جستجوی استاد راهنمای دانشگاهی

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.

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 .

• Automotive Electronics
• IoT Applications
• Microcontroller Systems
• +۸ مورد دیگر

Prof. Dr. rer. nat. Felix Hüning is a full-time professor at FH Aachen - University of Applied Sciences , affiliated with the College of Electrical Engineering and Information Technology . He teaches courses in Vehicle Systems and Fundamentals of Electrical Engineering and leads research in automotive electronics, microcontroller systems, and electromobility. Key Affiliations: Professor, Fachbereich 5 - Elektrotechnik und Informationstechnik Prodekan für Studium und Lehre Research Interests focus on: Embedded systems for automotive and IoT Microcontroller architectures In-vehicle bus communication Autonomous driving technologies Electronics for automation and propulsion Contact: huening@fh-aachen.de | Office: Room O05009, Hohenstauffenallee 10, 52066 Aachen

• Biophotonics
• Super-resolution Microscopy
• Open-source Scientific Hardware
• +۵ مورد دیگر

Benedict Diederich is a researcher at the Leibniz Institute of Photonic Technology , leading the Open-Source Instrumentation working group. His work focuses on democratizing advanced microscopy through affordable, reproducible hardware and software solutions. Develops open-source microscope systems (UC2 platform) Specializes in super-resolution and automated imaging Advocates for accessible lab automation Integrates 3D printing and consumer electronics Recent publications highlight innovations in structured illumination microscopy, portable ESPressoscope systems, and microfluidic particle sorting. His work bridges optical engineering, computational imaging, and open science principles. Key article trends include: Modular designs for microscopy upgrades Cost-reduction strategies (e.g., UC2, ESPressoscope) Integration of real-time feedback loops Reproducibility-focused documentation Applications in live-cell imaging and environmental monitoring Emphasis on accessibility for resource-limited settings

• Embedded Systems
• Cyber Physical Systems
• IoT Design
• +۳ مورد دیگر

Martin Streitenberger serves as a Professor in the Department of Electrical and Information Engineering at Hannover University of Applied Sciences and Arts, with his office located in room 1B.0.02 at Ricklinger Stadtweg 120, Hannover, and contactable via phone (+49 511 9296 1281) and email. His research expertise spans critical domains in modern engineering: Embedded Systems and Cyber Physical Systems integration IoT Design methodologies and implementation Digital Technology and Microprocessor Technology Microcontroller System Design and real-world applications No scientific awards were documented in the source material. Information regarding graduate student supervision, research funding, or laboratory affiliations was not provided in the available institutional profile.

• Automation
• Robotics
• Signal Processing
• +۵ مورد دیگر

Michael Kleer is a Professor at the College of Engineering, Saarland University of Applied Sciences. His academic focus lies in Automation and Robotics , with teaching responsibilities spanning courses such as Signal and Image Processing , Microcontrollers and Applications , and Industrial Robotics . Contact: Room 7206, Goebenstraße 40, 66117 Saarbrücken, Germany Phone: +49 (0)681 5867-216 Email: michael.kleer@htwsaar.de Office Hours: By appointment His research interests align with his teaching, emphasizing technical applications in: Automation systems Industrial robotics Microcontroller-based solutions Kinematic modeling

• RFID Technology
• Internet of Things (IoT)
• Wireless Sensor Networks
• +۳ مورد دیگر

Luca Catarinucci is affiliated with the University of Salento in Lecce, Italy. His research focuses on RFID technology, IoT systems, wireless sensor networks, and antenna design. He has collaborated extensively with researchers like Riccardo Colella and Luciano Tarricone, producing impactful work in smart healthcare systems, energy-autonomous sensors, and 3D-printed electromagnetic devices. His contributions span theoretical advancements in circuit design and practical applications in fields like environmental monitoring and biomedical research. Recent work emphasizes energy-efficient solutions and integration of AI-driven microcontrollers. Key research interests include improving RFID tag performance, developing IoT-aware architectures for healthcare, and advancing additive manufacturing techniques for antenna prototyping. His publications reflect a deep engagement with both hardware innovation and system-level integration of smart technologies. Notable projects include energy-autonomous parking sensors and novel RFID-based medical monitoring systems. Collaborations involve cross-disciplinary efforts in electrical engineering, computer science, and biomedical engineering, with applications ranging from industrial automation to personalized healthcare solutions. While no formal awards are listed, his prolific publication record and repeated funding of experimental platforms indicate significant academic influence.

• Cybersecurity
• Cyber-physical systems security
• Social network analysis
• +۷ مورد دیگر

Andrey Chechulin is a Professor at the St. Petersburg Federal Research Center of the Russian Academy of Sciences, Institute of Informatics Problems, where he leads research in cybersecurity within the Information Security Department. His work spans over 15 years with more than 80 publications in top-tier security conferences and journals. Dr. Chechulin's primary research interests include cybersecurity, cyber-physical systems security, social network analysis, and bot detection. His work focuses on developing practical methodologies for incident investigation, access control, and vulnerability assessment. He has pioneered approaches for analyzing social media bots, particularly on the VKontakte platform, and developed innovative frameworks for cryptocurrency transaction anomaly detection using neural networks. His publication record shows consistent contributions to major security venues including PDP, COMSNETS, and Sensors, with a notable increase in output since 2018. Recent work demonstrates his adaptation to emerging security challenges in AI-generated content detection and blockchain security. Best Paper Award at PDP 2021 Cybersecurity Research Excellence Award (2019) Dr. Chechulin maintains strong collaborative relationships with Igor V. Kotenko (60 joint publications), Dmitry Levshun, and Maxim Kolomeets. His research often bridges theoretical security concepts with practical implementations for real-world systems, including smart city infrastructure and automotive security applications.

Rainer Müllerمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Embedded Systems
• Operating Systems
• +۳ مورد دیگر

Rainer Müller is a Researcher in the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander University Erlangen-Nuremberg. His work focuses on real-time operating systems (RTOS), embedded systems, and hardware-accelerated scheduling techniques. His research emphasizes safety-critical systems, multi-core architectures, and compliance with automotive standards like AUTOSAR and OSEK. Key research contributions include the Sloth RTOS framework, which leverages hardware-based scheduling and memory protection mechanisms. Müller has collaborated on projects involving Infineon TriCore processors and ARM Cortex-M3 microcontrollers. His teaching responsibilities include system-level programming in C and internship supervision in applied systems software engineering. Publications highlight advancements in multi-core RTOS design, memory protection for safety-critical systems, and time-triggered scheduling algorithms. He has advised multiple theses on topics such as task isolation, communication interfaces for Intel Xeon Phi coprocessors, and OSEK-compliant kernel implementations. His research lab is part of the broader Computer Science 4 group, specializing in distributed systems and operating systems. Collaborations with industry partners (e.g., Infineon) underscore his focus on practical embedded system solutions.

Christian Heidornمشاهده پروفایل

پژوهشگر

• Deep Learning
• Hardware-Software Co-Design
• Neural Networks
• +۵ مورد دیگر

Christian Heidorn is a Researcher at the Chair of Computer Science 12 (Hardware-Software Co-Design) within the Department of Computer Science at Friedrich-Alexander University Erlangen-Nürnberg (FAU), Germany. He has held this position since 2018 and teaches "Fundamentals of Computer Engineering" regularly across multiple semesters. His educational background includes an M.Sc. in Medical Engineering (2015-2018) and a B.Sc. in Medical Engineering (2012-2016), both from FAU. Born in 1989 in Dachau, Germany, he maintains an office in Room 02.128 at Cauerstr. 11, Erlangen. Dr. Heidorn's research focuses on the Application of Deep Learning on Tightly Coupled Processor Arrays and Invasive Computing . His work bridges medical engineering with computer architecture, particularly emphasizing neural network deployment on specialized hardware. His research projects include OpTC and KISS Invasive Computing, which optimize neural networks for embedded systems and processor arrays. His recent publications demonstrate a strong trend toward efficient neural network deployment on embedded systems, with emphasis on automotive applications (AURIX microcontrollers), hardware-aware neural network pruning, and processor array optimization. His work spans both theoretical neural architecture search and practical implementations for real-world applications. His notable scientific contributions include: Development of the OpTC toolchain for neural network deployment on automotive microcontrollers Hardware-aware evolutionary filter pruning techniques for CNNs ALPACA: An accelerator chip design for nested loop programs Efficient mapping of CNNs onto tightly coupled processor arrays Dr. Heidorn has supervised numerous Master's and Bachelor's theses on topics ranging from neural network compression to robotic hand control using EMG data and processor array optimization. His advising reflects his dual expertise in medical engineering and computer architecture, with many projects focusing on practical embedded applications of deep learning. He is actively involved in research projects related to invasive computing and tightly coupled processor arrays, with a particular focus on making deep learning more accessible on resource-constrained devices for automotive and medical applications.

• Electronic Design Automation (EDA)
• RISC-V Architecture
• TinyML (Tiny Machine Learning)
• +۳ مورد دیگر

Philipp van Kempen is a researcher at the Chair of Design Automation (Prof. Schlichtmann) at the Technical University of Munich. His work focuses on electronic design automation, specifically targeting RISC-V architecture, TinyML optimization, and LLVM compiler infrastructure for custom hardware accelerators. Key Research Areas: RISC-V ISA extensions, autovectorization, neural network accelerators, and compiler toolchain automation. Collaborations: Works with Daniel Mueller-Gritschneder, Ulf Schlichtmann, and Jefferson Parker Jones. His recent publications highlight contributions to benchmarking TinyML CNN kernels on RISC-V vector hardware, developing semi-automated LLVM support for ISA extensions, and optimizing TinyML inference through frameworks like MLonMCU and muRISCV-NN.

• Control Engineering
• Automated Driving
• Trajectory Planning
• +۳ مورد دیگر

Samuel Zeitler, M.Sc., is a Research Associate at the Chair of Automatic Control within the School of Engineering and Design at the Technical University of Munich (TUM). His work focuses on trajectory planning in automated driving and control engineering applications. He is based in Garching bei München, Germany, and contributes to teaching and research in systems theory and mechatronics. Education: M.Sc. in Munich (2024) B.Sc. at the University of Bayreuth (2021) Research Interests: Samuel specializes in control engineering, with a focus on automated driving systems, trajectory planning, and nonlinear control strategies. His work intersects with mechatronic systems and energy-based modeling techniques. Teaching Contributions: He supports lectures and practical courses at TUM, including "Modern Methods of Control Engineering 2," "Controller Implementation on Microcontrollers," and experiments like the "Multi-tank system" in the summer semester. Laboratory Affiliation: Samuel is part of the Chair of Automatic Control (Prof. Boris Lohmann) at TUM, which engages in advanced research topics such as parametric control, model order reduction, and port-Hamiltonian systems.

Mario Neugebauerمشاهده پروفایل

استاد

• Wireless Sensor Networks
• Mobile Systems
• Robotics
• +۴ مورد دیگر

Prof. Dr.-Ing. Mario Neugebauer is a faculty member at the Faculty of Computer Science/Mathematics at Dresden University of Applied Sciences (HTW Dresden). His teaching areas span fundamental programming, database systems, mobile networks, and communication technologies. Research Focus: Off-road navigation, wearable systems for production/logistics, localization systems, and mobile sensor devices. Thesis Topics: Image analysis for bird conservation, shadow detection on wind turbines, bat monitoring, and mission planning for autonomous robots. Technologies: Rust, ROS2, Kotlin/Spring Boot, Python, Raspberry Pi, C/C++ for microcontrollers, and IEEE 802.15.4 protocols. Teaching Responsibilities: Courses include Programming I/II , Mobile Networks , and Business Informatics and Digitization for Informatik, Medieninformatik, and Umweltmonitoring programs.

Daniele Ottavianoمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Embedded Systems
• Virtualization
• +۴ مورد دیگر

Daniele Ottaviano is a Researcher at the Technical University of Munich (TUM) , affiliated with the Faculty of Mechanical Engineering and the Chair of Cyber-Physical Systems in Production Engineering . His work focuses on real-time virtualization , mixed-criticality systems , and embedded systems , particularly in optimizing memory hierarchies and managing heterogeneous processing elements including FPGA-based architectures . Education : Ph.D. in Fusion Science and Engineering (University of Padua & University of Naples Federico II, 2025), M.Sc. in Computer Engineering (University of Naples Federico II, 2021), B.Sc. in Computer Engineering (University of Naples Federico II, 2019). Prior Role : Visiting Researcher at Boston University's Cyber-Physical Systems Lab (2023-2024). His research investigates cache partitioning techniques , real-time virtualization for MPSoCs , and FPGA integration to enhance performance, isolation, and predictability in embedded systems. Publications highlight contributions to hypervisor optimization , container orchestration , and virtualization frameworks for mixed-criticality environments.

• Embedded Machine Learning
• Neural Architecture Search
• Signal Processing
• +۴ مورد دیگر

Christopher Ringhofer serves as a Researcher and PhD candidate at the Intelligent Embedded Systems department within the Faculty of Engineering and Computer Science at the University of Duisburg-Essen since April 2020. His work focuses on developing energy-efficient AI solutions for embedded platforms with current projects funded by the German Federal Ministry of Education and Research. He earned his BSc in Applied Informatics (2017) and MSc in Distributed Dependable Systems (2020) from the same institution, following three years of industry experience in IoT development at ithinx GmbH. His doctoral research centers on automated neural architecture search for signal processing on constrained devices. Ringhofer's research explores evolutionary algorithms for constructing latency-optimized neural networks targeting microcontrollers and embedded FPGAs, with primary applications in digital audio processing for studio/live environments. His work bridges hardware constraints with deep learning requirements through techniques like precomputed convolutional layers and hardware-aware NAS. He actively contributes to academic instruction through the Bachelor's course 'Embedded Systems' and specialized student projects on 'AI-based Neurosignal Processing', maintaining consistent teaching involvement since Winter Semester 2020/21. Current research projects include 'TransfAIr: Transfer Approaches for Artificial Intelligence in Industry' (since May 2024) and previous work on 'LUTNet' and 'KI-LiveS' initiatives. His technical contributions focus on the IoT Garage infrastructure and Elastic AI ecosystem development for pervasive computing environments.