Feasibility Study of Subfoveal Choroidal Thickness Changes in Spectral-Domain Optical Coherence Tomography Measurements of Macular Telangiectasia Type 2. - Tiziano Ronchetti; Peter Maloca; Emanuel Ramos de Carvalho; Tjebo F. C. Heeren; Konstantinos Balaskas; Adnan Tufail; Catherine Egan; Mali Okada; Selim Orgül; Christoph Jud; Philippe C. Cattin (COMPAY/OMIA@MICCAI, 2018)

A Hybrid Machine Learning Approach Using LBP Descriptor and PCA for Age-Related Macular Degeneration Classification in OCTA Images. - Abdullah Alfahaid; Tim Morris 001; Tim Cootes; Pearse A. Keane; Hagar Khalid; Nikolas Pontikos; Panagiotis I. Sergouniotis; Konstantinos Balaskas (MIUA, 2019)

ECG Analysis and Heartbeat Classification Based on Shallow Neural Networks. - Konstantinos Balaskas; Kostas Siozios (MOCAST, 2019)

Fatigue Detection Using Deep Long Short-Term Memory Autoencoders. - Konstantinos Balaskas; Kostas Siozios (MOCAST, 2021)

Code-free deep learning for multi-modality medical image classification. - Edward Korot; Zeyu Guan; Daniel Ferraz; Siegfried K. Wagner; Gongyu Zhang; Xiaoxuan Liu; Livia Faes; Nikolas Pontikos; Samuel G. Finlayson; Hagar Khalid; Gabriella Moraes; Konstantinos Balaskas; et al. (Nat. Mach. Intell., 2021)

Automated Design Approximation to Overcome Circuit Aging. - Konstantinos Balaskas; Georgios Zervakis 001; Hussam Amrouch; Jörg Henkel; Kostas Siozios (IEEE Trans. Circuits Syst. I Regul. Pap., 2021)

Approximate Decision Trees For Machine Learning Classification on Tiny Printed Circuits. - Konstantinos Balaskas; Georgios Zervakis 001; Kostas Siozios; Mehdi B. Tahoori; Jörg Henkel (ISQED, 2022)

Variability-Aware Approximate Circuit Synthesis via Genetic Optimization. - Konstantinos Balaskas; Florian Klemme; Georgios Zervakis 001; Kostas Siozios; Hussam Amrouch; Jörg Henkel (IEEE Trans. Circuits Syst. I Regul. Pap., 2022)

Differentiable Slimming for Memory-Efficient Transformers. - Nikolay Penkov; Konstantinos Balaskas; Martin Rapp; Jörg Henkel (IEEE Embed. Syst. Lett., 2023)

Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction. - Biraja Ghoshal; William Woof; Bernardo Mendes; Saoud Al-Khuzaei; Thales Antonio Cabral De Guimaraes; Malena Daich Varela; Yichen Liu; Sagnik Sen 003; Siying Lin; Mital Shah; Yu Fujinami-Yokokawa; Andrew R. Webster; et al. (UNSURE@MICCAI, 2024)

Energy-Aware Heterogeneous Federated Learning via Approximate Systolic DNN Accelerators. - Kilian Pfeiffer; Konstantinos Balaskas; Kostas Siozios; Jörg Henkel (CoRR, 2024)

Hardware-Aware DNN Compression via Diverse Pruning and Mixed-Precision Quantization. - Konstantinos Balaskas; Andreas Karatzas; Christos Sad; Kostas Siozios; Iraklis Anagnostopoulos; Georgios Zervakis 001; Jörg Henkel (IEEE Trans. Emerg. Top. Comput., 2024)

Heterogeneous Accelerator Design for Multi-DNN Workloads via Heuristic Optimization. - Konstantinos Balaskas; Heba Khdr; Mohammed Bakr Sikal; Fabian Kreß; Kostas Siozios; Jürgen Becker 001; Jörg Henkel (IEEE Embed. Syst. Lett., 2024)

Late Breaking Results: Energy-Efficient Printed Machine Learning Classifiers with Sequential SVMs. - Spyridon Besias; Ilias Sertaridis; Florentia Afentaki; Konstantinos Balaskas; Georgios Zervakis 001 (DATE, 2025)

Late Breaking Results: Leveraging Approximate Computing for Carbon-Aware DNN Accelerators. - Aikaterini Maria Panteleaki; Konstantinos Balaskas; Georgios Zervakis 001; Hussam Amrouch; Iraklis Anagnostopoulos (DATE, 2025)

Computing with Printed and Flexible Electronics. - Mehdi B. Tahoori; Emre Ozer; Georgios Zervakis 001; Konstantinos Balaskas; Priyanjana Pal (ETS, 2025)

Compact Yet Highly Accurate Printed Classifiers Using Sequential Support Vector Machine Circuits. - Ilias Sertaridis; Spyridon Besias; Florentia Afentaki; Konstantinos Balaskas; Georgios Zervakis 001 (ISCAS, 2025)

Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability. - Aikaterini Maria Panteleaki; Konstantinos Balaskas; Georgios Zervakis 001; Hussam Amrouch; Iraklis Anagnostopoulos (CoRR, 2025)

Energy-Aware Heterogeneous Federated Learning via Approximate DNN Accelerators. - Kilian Pfeiffer; Konstantinos Balaskas; Kostas Siozios; Jörg Henkel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)