As a passionate student in the field of Cybersecurity, my research is driven by a fascination with Federated Learning, the acceleration of distributed encrypted training, and fine-tuning of large language models with a strong focus on privacy-preserving techniques such as Homomorphic Encryption and Differential Privacy.
Outside the digital realm, I channel my energy into swimming and fitness.
- Improving efficiency and security in Federated Learning systems.
- Exploring advanced encryption methods for privacy in AI, including Homomorphic Encryption.
- Investigating Differential Privacy applications in fine-tuning large language models.
- Python, PyTorch, C++, Java, C
- Homomorphic Encryption Libraries
- Differential Privacy Frameworks
- CUDA & Parallel Computing Platforms
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Thanks for stopping by, and please feel free to check out my repositories below!