An Application Specific Framework for HLS-based FPGA Design of Articulated Robot Inverse Kinematics. - Safdar Mahmood; Pavel Shydlouski; Michael Hübner 001 (ReConFig, 2018)

IP Core Identification in FPGA Configuration Files using Machine Learning Techniques. - Safdar Mahmood; Jens Rettkowski; Arij Shallufa; Michael Hübner 001; Diana Göhringer (ICCE-Berlin, 2019)

Inspection of Partial Bitstreams for FPGAs Using Artificial Neural Networks. - Jens Rettkowski; Safdar Mahmood; Arij Shallufa; Michael Hübner 001; Diana Göhringer (IPDPS Workshops, 2019)

A Modular Software Library for Effective High Level Synthesis of Convolutional Neural Networks. - Hector Gerardo Muñoz Hernandez; Safdar Mahmood; Marcelo Brandalero; Michael Hübner 001 (ARC, 2020)

A Survey on Machine Learning Approaches to ECG Processing. - Javier Hoffmann; Safdar Mahmood; Priscile Suawa Fogou; Nevin George; Solaiman Raha; Sabur Safi; Kurt J. G. Schmailzl; Marcelo Brandalero; Michael Hübner 001 (SPA, 2020)

Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy. - Florian Fricke; Safdar Mahmood; Javier Hoffmann; Marcelo Brandalero; Sascha Liehr; Simon Kern; Klas Meyer; Stefan Kowarik; Stephan Westerdick; Michael Maiwald; Michael Hübner 001 (DATE, 2021)

Detecting Improvised Land-mines using Deep Neural Networks on GPR Image Dataset targeting FPGAs. - Safdar Mahmood; Stefan Scharoba; Jonas Schorlemer; Christian Schulz 010; Michael Hübner 001; Marc Reichenbach (NorCAS, 2022)

InjectMeAI - Software Module of an Autonomous Injection Humanoid. - Kwame Owusu Ampadu; Florian Rokohl; Safdar Mahmood; Marc Reichenbach; Michael Hübner 001 (Sensors, 2022)

A Design-Space Exploration Framework for Application-Specific Machine Learning Targeting Reconfigurable Computing. - Safdar Mahmood; Michael Hübner 001; Marc Reichenbach (ARC, 2023)