F. Simon-Mertens, Effizienzanalyse leichtgewichtiger Neuronaler Netze für FPGA-basierte Modulationsklassifikation. 2023.

A. Sprenger, Testinstrumente und Testdatenanalyse zur Verarbeitung von Unsicherheiten in Logikblöcken hochintegrierter Schaltungen. Paderborn: Universität Paderborn, 2023.

T. Hansmeier, XCS for Self-awareness in Autonomous Computing Systems. 2023.

Q. A. Ahmed, Hardware Trojans in Reconfigurable Computing. Paderborn:  Paderborn University, Paderborn, Germany, 2022.

L. M. Witschen, Frameworks and Methodologies for Search-based Approximate Logic Synthesis. 2022.

F. Mehlich, An Evaluation of XCS on the OpenAI Gym. Paderborn: Paderborn University, 2022.

V. I. Tcheussi Ngayap, FreeRTOS on a MicroBlaze Soft-Core Processor with Hardware Accelerators. 2022.

T. Wiersema, Guaranteeing Properties of Reconfigurable Hardware Circuits with Proof-Carrying Hardware. Paderborn: Paderborn University, 2021.

C. Kashikar, A Comparison of Machine Learning Techniques for the On-line Characterization of Tasks Executed on Heterogeneous Compute Nodes. Paderborn: Paderborn University, 2021.

J. W. Rehnen, Decomposition of Arithmetic Components for the Approximate Circuit Synthesis with EvoApproxLib. 2021.

M. Brede, Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn: Paderborn University, 2021.

M. A. Sheikh, Design and Implementation of a ReconROS-based Obstacle Avoidance System. Paderborn University, 2021.

K. Chandrakar, Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis. 2020.

L.-S. Henke, Evaluation of a ReconOS-ROS Combination based on a Video Processing Application. 2020.

S. Thiele, Implementing Machine Learning Functions as PYNQ FPGA Overlays. 2020.

V. Jaganath, Extension and Evaluation of Python-based High-Level Synthesis Tool Flows. 2020.

F. P. Jentzsch, Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture. 2020.

M. Keerthipati, A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking. Universität Paderborn, 2019.

N. S. Sabu, FPGA Acceleration of String Search Techniques in Huge Data Sets. Paderborn University, 2019.

T. Hansmeier, Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn, 2019.

C. Lienen, Implementing a Real-time System on a Platform FPGA operated with ReconOS. Universität Paderborn.

J.-P. Schnuer, Static Scheduling Algorithms for Heterogeneous Compute Nodes. Universität Paderborn, 2018.

M. Croce, Evaluation of OpenCL-based Compilation for FPGAs. Universität Paderborn, 2018.

N. Ho, FPGA-based Reconfigurable Cache Mapping Schemes: Design and Optimization. Universität Paderborn, 2018.

T. Hansmeier, An FPGA Accelerator for Checking Resolution Proofs. Universität Paderborn, 2017.

L. M. Witschen, A Framework for the Synthesis of Approximate Circuits. Universität Paderborn, 2017.

C. Knorr, OpenCL-basierte Videoverarbeitung auf heterogenen Rechenknoten. Universität Paderborn, 2017.

C. Knorr, Evaluation von Bildverarbeitungsalgorithmen in heterogenen Rechenknoten. Universität Paderborn, 2015.

B. Koch, Hardware Acceleration of Mechatronic Controllers on a Zynq Platform FPGA. Paderborn University, 2014.

L. Schäfers, Parallel Monte-Carlo Tree Search for HPC Systems and its Application to Computer Go. Berlin: Logos Verlag Berlin GmbH, 2014.

S. Surmund, Multithreaded Parallelization of Mechatronic Controllers on a Zynq Platform FPGA. Paderborn University, 2014.

P. Kaufmann, Adapting Hardware Systems by Means of Multi-Objective Evolution. Berlin: Logos Verlag Berlin GmbH, 2013.

M. Happe, Performance and thermal management on self-adaptive hybrid multi-cores. Berlin: Logos Verlag Berlin GmbH, 2013.

S. Drzevitzky, Proof-Carrying Hardware: A Novel Approach to Reconfigurable Hardware Security. Universität Paderborn, 2012.

H. Giefers, Design and Programming of Reconfigurable Mesh based Many-Cores. Berlin: Logos Verlag Berlin GmbH, 2012.