Fernando Camarena, PhD

Computer Vision & AI Researcher

Welcome! I'm a Computer Science researcher specializing in Video-Based Human Action Recognition. My work focuses on advancing state-of-the-art methods through self-supervised learning, few-shot learning, and modern knowledge distillation techniques.

I completed my Ph.D. at Tecnológico de Monterrey with an outstanding thesis on "Enhancing Video-Based Human Action Recognition Model Training through Knowledge Distillation," which earned second place in the prestigious "José Negrete" award from the Mexican Society for Artificial Intelligence.

🏆 Key Achievements

  • Published 3 Q2 Journal articles and multiple conference papers
  • Achieved a 99.89/100 Ph.D. GPA, earning the Medal of Merit
  • Completed Deep Learning specialization from DeepLearning.AI
  • Earned gold certificates from OpenCV University in PyTorch and Computer Vision
  • Developed innovative approaches in self-supervised learning and knowledge distillation

🔬 Research Focus

My research lies at the intersection of:

  • Video Understanding: Developing advanced methods for human action recognition in videos
  • Self-supervised Learning: Creating efficient approaches for learning from unlabeled video data
  • Knowledge Distillation: Exploring innovative techniques for model compression and training
  • Few-shot Learning: Advancing methods for learning from limited examples
  • Deep Learning: Implementing state-of-the-art architectures for computer vision tasks

📚 Recent Publications

🤝 Let's Connect

I'm always interested in collaborating on research projects and discussing ideas in Computer Vision and AI: