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• 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.