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Giovanni BeltrameView profile

Professor

• Intelligent Systems
• Embedded Systems
• Aerospace
• +1 more

Giovanni Beltrame is a Professor at Polytechnique Montréal's Department of Computer and Software Engineering, where he directs the MIST Laboratory. His work bridges academic research and aerospace engineering applications. Education: M.Sc. in Electrical Engineering and Computer Science, University of Illinois, Chicago (2001) Laurea in Computer Engineering, Politecnico di Milano (2002) MS in Information Technology, CEFRIEL, Milan (2002) Ph.D. in Computer Engineering, Politecnico di Milano (2006) Research Focus: His work spans four interconnected domains: Intelligent Systems (swarm robotics, distributed planning, SLAM), Embedded Systems (hardware/software modeling and verification), Aerospace (avionics, radiation-hardened systems), and Optimization (multi-objective algorithms, parallel programming). These areas converge in space-system applications and fault-tolerant computing. Leadership: As Principal Investigator, he leads multiple government and industry-funded projects. He actively recruits researchers through the MIST Laboratory's structured onboarding process, requiring candidates to demonstrate prior engagement with lab materials. Teaching: He instructs specialized courses including Swarm Intelligence (INF6593ME) and Space Systems Computing (AER8300), covering topics from microprocessor architecture to spacecraft data processing design. Lab Operations: The MIST Laboratory serves as the hub for his research activities, with documented procedures for student recruitment and project collaboration in swarm intelligence and embedded aerospace systems.

Chistyakov Gennady NikolaevichView profile

Associate Professor

• Electrical Engineering
• Power Systems
• Renewable Energy
• +4 more

Gennady Nikolaevich Chistyakov is an Associate Professor at the Department of Electric Power Engineering, Mechanical Engineering and Automobile Transport at Khakassian Technical Institute (branch of Siberian Federal University). With over 42 years of work experience, he teaches subjects including electromagnetic compatibility, relay protection, and mathematical problems of energy. His research focuses on power systems, with emphasis on renewable energy integration, geomagnetic storm impacts, and transient analysis. Recent publications highlight solar power optimization and protection device reliability. 2021: Small solar power plant analysis for Khakassia 2019: Relay protection during geomagnetic storms 2018: Overvoltage pulse experiments Scientific Awards: 2015: KhTI Diploma 2015: Ministry of Education and Science of Khakassia Certificate 2007: Russian Federation Honorary Worker of Higher Professional Education He has led multiple RFBR and Khakassia Republic grants (2013-2016) on power quality optimization and reliability. Advanced training includes e-learning technologies, cloud systems, and inclusive education.

Rainer LienhartView profile

Professor

• Computer Vision
• Machine Learning
• Deep Learning
• +5 more

Rainer Lienhart is a tenured Professor at the University of Augsburg, where he holds the Chair for Machine Learning & Computer Vision within the Faculty of Applied Computer Science's Institute of Computer Science. He has served as the executive director of the Institute for Computer Science since April 2010. His research group, the Machine Learning and Computer Vision Lab (MLCV Lab), focuses on large-scale image, video, human pose, sensor and data mining algorithms; object, human pose and action detection/recognition; and image, video, human pose and action retrieval. Dr. Lienhart received his PhD in Computer Science from the University of Mannheim, Germany in 1998. Prior to joining the University of Augsburg, he worked as a Staff Researcher at Intel's Microprocessor Research Lab in Santa Clara, California from August 1998 to July 2004. He has also taken sabbaticals at FXPAL (August 2017 to March 2018) and Willow Garage (2009). His research spans multiple areas of computer vision and machine learning with particular emphasis on object detection/recognition, human pose estimation, image/video captioning, automated visual inspection, medical image analysis, deep learning, statistical computing, and explainable AI. His work on multimedia data mining and signal processing has led to significant contributions in video content analysis, including text detection/recognition, commercial detection, face detection, shot and scene detection, and automatic video abstraction. The publication record shows a consistent research trajectory focusing on human pose estimation, winter sports analysis, scene graph generation, and segmentation techniques, with recent work emphasizing transformer-based architectures, 3D pose estimation, and physics-informed computer vision approaches. His research demonstrates a strong interdisciplinary focus, connecting computer vision with sports science, medical applications, and multimedia content analysis. Prof. Lienhart has served as general co-chair of ACM Multimedia 2017 and 2007, as well as SPIE Storage and Retrieval of Media Databases 2004 and 2005. He has served on editorial boards of three international journals and was vice chair of SIGMM from July 2009 to June 2017. His professional service includes committee membership for major conferences including ACM Multimedia, IEEE ICME, and SPIE Storage and Retrieval of Media Databases. His laboratory, the MLCV Lab, maintains an active research program with numerous collaborators and students working on cutting-edge computer vision problems. Current research directions include human pose estimation in sports contexts, winter sports equipment segmentation, scene graph generation, and medical image analysis applications.

Marius RosenbaumView profile

Lecturer

• Embedded Systems
• Avionics
• Flight Control Systems
• +3 more

Dr. Marius Rosenbaum is a Lecturer at the Faculty of Mathematics and Computer Science of FernUniversität in Hagen. Located in Room H113, Building 3, he teaches courses including Application-Oriented Microprocessors, Embedded Systems, FPGA programming, and seminars on Modeling/Simulation and Aviation Digitalization. His examinations are conducted in written format. Research interests focus on aviation technology and embedded systems, with emphasis on: Flight assistance systems (glide path calculation, emergency landing field detection) AI applications in avionics (neural networks for traffic forecasting) Distributed computing (Kubernetes-based neural architecture search) Sensor-based guidance systems (Lidar, multi-modal image processing) His publications (2017-2025) demonstrate strong thematic coherence around aviation safety systems, integrating computer vision, path planning algorithms, and machine learning. Recent works explore mixed reality interfaces for pilot assistance and real-time glide path optimization. He actively supervises student theses, with 2024 projects including electric skateboard control systems, flight simulator plugins, speech recognition for air traffic, and ARM processor design. Collaborative research involves colleagues like Wolfgang Schiffmann and Alexander Klos in projects spanning emergency landing systems and neural architecture frameworks.

Matthias FertigView profile

Professor

• Digital Systems
• Microprocessor Architecture
• VHDL Design
• +6 more

Professor Matthias Fertig serves as Professor of Digital Systems at the Faculty of Electrical Engineering and Information Technology, Konstanz University of Applied Sciences. His academic profile bridges theoretical research with practical engineering applications in digital systems design. His research portfolio spans several critical domains: Near-/In-Memory Computing (Universal Memory Automata theory) Digital HDL Design methodology (RAPID VHDL package development) Massively Parallel EM-Simulation optimization Computational Optics using advanced Fourier methods (WPM/VWPM) ASIC design and implementation workflows Prior to academia, Professor Fertig gained substantial industry experience at IBM (microprocessor design), Dialog Semiconductor (Power Management ICs), and Volvo Construction Equipment (control systems for heavy machinery). This background informs his practical teaching approach that emphasizes real-world applications alongside theoretical foundations. His professional recognition includes an invitation to join the Editorial Board of the American Journal of Computer Science and Technology (AMJCST) in May 2025. Professor Fertig actively develops new course content, with a 'uProcessor Architecture' course scheduled for summer term 2026. He teaches across the curriculum from undergraduate Digital Engineering courses through specialized Master's level laboratories in Silicon Photonics and Electromagnetic Simulation, utilizing industry-standard Cadence tools to provide students with professional design experience.

• Machine Vision
• 3D-camera design
• Real-time image processing
• +5 more

Professor Stephan Hußmann is a faculty member at the West Coast University of Applied Sciences (FHW) in the Department of Microprocessor Technology and Electronics within the Faculty of Engineering. He has been a full-time Professor at FHW since December 2004, after working as a Lecturer at the University of Auckland from 2001-2003 and as a project leader for PMDTec GmbH in 2004. His research interests focus on Machine Vision applications, 3D-camera design, real-time image processing, embedded systems design, and automation in agriculture and forestry applications. Hußmann has developed innovative optical multi-sensor systems for quality control and inspection, with particular emphasis on drone-based AI sensor systems for agricultural applications in times of climate change. His work bridges theoretical research with practical industrial applications, particularly in the organic farming sector. Analysis of his recent publications reveals a strong trend toward drone-based agricultural applications, with significant focus on weed detection and control using deep learning approaches. His research spans multiple disciplines including computer vision, robotics, agricultural engineering, and real-time processing systems. The majority of his recent work focuses on practical implementations for organic farming challenges, demonstrating a consistent commitment to solving real-world agricultural problems through technological innovation. Top Twenty Faculty Teachers award (2002) Best Lecturer-Computer Systems Engineering Department award (2003) Senior member of IEEE (since 2011) Professor Hußmann has supervised numerous PhD, Master's, and Bachelor's students, with a particular focus on practical applications in machine vision and agricultural technology. His research has been supported by significant funding, including multiple projects from the Federal Ministry of Education and Research (BMBF) totaling over 8.2 million euros. Current major projects include drone-based AI sensor systems for agriculture in times of climate change, water rescue drones, and aerial photogrammetric surveys. He co-founded the Machine Vision Technology Institute (Ma.Vi.Tec) in 2009, which later became eyespec GmbH, and is the acting chairman of the registered association Initiative Bildverarbeitung e.V. Since 2018, he has led the FHW research group 'Digitalization in Agriculture and Forestry,' which resulted in the founding of naiture® GmbH & Co. KG in 2018. His teams regularly collaborate with industry partners through the Initiative Bildverarbeitung e.V., which organizes lectures where industry and university members discuss potential joint projects.

• Communication Systems
• Digital Signal Processing
• Digital Circuit Technology
• +4 more

Prof. Georg Schmidt is a Professor at Esslingen University of Applied Sciences since 2011, specializing in communication systems, digital technology, and coding theory. He holds a PhD in algebraic decoding of Reed-Solomon codes and has extensive industry experience, including roles at Ubidyne GmbH and the University of Ulm's Institute of Telecommunications Technology. His research interests span digital signal processing, embedded systems security, and error-correcting codes. He lectures on advanced channel coding and serves on the DV and Foreign Affairs Committees. Education: 1994–2000: Studied Electrical Engineering at the University of Ulm, focusing on systems engineering, communications, and network technology. Doctorate: Algebraic decoding of Reed-Solomon codes over half the minimum distance (University of Ulm). Research Focus: Communication systems and digital signal processing. Coding theory (e.g., Reed-Solomon codes, expander codes). Data security and embedded systems. Motor control and delta-sigma modulation techniques. Recent Publications Trends: Recent work emphasizes practical applications like Bluetooth Low Energy systems, energy harvesting, and advanced motor control algorithms, complementing foundational research in coding theory and error correction. Awards & Grants: No specific awards or grants listed. Active in patenting (e.g., antenna arrays, calibration methods, and energy systems). Advising & Labs: No student advisees listed. Engaged in collaborative projects on coding and industrial communication at Esslingen’s engineering faculty.

• Embedded Systems
• Microprocessor Technology
• Autonomous Driving
• +5 more

Jakob Czekansky is a Lecturer for Special Tasks at the Technical University of Central Hesse (THM) , affiliated with the Department of Mathematics, Natural Sciences and Computer Science (MNI) and the Institute of Technology and Computer Science . He holds an M.Sc. in Engineering and Computer Science (2020) and a B.Sc. in Computer Science Engineering (2018), both from THM. His research focuses on embedded systems , autonomous driving , and remote laboratory technologies . He leads the MICRO project—a virtual microprocessor lab—and has collaborated on industrial projects like a ZIM-funded wood analysis system with Rinntech-Metriwerk GmbH. Key interests include: Microcontroller development Edge computing for autonomous vehicles Hybrid lab infrastructure Computer vision applications He supervises student theses in embedded systems, distributed software, and quantum computing visualization. As a member of the International Association of Online Engineering (IAOE) and Global Online Laboratory Consortium , he promotes remote-access education tools.

Michael ĆurčićView profile

Professor

• Microelectronic Sensors
• Electromagnetic Compatibility
• Microprocessor Technology
• +6 more

Prof. Dr. Michael Ćurčić is a Professor for Microelectronics/Microsystem Technology, specializing in Sensor Technology and Actuators, at Hochschule Düsseldorf (University of Applied Sciences) since 2023. His career spans academia and industry, with prior roles as a Research Scientist and MEMS System Architect at Robert Bosch GmbH, where he focused on sensor design and protection mechanisms. PhD in Physics from Max Planck Institute for Intelligent Systems Postdoctoral work at BESSY II and ALS 20+ patents in MEMS technology His research concentrates on magnetic vortex dynamics, MEMS security against infrared threats, and nonlinear dynamical system modeling. Notably, he received the Best Paper Award at Smart System Integration 2017 for MEMS gyroscope fingerprinting work. He has co-authored over 15 publications in magnetic and microsystem technologies, with a focus on spintronics, sensor design, and nanomagnetic structures. Scientific Awards: Best Paper Award Winner SSI 2017

Manfred OlschewskiView profile

Researcher

• Virtual Reality
• Plant Planning
• Visualization Technology
• +3 more

Manfred Olschewski is a Researcher in the Department of Design at Düsseldorf University of Applied Sciences. His work focuses on virtual reality applications, physical computing, and electrical engineering fundamentals. Teaching: Leads the course 'Introduction to Virtual Reality' and oversees projects in the Physical Computing Lab and Virtual Reality Lab. Research: Specializes in VR simulators for industrial applications and microprocessor-based electronics education. Labs: Manages technical equipment in the Physical Computing Lab (00104) and VR Lab (02202), including Arduino, Raspberry Pi, and soldering/measurement tools.

Winfried GehrkeView profile

Professor

• Digital Systems
• Microprocessor Technology
• Embedded Systems
• +3 more

Prof. Dr.-Ing. Winfried Gehrke is a faculty member at the Faculty of Engineering and Computer Science of Osnabrück University of Applied Sciences. He leads the Laboratory for Digital and Microprocessor Technology, focusing on applications in microcomputer systems and digital electronics. His work primarily involves technical education and applied research in computational engineering disciplines. Key affiliations include: Osnabrück University of Applied Sciences (Faculty of Engineering and Computer Science) His research centers on digital systems and microprocessor technology, with applications in industrial computing and embedded systems development.

Rainer HöckmannView profile

Researcher

• Digital Technology
• Microprocessor Systems
• FPGA Accelerators
• +4 more

Rainer Höckmann is a Researcher at the Laboratory for Digital and Microprocessor Technology , part of the Faculty of Engineering and Computer Science at Osnabrück University of Applied Sciences . Since 2008, he has focused on digital systems, FPGA accelerators, and wireless network concepts. Education: Diplom-Ingenieur (FH) in Computer Science (2006) Research interests include: Digital and microprocessor technology FPGA-based hardware acceleration Embedded microcomputing systems Compiler construction and sensor technology Wireless network relaying strategies Quality-of-service mechanisms in telecom networks His publication trends show expertise in: Cooperative relaying topologies Multimedia broadcasting enhancements Portable FPGA design frameworks Next-gen network concepts Teaching activities include: Bildgebende Sensortechnik Compilerbau Digitaltechnik Embedded Systems Hardware/Software Co-Design Rechnerarchitektur Professional projects : HPVis visual data project (2012-2014) C-MOBILE (mobile multicast/broadcast) C-CAST (context-dependent data transport)

• Computational Neuroscience
• Biomechatronics
• Bio-inspired Robotics
• +5 more

Dr. Hanno Gerd Meyer is a Postdoctoral Fellow at the Faculty of Engineering, University of Bielefeld, working with the Center for Cognitive Interaction Technology (CITEC) and the Research Group Biomechatronics since January 2016. His research focuses on understanding insect visual systems and developing bio-inspired camera systems for robotic platforms. Dr. Meyer received his PhD in Computational Neuroscience from Bielefeld University in February 2014 with his dissertation titled 'Representation of Visual Motion Information in the Fly Brain'. His academic background includes an International Master's program in 'Systems Biology of Brain and Behavior' (2008-2010) and undergraduate studies in Biology and Psychology (2003-2008), all at Bielefeld University. His research centers on how flying insects like flies and bees use their visual systems for course control, collision avoidance, and spatial navigation. Despite having relatively few neurons and poor spatial resolution compared to artificial systems, insect visual systems demonstrate remarkable speed, flexibility, and resource efficiency. Dr. Meyer's work aims to translate these biological principles into engineering applications for robotic vision systems. He collaborates with the Cognitronics group at CITEC to develop algorithms on dynamically reconfigurable hardware combined with low power microprocessors. These algorithms extract motion information from optic flow to enable robotic agents to perform visually-guided orientation behavior in unfamiliar terrain based on principles found in insect neurobiology. Dr. Meyer has been actively involved in research at Bielefeld University since 2010, progressing from Scientific Assistant positions in the Department of Neurobiology to his current Postdoctoral Fellowship. His work contributes to Bielefeld's Socio-Technical World strategic research area, which focuses on capabilities enabling agents like humans, robots, and AI to act and communicate in complex environments.

• Computer Architecture
• VLSI Design
• Hardware Testing and Verification
• +3 more

Subhasish Mitra is a Professor in the Department of Electrical Engineering and by courtesy in Computer Science at Stanford University’s School of Engineering. His pioneering work focuses on creating robust, error-tolerant hardware systems through the Resilient Silicon paradigm, addressing critical challenges in modern microprocessors and memory design. Education Ph.D. in Electrical Engineering, Stanford University, 1999 B.Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1994 His research spans Computer Architecture , VLSI Design , and Hardware Security , with breakthroughs in defect-tolerant circuits and aging-induced error mitigation. Mitra’s work bridges theoretical innovation and industrial adoption, notably in Intel’s high-volume manufacturing processes. Key recognitions include: IEEE Fellow (2015) for “contributions to design and test of robust microprocessors” ACM Fellow (2015) for foundational reliability frameworks Phil Kaufman Award (2020), EDA’s highest honor He leads Stanford’s Robust Systems Group with sustained funding from NSF, DARPA, and semiconductor industry partners, driving next-generation secure hardware for AI accelerators and IoT devices.

Jan RichlingView profile

Professor

• Microprocessor systems
• Embedded systems
• Real-time systems
• +3 more

Prof. Dr.-Ing. habil. Jan Richling serves as a Professor in the Department of Electrical Engineering and Information Technology at South Westphalia University of Applied Sciences in Hagen, Germany. Based in Room H.318 at Haldener Straße 182 (58095 Hagen), he maintains active academic engagement with consultation hours by appointment and can be contacted via phone (+49 2331 9330-6219) or email (richling.jan@fh-swf.de). His research expertise spans critical domains in computer engineering, with particular focus on: Microprocessor architecture and design Embedded system optimization Real-time operating environments Network protocol implementation Energy-efficient computing solutions Fail-safe system reliability These interconnected fields address modern challenges in efficient, robust computing infrastructure. Prof. Richling's teaching portfolio includes foundational and advanced courses such as Microcontroller Systems, Computer Organization, Operating Systems, IP Networks Programming, and Fail-safe Systems (a compulsory elective), directly reflecting his research specializations. No information regarding scientific awards, graduate student supervision, research grants, or laboratory facilities was provided in the source material.