On Guaranteeing Schedulability of Periodic Real-time Hardware Tasks under ReconO
L. Clausing, Z. Guetattfi, P. Kaufmann, C. Lienen, M. Platzner, in: Proceedings of the 19th International Symposium on Applied Reconfigurable Computing (ARC), 2023.

Flexible Industrial Analytics on Reconfigurable Systems-On-Chip
A. Boschmann, L. Clausing, F. Jentzsch, H. Ghasemzadeh Mohammadi, M. Platzner, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 225–236.

On-The-Fly Computing -- Individualized IT-services in dynamic markets
C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim, On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023.

Reconfigurable Random Forest Implementation on FPGA
M. Raeisi Nafchi, Reconfigurable Random Forest Implementation on FPGA, Paderborn University, 2023.

Data Analytics for Predictive Maintenance of Time Series Data
N. Yadalam Murali Kumar, Data Analytics for Predictive Maintenance of Time Series Data, Paderborn University, 2023.

ReconO: A Hardware Operating System for Modern Platform FPGAs with 64-Bit Support
L. Clausing, M. Platzner, in: 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE, 2022, pp. 120–127.

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

Dealing With Pre-Processing And Feature Extraction Of Time-Series Data In  Predictive Maintenance
S. Manjunatha, Dealing With Pre-Processing And Feature Extraction Of Time-Series Data In  Predictive Maintenance, Paderborn University , 2022.

Analysis of Time-Series Classification in Conditional Monitoring Systems
P. Kaur , Analysis of Time-Series Classification in Conditional Monitoring Systems, Paderborn University , 2022.

ReconO: High-Performance Embedded Computing for Industrial Analytics on a Reconfigurable System-on-Chip
L. Clausing, in: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, ACM, 2021.

FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial Analytics
H. Ghasemzadeh Mohammadi, F. Jentzsch, M. Kuschel, R. Arshad, S. Rautmare, S. Manjunatha, M. Platzner, A. Boschmann, D. Schollbach, in:  Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Springer, 2021.

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

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

A Case for a New IT Ecosystem: On-The-Fly Computing
H. Karl, D. Kundisch, F. Meyer auf der Heide, H. Wehrheim, Business &; Information Systems Engineering 62 (2020) 467–481.

DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms
H. Ghasemzadeh Mohammadi, R. Arshad, S. Rautmare, S. Manjunatha, M. Kuschel, F.P. Jentzsch, M. Platzner, A. Boschmann, D. Schollbach, in: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020.

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

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