud computing, and embedded systems, with strong ties to industrial applications and sustainable technologies. His research interests include: Event-Based and Stochastic Control Networked and Embedded Control Systems Cloud-Based Control and Resource Management Real-Time Scheduling and Performance Analysis Digital Twins and Fluid Modeling in Cloud Environments He has led major research projects funded by the Swedish Research Council, WASP, and ELLIIT, focusing on robust and secure cloud control, self-adaptive systems, and distributed learning. His software tools—TrueTime, Jitterbug, and TinyRealTime—are widely used in academia and industry for simulating and analyzing real-time control systems. The most recent publications highlight a shift toward intelligent, adaptive control using reinforcement learning, fluid modeling for microservices, and timing-robust cloud control—indicating a strong trend in merging traditional control theory with modern computing paradigms. His scientific contributions have been recognized with multiple Best Paper Awards: Best Paper Award - ECRTS 2021 Best Paper Award - RTNS 2016 Best Paper Award - RTCSA 2004 Best Paper Award - ECRTS 2003 Best Student Paper Award - RTCSA 1999 Anton Cervin has supervised numerous PhD students, including Max Nyberg Carlsson, Nils Vreman, and Claudio Mandrioli, and has served in key academic roles such as Director of PhD Studies and Deputy Head of Department. He has also led educational initiatives like doctoral study circles on programming languages and the history of control. He is affiliated with research environments such as WASP and ELLIIT and contributes to UN Sustainable Development Goals through advancements in smart systems and sustainable automation.

Andrew R. Brownمشاهده پروفایل

استاد

• Creative AI
• Algorithmic music and art
• Interaction design
• +۳ مورد دیگر

Andrew R. Brown is a Professor at Griffith University's Queensland College of Art and Design , with a focus on Creative AI, algorithmic music/art, and interaction design. He leads the Creative Arts Research Institute and co-authored Making Music with Computers: Creative Programming in Python . His research spans computational creativity, digital music tools, and technology's philosophical dimensions. Education : PhD (UQ 2004), Master of Education (U. Melbourne 1993), Graduate Diploma in Computer Science (Deakin 1990), Bachelor of Education (Melbourne CAE 1984). Research Themes : Brown bridges music, computer science, and design through projects like low-cost DIY grooveboxes (OnBoard Quadra), live-coding performance systems, and AI-assisted creative frameworks. His work examines how constraints in technology foster innovation and democratize artistic expression. Recent Publications emphasize accessible electronic instruments, algorithmic pattern generation, and intersections between handmade hardware and digital fabrication. He has secured significant ARC Discovery Project grants and internal university funding for interactive media research. Supervision includes doctoral candidates exploring AI collaboration in art, sonic expression through costume instruments, and open-source design pathways. He also delivered keynotes at ComputationWorld 2019 (Venice) and World Science Festival 2016.

• Biomedical Engineering
• Biosensors
• Microfluidics
• +۵ مورد دیگر

Dr. Orhan Erdem Haberal serves as a Lecturer in the Biomedical Engineering Program at Başkent University's Faculty of Engineering. His academic work focuses on cutting-edge biomedical technologies with applications in diagnostics, medical devices, and tissue engineering. With a strong publication record spanning over a decade, Dr. Haberal has established himself as an active researcher in Turkey's biomedical engineering community. Dr. Haberal's research interests primarily center around biomedical sensors, microfluidics, and nanotechnology applications in medicine. His work spans from developing point-of-care diagnostic devices like PCR microchips and QCM-based biosensors to exploring 3D bioprinting techniques and cardiovascular monitoring systems. His research demonstrates a strong interdisciplinary approach, bridging engineering principles with clinical applications, particularly in the areas of diagnostic technology development and biomaterials. Analysis of Dr. Haberal's recent publications reveals a consistent focus on practical biomedical solutions with immediate clinical relevance. His work shows particular strength in developing diagnostic technologies for point-of-care settings, with multiple publications on microfluidic PCR systems, biosensors for blood analysis, and pathogen detection devices. Additionally, his research extends into cardiovascular engineering with studies on oxygenator systems and pulsatile flow effects, as well as tissue engineering with work on angiogenesis and 3D bioprinting. Dr. Haberal actively contributes to academic education through teaching courses including Biomedical Engineering Introduction, Microcontrollers, System Physiology for Engineers, Modeling in Biological Systems, Electronics, Mathematical Physiology, Human Anatomy and Physiology, and Introduction to Biological Science. His teaching portfolio reflects the interdisciplinary nature of biomedical engineering, spanning both engineering fundamentals and biological sciences. Professional activities show Dr. Haberal's involvement with the Biomedical & Biotechnology R&D center, Biyotek Technology Development Center, and ilab Technology Research and Development Ltd. His work appears to have practical industry applications alongside academic contributions, as evidenced by the multiple projects and company affiliations mentioned in his profile.

Orlando Hernandezمشاهده پروفایل

دانشیار

• VLSI Architectures
• Computer Vision
• Image Processing
• +۴ مورد دیگر

Orlando Hernandez is an Associate Professor in the Department of Electrical and Computer Engineering at The College of New Jersey. He holds a Ph.D. in Electrical Engineering from Southern Methodist University (2002), an M.S.E.E. (1993) and B.S.E.E. (1991) from the University of South Florida. Prior to his academic career, he held industry positions at Texas Instruments and Maxim Integrated Products from 1993-2003, serving in design management roles for imaging systems, ASIC development, and microcontroller technologies. His research focuses on high-performance VLSI architectures for computer vision applications, including color image segmentation, digital signal processing, embedded systems, and mixed-signal design. Key research areas include hardware acceleration for image compression algorithms, real-time traffic monitoring systems, autonomous robotics, and advanced encryption implementations. His work consistently bridges theoretical algorithms with practical hardware implementations. Professional affiliations include Senior Membership in the Institute of Electrical and Electronics Engineers (IEEE). He has secured multiple research grants including a $93,320 National Science Foundation award for image processing instrumentation and several industry-sponsored equipment grants from Texas Instruments and Xilinx.

Alexandre Sébastien Julien Levisseمشاهده پروفایل

مدرس

• Computer Architecture
• VLSI Design
• Low-Power Electronics
• +۴ مورد دیگر

Alexandre Sébastien Julien Levisse is a Lecturer at the Institute of Electrical Engineering within EPFL's School of Engineering, with additional roles as System Specialist in PAT/SEL departments and Scientist in IEM. His work centers on energy-efficient hardware architectures for edge computing and AI applications. Research focuses on: Computer Architecture & VLSI Design Low-Power Electronics for edge devices Emerging Memory Technologies (RRAM, OxRAM) Neuromorphic & Approximate Computing In-Memory/ Near-Memory Computing Edge AI Hardware Acceleration His 2022-2025 publications reveal strong emphasis on specialized edge AI hardware, including near-DRAM architectures (SideDRAM), RISC-V microcontrollers for healthcare (HEEPOcrates), and overflow-free memory systems. Key innovations involve hardware-software co-design for energy efficiency, variable precision computation, and novel memory hierarchies targeting wearable sensors and edge inference. Levisse teaches Fundamentals of VLSI Design and Lab in Advanced VLSI Design at EPFL. He actively contributes to digital education as a member of EPFL's Centre for Digital Education (CCE), developing curricula for next-generation hardware engineers.

Michał Kowalewskiمشاهده پروفایل

استادیار

• Embedded Systems
• Wireless Sensor Networks
• Metrology
• +۳ مورد دیگر

Dr. Michał Kowalewski serves as an Assistant Professor at the Department of Metrology and Electronic Systems within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His research bridges theoretical electronics with practical embedded systems applications, focusing on metrological solutions for industrial and sensor networks. His primary research domains include Embedded Systems (specializing in microcontroller programming with ANSI C and AVR Assembler), Wireless Sensor Networks (particularly Z-Wave protocol implementations), Metrology (evaluating accuracy, linearity, and resolution in measurement systems), and Neural Networks for Sensor Applications . He has pioneered methods for random signal generation using DACs/ADCs, developed neural classifiers for corrosion modeling, and engineered Z-Wave-based measurement systems with mesh networking capabilities. Analysis of his 2015-2018 publications reveals a consistent trajectory toward wireless distributed measurement systems, with increasing emphasis on neural network integration for fault diagnosis and sensor classification. His work demonstrates strong interdisciplinary connections between analog circuit design, wireless communication standards, and machine learning applications in industrial metrology. Dr. Kowalewski frequently collaborates with researcher Z. Czaja on projects involving noise generation and analog circuit testing, though specific grant details remain unreported. His technical contributions span both theoretical frameworks (e.g., TCBF classifiers) and practical implementations (e.g., USB Z-Wave controllers using OpenZWave library in C++).

• Machine Learning
• Deep Learning
• AI Safety
• +۵ مورد دیگر

Saikat Barua is a Senior Researcher at North South University in Dhaka, Bangladesh, affiliated with the Department of Electrical Engineering and Computer Science. His research focuses on designing intelligent systems aligned with human values, aiming to create beneficial AI that collaborates with humanity for a better future. With expertise spanning Machine Learning, Deep Learning, AI Safety, Quantum Error Correction, and Natural Language Processing, Barua contributes significantly to advancing artificial intelligence with strong emphasis on ethical and practical applications. Barua's research centers on developing transparent, reliable, and human-centered AI systems across multiple cutting-edge domains. His work in explainable AI (XAI) addresses the critical need for interpretability in complex machine learning models, while his investigations into quantum machine learning explore novel approaches to hybrid quantum-classical systems. He actively researches autonomous agents and large language models, examining their security vulnerabilities and potential for beneficial societal impact. A recurring theme in his work is bridging the gap between sophisticated AI capabilities and human understanding, ensuring technologies remain accessible and trustworthy. His publication record reveals a strategic focus on making AI more transparent, secure, and energy-efficient across diverse applications. Barua has developed integrated environments for knowledge analysis (KAXAI), energy-efficient medical imaging frameworks (ELMAGIC), and quantum error correction techniques (RESCUED). His recent work increasingly addresses the security challenges of agentic systems and the practical implementation of quantum machine learning. The trajectory of his research demonstrates consistent progression from foundational AI techniques toward increasingly complex, interdisciplinary applications with real-world impact. As an active researcher with nine publications accumulating over 11,988 reads and 14 citations, Barua engages deeply with the scientific community through ResearchGate. His research questions explore critical intersections of AI with healthcare empathy, machine learning data collection, human resource management, and responsible research practices. This comprehensive engagement reflects his commitment to advancing both the technical frontiers of AI and its thoughtful integration into societal frameworks, positioning him as a thoughtful contributor to the evolving landscape of artificial intelligence research.