antoniosmakris [at] mail [dot] ntua [dot] gr

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Education

PhD in Distributed Systems

Harokopio University of Athens, Greece
Thesis: A study on the query response time minimization in distributed (spatiotemporal) data stores [link]

Oct 2015 – July 2022

MSc in Web Engineering

Harokopio University of Athens, Greece
Thesis: Implementation of function in R tool in parallel environment [link]

Sep 2013 – July 2015

BSc in Informatics and Telematics

Harokopio University of Athens, Greece
Thesis: Gadget recommendation and composition mechanism, in the environment of academic social network Unity, based on user experience

Sep 2008 – Sep 2013

Research Projects

↪ Ongoing Projects

• CoEvolution (HE)

  A Comprehensive Trustworthy Framework for Connected Machine Learning and Secure Interconnected AI Solutions.

  Role: Deputy Project Coordinator

  Nov 2024 – Present

• MUSIT (HORIZON-MSCA-2023)

  MultiSensor Inferred Trajectories.

  Nov 2024 – Present

↪

Past Projects

• CHARITY (H2020)

  CHARITY aspires to leverage the benefits of intelligent, autonomous orchestration of cloud, edge, and network resources, to create a symbiotic relationship between low and high latency infrastructures that will facilitate the needs of emerging applications.

  Jan 2021 – Jul 2024

• SmartShip (H2020-MSCA-RISE-2018)

  A data analytics, decision support and circular economy – based multi-layer optimization platform towards a holistic energy efficiency, fuel consumption and emissions management of vessels.

  May 2019 – Mar 2024

• FNS-Cloud (H2020)

  Food Nutrition Security Cloud (FNS-Cloud) has launched the first ‘food cloud’, federating existing and emerging datasets, tools and services to support European research.

  Apr 2019 – June 2023

• GLASSEAS (National funded ESPA 2019)

  A global, distributed surveillance system for early detection and analysis of anomalous vessel trajectories.

  Apr 2019 – June 2020

• MASTER (H2020-MSCA-RISE-2017)

  MASTER (Multiple ASpects TrajEctoRy management and analysis) is a project with the objective of forming an international and inter-sectoral network of organisations working on a joint research programme to define new methods to build, manage and analyse multiple aspects semantic trajectories.

  Mar 2018 – Dec 2023

• Productive 4.0 (H2020)

  Productive4.0 is an ambitious holistic innovation project, meant to open the doors to the potentials of Digital Industry and to maintain a leadership position of the industries in Europe. All partners involved will work on creating the capability to efficiently design and integrate hardware and software of Internet of Things (IoT) devices.

  May 2017 – Apr 2020

• Optimal (HUA internally-funded project)

  Middleware development for the optimal replica placement in distributed key-value stores & fault tolerance techniques in infrastructures for large-scale data management.

  Dec 2016 – Dec 2017

• Asylum Service Application (National funded)

  Mobile Application for international applicants protection.

  Mar 2016 – May 2016

• Fortissimo (FP7)

  Cloud-based simulation of the binding capacities of target drug.

  Sep 2014 – May 2016

Publications

Selected peer-reviewed papers

• Cross-Cluster Networking to Support Extended Reality Services. Theodoropoulos, T., Rosa, L., Boudi, A., Benmerar, T. Z., Makris, A., Taleb, T., ... & Song, J. (2024) IEEE Network.
• Efficient Application Image Management in the Compute Continuum: A Vertex Cover Approach Based on the Think-Like-A-Vertex Paradigm. Carlini, E., Dazzi, P., Makris, A., Mordacchini, M., Theodoropoulos, T., & Tserpes, K. (2024). In 2024 IEEE 17th International Conference on Cloud Computing (CLOUD).
• Pro-active component image placement in Edge computing environments. Makris, A., Psomakelis, E., Carlini, E., Mordacchini, M., Theodoropoulos, T., Dazzi, P., & Tserpes, K. (2024). Future Generation Computer Systems.
• GNOSIS: Proactive Image Placement Using Graph Neural Networks & Deep Reinforcement Learning. Theodoropoulos, T., Makris, A., Psomakelis, E., Carlini, E., Mordacchini, M., Dazzi, P., & Tserpes, K. (2023, July). In 2023 IEEE 16th International Conference on Cloud Computing (CLOUD) (pp. 120-128). IEEE.
• Graph neural networks for representing multivariate resource usage: A multiplayer mobile gaming case-study. Theodoropoulos, T., Makris, A., Kontopoulos, I., Violos, J., Tarkowski, P., Ledwoń, Z., ... & Tserpes, K. (2023). International Journal of Information Management Data Insights, 3(1), 100158.
• A comparison of trajectory compression algorithms over AIS data. Makris, A., Kontopoulos, I., Alimisis, P., & Tserpes, K. (2021). IEEE Access, 9, 92516-92530.
• MongoDB Vs PostgreSQL: A comparative study on performance aspects. Makris, A., Tserpes, K., Spiliopoulos, G., Zissis, D., & Anagnostopoulos, D. (2021). GeoInformatica, 25, 243-268.
• COVID-19 detection from chest X-Ray images using Deep Learning and Convolutional Neural Networks. Makris, A., Kontopoulos, I., & Tserpes, K. (2020, September). In 11th hellenic conference on artificial intelligence (pp. 60-66).
• Parallelization of large-scale drug–protein binding experiments. Michail, D., Makris, A., Varlamis, I., & Sawyer, M. (2019). Future Generation Computer Systems, 97, 492-502.
• A novel object placement protocol for minimizing the average response time of get operations in distributed key-value stores. Makris, A., Tserpes, K., & Anagnostopoulos, D. (2017, December). In 2017 IEEE International Conference on Big Data (Big Data) (pp. 3196-3205). IEEE.
• A classification of NoSQL data stores based on key design characteristics. Makris, A., Tserpes, K., Andronikou, V., & Anagnostopoulos, D. (2016). Procedia Computer Science, 97, 94-103.