Mixture of learners for cancer stem cell detection using CD13 and H and E stained images. - Oguzhan Oguz; Cem Emre Akbas; Maen Mallah; Kasim Tasdemir; Ece Akhan Güzelcan; Christian Münzenmayer; Thomas Wittenberg; Aysegül Üner; A. Enis Çetin; Rengül Çetin-Atalay (Digital Pathology, 2016)

A Hardware Inference Accelerator for Temporal Convolutional Networks. - Rashid Ali; Maen Mallah; Martin Leyh; Philipp Holzinger; Marco Breiling; Marc Reichenbach; Dietmar Fey (NORCAS, 2019)

Simulating large neural networks embedding MLC RRAM as weight storage considering device variations. - Markus Fritscher; Johannes Knödtel; Daniel Reiser; Maen Mallah; Stefan Pechmann; Dietmar Fey; Marc Reichenbach (LASCAS, 2021)

Mitigating the Effects of RRAM Process Variation on the Accuracy of Artificial Neural Networks. - Markus Fritscher; Johannes Knödtel; Maen Mallah; Stefan Pechmann; Emilio Pérez-Bosch Quesada; Tommaso Rizzi; Christian Wenger; Marc Reichenbach (SAMOS, 2021)

Performance Evaluation of Federated Learning in Intelligent Wireless Receivers. - Maen Mallah; Ömer Karakas; Mehdi Harounabadi (CSCN, 2022)

Multi-Partner Project: A Deep Learning Platform Targeting Embedded Hardware for Edge-AI Applications (NEUROKIT2E). - Rajendra Bishnoi; Mohammad Amin Yaldagard; Said Hamdioui; Kanishkan Vadivel; Manolis Sifalakis; Nicolas Daniel Rodriguez; Pedro Julián; Lothar Ratschbacher; Maen Mallah; Yogesh Ramesh Patil; Rashid Ali; Fabian Chersi (DATE, 2025)