Dimitrios Tsourounis | Computer Science | Best Researcher Award

Dr. Dimitrios Tsourounis | Computer Science | Best Researcher Award

Dr. Dimitrios Tsourounis | Computer Science | University of Patras | Greece

Dimitrios Tsourounis is a passionate computer scientist specializing in computer vision, deep learning, and quantum machine learning. Born on February 26, 1991, in Greece, Dimitrios earned his Ph.D. from the University of Patras in 2023, focusing on deep learning strategies for problems with limited data. He has contributed significantly to advancing machine learning methods and quantum computing integration, currently working as a Research Scientist at Quantum Neural Technologies (QNT) in Athens. Dimitrios is also involved in autonomous aerial systems research at the Athena Research Center, applying computer vision techniques to fuse radar and RGB camera data for UAVs. His multidisciplinary expertise includes physics, electronics, and artificial intelligence, supported by multiple successful EU-funded projects. With a proven track record in innovation and real-world applications, Dimitrios is recognized for bridging theoretical research and industrial challenges, particularly in quantum-enhanced machine learning and biometric security.

Author Profile

Scopus | Orcid | Google Scholar

Education 

Dimitrios completed his Ph.D. in Computer Vision at the University of Patras, Greece (2017-2023), specializing in deep learning, neural networks, and AI strategies for limited data scenarios under Prof. George Economou’s supervision. His doctoral thesis explored novel transfer learning and knowledge distillation techniques. Prior to this, Dimitrios earned an M.Sc. in Electronics, Engineering and Computer Science (2015-2017) from the University of Patras, graduating summa cum laude with a thesis on deep sparse coding. His academic foundation was built on a B.Sc. in Physics (2010-2015) from the same university, graduating magna cum laude, with research focused on sparse representation for offline handwritten signature recognition. Dimitrios also briefly studied medicine before shifting to physics and computing, showcasing a diverse academic background. Throughout his studies, he demonstrated academic excellence, receiving top grades and honors in rigorous technical fields that combine physical sciences with computer engineering.

Experience

Dimitrios currently works as a Research Scientist in Quantum Machine Learning at Quantum Neural Technologies (QNT) in Athens, designing quantum algorithms and integrating machine learning with quantum computing for industrial applications such as pharmaceuticals, cryptography, and finance. Since July 2025, he has been a Computer Vision Scientist at the Athena Research Center, focusing on UAV systems that fuse radar and camera data for autonomous aerial navigation. His Ph.D. research (2017-2023) involved deep learning for limited data, emphasizing convolutional neural networks and biometric applications. Dimitrios contributed to the DeepSky project on cloud type estimation using multi-sensor data and worked on Greek lip reading datasets employing deep sequential models. He also participated in RoadEye, developing AI solutions for road condition monitoring, pothole, and speed bump detection. Throughout his career, Dimitrios has utilized tools like Python, PyTorch, TensorFlow, Qiskit, and Matlab, continuously merging theoretical innovation with practical applications in computer vision, AI, and quantum technologies.

Awards and Honors

Dimitrios Tsourounis has received notable recognition for his academic and research excellence. He was awarded a prestigious scholarship from the Greek State Scholarships Foundation (IKY) to support his Ph.D. studies, reflecting his outstanding merit. Throughout his academic career, Dimitrios graduated summa cum laude for his M.Sc. and magna cum laude for his B.Sc., highlighting consistent academic distinction. His research contributions have been supported by competitive European Union and Greek national funding programs, including co-funding for projects such as DeepSky and RoadEye. Dimitrios has also been acknowledged within the quantum computing and AI research communities for pioneering integration of machine learning with quantum frameworks. His work has earned invitations to collaborate with leading academic and industry partners, reinforcing his reputation as an innovative scientist. While yet to accumulate traditional prize awards, his growing publication record and project leadership positions underscore his impact and future promise in computer science and quantum technologies.

Research Focus 

Dimitrios Tsourounis’s research centers on computer vision, deep learning, and quantum machine learning, with a particular focus on addressing challenges of limited data availability in neural network training. His Ph.D. work pioneered transfer learning and knowledge distillation methods tailored to biometric security and pattern recognition. Currently, Dimitrios explores quantum-enhanced machine learning algorithms leveraging variational quantum circuits to improve performance on complex scientific and industrial problems. His expertise also spans multimodal data fusion, combining radar and visual data in autonomous aerial systems to enhance object detection accuracy. Additionally, he investigates sequential deep learning architectures for tasks such as lip reading in the Greek language and environmental sensing through cloud type recognition using thermal and all-sky cameras. Dimitrios integrates classical machine learning frameworks like PyTorch with quantum programming tools such as Qiskit and Pennylane, pushing the frontier of hybrid classical-quantum AI. His work aims to bridge theoretical advances and practical applications across fields including cryptography, healthcare, and autonomous vehicles.

Publications 

  • “Deep Sparse Coding for Signal Representation”

  • “Neural Networks for Biometric Applications with Limited Data”

  • “Quantum Variational Circuits in Machine Learning”

  • “Fusion of Radar and RGB Data in UAV Object Detection”

  • “Lip Reading Greek Words Using Sequential Deep Learning”

  • “Cloud Type Estimation with All-Sky and Thermal Cameras”

  • “Real-Time Road Condition Monitoring via Computer Vision”

  • “Knowledge Distillation Techniques in Convolutional Neural Networks”

Conclusion

Dimitrios Tsourounis exemplifies a forward-thinking computer scientist, seamlessly integrating deep learning and quantum computing to tackle real-world challenges. His academic excellence, coupled with his innovative research in limited-data neural networks and quantum-enhanced AI, positions him as a leading researcher in computer vision and machine learning. Dimitrios’s contributions advance both theoretical knowledge and practical solutions across diverse sectors, from autonomous systems to pharmaceuticals. His dedication and interdisciplinary approach promise significant future impact in computer science and emerging quantum technologies.

 

Ahlem Ayari | Computer Science | Best Researcher Award

Dr. Ahlem Ayari | Computer Science | Best Researcher Award

Dr. Ahlem Ayari, Higher Institute of Management of Sousse, Tunisia 

Ahlem Ayari is a dedicated PhD student at the National Engineering School of Sousse (ENISo), specializing in cloud computing, edge computing, and high-performance computing. She has extensive experience as a lecturer and trainer in computer science, particularly in database management, object-oriented programming, and web development. With a strong foundation in Java, C, JavaScript, and other programming languages, Ahlem has contributed to various software and web-based projects. Her research focuses on distributed systems, artificial intelligence, and machine learning algorithms. She has actively participated in international conferences and academic collaborations, highlighting her expertise in deploying e-health applications on cloud and edge computing environments. Ahlem is passionate about advancing technology in healthcare and has successfully developed innovative platforms that integrate deep learning algorithms for medical data analysis. She remains committed to contributing to technological advancements and mentoring the next generation of computer scientists through her academic and research pursuits.

Professional Profile

Scopus

Suitability for the Research for Best Researcher Award – Ahlem Ayari

Ahlem Ayari demonstrates a strong academic background and technical expertise, making her a promising candidate for the Research for Best Researcher Award. She is currently a PhD student at the National Engineering School of Sousse (ENISo), Tunisia, specializing in advanced computing fields such as distributed systems, high-performance computing, artificial intelligence, and machine learning. Her research contributions, particularly in cloud and edge computing for e-health applications, highlight her commitment to solving real-world challenges through innovative technology.

Her experience extends beyond academia, as she has actively contributed to teaching and training at multiple institutions, including Higher Institute of Management (ISG) and The Maghreb Institute of Economic Sciences and Technology (IMSET). She has taught courses in database management, programming, UML, MERISE, and cloud computing, demonstrating her ability to disseminate knowledge effectively. Additionally, her industry experience as a web developer strengthens her profile by bridging the gap between theoretical research and practical application.

🎓 Education

  • 2023-2024: PhD Student in Computer Science, “Mars” Laboratory, National Engineering School of Sousse (ENISo), Sousse University. Supervisor: Prof. Mohamed Nazih Omri, Co-supervisor: Hassen Hamdi.
  • 2021-2023: Master in Business Computing, Higher Institute of Management (ISG), Sousse University. Supervisor: Hassen Hamdi.
  • 2017-2020: Bachelor’s Degree in Business Computing, Higher Institute of Management (ISG), Sousse University. Supervisor: Kamel Garrouch.
  • 2017: Mathematics Baccalaureate, Ibn Rachik Kairouan.

Ahlem Ayari’s academic journey reflects her commitment to interdisciplinary learning, combining computer science and business computing. Her doctoral research focuses on cloud and edge computing, aiming to optimize computational efficiency and data security in medical applications. Throughout her studies, she has acquired expertise in artificial intelligence, database management, software engineering, and statistical analysis, contributing to her proficiency in designing and implementing complex computational systems.

💼 Professional Experience 

  • Trainer, Maghreb Institute of Economic Sciences and Technology (IMSET) (2024)
    • Taught courses on E-commerce, UML, MERISE, and SQL database management.
    • Conducted practical training in software development and IT systems.
  • Assistant Master, Higher Institute of Management (ISG), Sousse (2024)
    • Lectured in object-oriented programming (Java), cloud computing, big data, and C2I (Certificate in Computer Science and Internet).
  • Trainer, Higher Institute of Management (ISG), Sousse (2024)
    • Conducted LaTeX training for CV, report, and presentation creation.
  • Web Developer, Access Leader (March 2020 – September 2020)
    • Developed a web application using Angular for truck sales management.

🏅 Awards and Recognition

  • 12th International Conference of ISG Sousse (2023): Recognized for research on deploying e-health applications in edge and cloud computing environments.
  • 28th International Conference on Knowledge-Based and Intelligent Information Engineering Systems, Seville, Spain (2024): Presented innovative research on IoMT-based e-health applications.
  • Academic Distinction: Awarded recognition for excellence in cloud computing and AI research.
  • Best Research Presentation Award: Acknowledged for outstanding work in high-performance computing.

🌍 Research Skills On Computer Science

Ahlem Ayari possesses advanced research skills in distributed computing, cloud and edge computing, big data analytics, and AI-driven applications. Her expertise extends to designing and implementing machine learning models for real-time data processing. She is proficient in various programming languages (Java, C, Python) and frameworks (Angular, Symfony, Node.js). Her research methodologies involve deep learning algorithms for e-health applications and optimizing computational infrastructures. Ahlem actively contributes to international conferences, presenting innovative solutions in high-performance computing.

📖 Publication Top Notes

E-health Application In IoMT Environment Deployed in An Edge And Cloud Computing Platforms

  • Author: A., Ayari, Ahlem, H., Hassen, Hamdi, K.A., Alsulbi, Khlil Ahmad