Dr. Emmanuel Pintelas | Few-shot learning | Best Researcher Award

Doctorate at Department of Electrical and Computer Engineering, University of Peloponnese, Greece

👨‍🎓 Profiles

👤Academic Background

Emmanuel Pintelas is a Postdoctoral Researcher in the Department of Electrical and Computer Engineering at the University of Peloponnese. He excels in computer vision, deep learning, and video analytics. His notable achievements include high placements in international competitions and numerous publications in esteemed journals.

🎓 Education

  • Ph.D. in Mathematics and Computer Science (Feb 2020 – Aug 2023)
    University of Peloponnese, Greece
    Dissertation: “Interpretable Machine Learning Frameworks for Image Classification”
  • M.Sc. in Technologies and Services of Intelligent Information Systems and Communications (Sep 2020 – Apr 2022)
    University of Peloponnese, Greece
    Dissertation: “Deep Neural Networks for Bitcoin Price Prediction”
  • B.Sc. in Electrical & Computer Engineering (Sep 2008 – Feb 2018)
    University of Patras, Greece
    Focus: Automatic electrical-virtual-machines for grid supply stability and control.

💼 Professional Experience

  • Postdoctoral Researcher (Sep 2023 – Present)
    University of Peloponnese
    Specializes in computer vision, deep learning, and video analytics. Involved in research paper writing, course instruction, and distributed programming.
  • Internship Scholarship (Jun 2022 – Aug 2022)
    Archimedes Unit
    Collaborated on AI challenges, proposed solutions in computer vision, and engaged with leading researchers.
  • Technical Manager and Shareholder (2012 – 2016)
    Φωτοβολταικα Αγιου Βασιλείου ΙΚΕ
    Managed operation and maintenance of solar parks.
  • Shareholder and Manager (2016 – Present)
    Φωτοβολταικα Αγίου Βασιλείου ΙΚΕ
    Oversees remote management and optimization of solar park production.

🔬 Research Interests

Emmanuel’s research focuses on computer vision, deep learning, and time-series analysis, with applications in medical imaging, object detection, deepfake detection, and few-shot learning. He is particularly interested in developing interpretable machine learning frameworks and innovative deep learning architectures.

🏆 Accomplishments

  • NeurIPS 2022 Competitions: Achieved 2nd place in the Cross-Domain MetaDL challenge.
  • Kaggle Competitions: Awarded a Bronze Medal in the RANZCR CLiP medical imaging challenge.

📖 Publications

Adaptive Augmentation Framework for Domain Independent Few Shot Learning
    • Authors: Pintelas, E., Livieris, I.E., Pintelas, P.
    • Year: 2024
Explainable Image Similarity: Integrating Siamese Networks and Grad-CAM
    • Authors: Livieris, I.E., Pintelas, E., Kiriakidou, N., Pintelas, P.
    • Year: 2023
XSC—An eXplainable Image Segmentation and Classification Framework: A Case Study on Skin Cancer
    • Authors: Pintelas, E., Livieris, I.E.
    • Year: 2023
A Multi-View-CNN Framework for Deep Representation Learning in Image Classification
    • Authors: Pintelas, E., Livieris, I.E., Kotsiantis, S., Pintelas, P.
    • Year: 2023
Explainable Feature Extraction and Prediction Framework for 3D Image Recognition Applied to Pneumonia Detection
    • Authors: Pintelas, E., Livieris, I.E., Pintelas, P.
    • Year: 2023
NeurIPS’22 Cross-Domain MetaDL Challenge: Results and Lessons Learned
    • Authors: Carrión-Ojeda, D., Alam, M., Escalera, S., … Wu, J., Yin, X.
    • Year: 2023
Emmanuel Pintelas | Few-shot learning | Best Researcher Award

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