Journal Publications

1. K. G. Liakos, F. Plessas, “Analog Design and Machine Learning: A Review”, Electronics, vol.14, doi: 10.3390 electronics14173541

2. K. G. Liakos, V. Athanasiadis, E. Bozinou, S. I. Lalas, “Machine Learning for Quality Control in the Food Industry: A Review”, Foods, 2025, vol. 14, doi: 10.3390/foods14193424

3. M. Mantiniotou, V. Athanasiadis, K. G. Liakos, E. Bozinou, S. I. Lalas, “Ultrasound-Assisted Extraction of Antioxidant Compounds from Pomegranate Peels and Simultaneous Machine Learning Optimization Study”, Processes, 2025, vol. 13, doi: 10.3390/pr13113700

4. M. Mantiniotou, V. Athanasiadis, K. G. Liakos, E. Bozinou, S. I. Lalas, “Artificial Intelligence and Extraction of Bioactive Compounds: The Case of Rosemary and Pressurized Liquid Extraction”, Processes, 2025, vol. 13, doi:10.3390/pr13061879

5. K. G. Liakos, G. K. Georgakilas, F. C. Plessas, and P. Kitsos, “GAINESIS: Generative Artificial Intelligence NEtlists SynthesIS,” Electronics, 2022, vol. 11, doi:10.3390/electronics11020245

6. K. G. Liakos, G. K. Georgakilas, S. Moustakidis, N. Sklavos, and F. C. Plessas, “Conventional and Machine Learning Approaches as Countermeasures Against Hardware Trojan Attacks,” Microprocessors and Microsystems, 2020, vol. 79, doi: 10.1016/j.micpro.2020.103295

7. G. K. Georgakilas, A. Grioni, K. G. Liakos, E. Chalupova, F. C. Plessas, P. Alexiou, “Multi-branch convolutional neural network for identification of small non-coding RNA genomic loci”, Scientific reports, 2020, vol. 10, doi:10.1038/s41598-020-66454-3

8. K. G. Liakos, P. Busato, D. Moshou, S. Pearson and D. Bochtis, “Machine Learning in Agriculture: A Review”, Sensors, 2018, vol. 18, doi.org/10.3390/s18082674

Conference Publications
1. K. G. Liakos, F. C. Plessas, “CAS-HtBase: a new database for the study of HTs at the pre-silicon stage of ASICs”

2. K. G. Liakos, G. K. Georgakilas, F. C. Plessas, “Hardware Trojan Classification at Gate-level Netlists based on Area and Power Machine Learning Analysis”, In Proceedings of the 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Tampa, USA, 7-9 July 2021, doi:10.1109/ISVLSI51109.2021.00081

3. S. P. Moustakidis, K. G. Liakos, G. K. Georgakilas, N. Sketopoulos, S. Simoglou, P. Karlsson, F. Plessas, “A Novel Holistic Approach for Hardware Trojan Detection Powered by Deep Learning (HERO)”, In Proceedings of the 2020 ATTRACT Final Conference

4. K. G. Liakos, G. K. Georgakilas, TS. Moustakidis, P. Karlsson, F. C. Plessas, “Machine Learning for Hardware Trojan Detection: A Review”, In Proceedings of the 2019 Panhellenic Conference on Electronics & Telecommunications (PACET), Volos, Greece, 08-09 November 2019, doi:10.1109/PACET48583.2019.8956251

5. K. G. Liakos, S. Moustakidis, G. Tsiotra, T. Bartzanas, D. Bochtis, C. Parisses, “Machine Learning Based Computational Analysis Method for Cattle Lameness Prediction”, In Proceedings of the 8th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, Chania, Greece, 21-24 September 2017

6. D. Katikaridis, D. Bechtsis, I. Menexes, K. G. Liakos, D. Vlachos, D. Bochtis, “A Software Tool for Efficient Agricultural Logistics”, In Proceedings of the 8th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, Chania, Greece, 21-24 September 2017

7. V. Moisiadis, D. Bechtsis, K. G. Liakos, D. Bochtis, D. Vlachos, “Development of Virtual Interface for the Design and the Control Navigation of Autonomous Agricultural Vehicles”, In Proceedings of the 10th Panhellenic Conference on Society of Agricultural Engineers of Greece, Athens, Greece, 28-29 September 2017

Preprint Paper
1. G. K. Georgakilas, A. Grioni, K. G Liakos, E. Malanikova, F. C. Plessas, P. Alexiou, “MuStARD: Deep Learning for Intra- and Inter-species Scanning of Functional Genomic Patterns”, bioRxiv, 2019, doi: https://doi.org/10.1101/547679

Book Chapter
1. K. G. Liakos, F. Plessas, 2022. “Hardware and System Security-Attacks and Countermeasures Against Hardware Trojans”. Frontiers of Electronic Design, Electronic Design for AI, IoT and Hardware Security

Working Paper Project
1. Large Language Model for Analog Design Optimization

2. Funding Tool - Pharos Greek FactoryAI

3. Research Matchmaking Tool - Pharos Greek FactoryAI

4. Norovirus Outbreak Forecasting for Cruise Shipping

5. Quantum Chromodynamics: Generative Model for Sampling in Lattice Quantum
Chromodynamics

6. NCSR"Demokritos" - Data Space

National Centre for Scientific Research “Demokritos” – Institute of Informatics and Telecommunication, Athens, Greece

• Contributed to WP4 – Interoperability, focusing on system integration and data interoperability across heterogeneous platforms, for the research program “DeployAI”·
• Participated in WP5 – Technology Transfer, Customization and Integration of High-Value Domain Services (Use Cases), supporting the technical adaptation and deployment of specialized services, for the research program “DeployAI”·
• Involved in WP6 – Deployment and Operation, assisting with the setup, testing, and operational phases of the platform, for the research program “DeployAI”
• Contributed to WP3 – AI and HPC Interoperability, focusing on system integration and data interoperability across heterogeneous platforms, for the research program “PharosAI”
• Involved in WP6 – Networking and Collaboration with National and EU
  Initiatives, for the research program “PharosAI”

University of Thessaly - Circuits and Systems Laboratory, Volos, Greece

• Analog and mixed-signal integrated circuit design, with an emphasis on machine learning-assisted design automation. Current work centers on developing surrogate models for fast circuit performance prediction, along with inverse design and design space exploration methods for OTA amplifiers in nanometer CMOS technologies.