I am a Research Fellow with extensive experience in AI research and development, particularly in deep learning and AI security. I have worked on diverse projects, from intrusion detection to click-through rate (CTR) prediction in programmatic advertising. My career spans both academia and industry, where I have contributed to cutting-edge AI solutions, collaborated on large-scale research projects, and mentored engineers and researchers.

🔭 I’m currently working at CSIT, QUB, focusing on AI-driven security solutions and trustworthy AI applications.
🌱 I’m currently exploring more about spiking neural networks and federated learning for AI security.
🤝 I’m looking to collaborate on AI projects involving CTR/CVR prediction, intrusion detection, graph theory, and secure machine learning applications.
🤔 I’m seeking new challenges in advancing LLMs, generative AI, and robust AI systems for real-world applications.
💬 Ask me about AI, deep learning models, or my latest research on CTR prediction.
📫 How to reach me: d.aksu[at]qub.ac.uk
⚡ Fun fact: I’ve worked on projects ranging from gaze estimation systems for people with disabilities to autonomous vehicle development!

• Languages: Python, C++, C#, Java, SQL
• Frameworks: TensorFlow, PyTorch, Keras
• Tools: Docker, Apache Spark, MLOps, DataOps, Git, Overleaf
• Expertise: Machine learning, Deep learning, AI Security, Recommender Systems, Intrusion Detection Systems

Feel free to explore my GitHub repositories, visit my webpage, or connect with me on LinkedIn.