Hamed Habibi

I am a software developer and doctoral researcher at the Department of Mathematics and Computer Science at FU Berlin. My expertise lies in the field of network intrusion detection (Cybersecurity), with a focus on anomaly detection, utilizing cutting-edge machine and deep learning methods. My research explores the applications of unsupervised learning, self-supervised learning, and weakly supervised learning techniques for analyzing tabular data, enabling efficient detection of network anomalies. I am part of the 6G-RIC and Center of trusted artificial intelligence in Berlin. Additionally, I possess valuable experience in working with diverse data types, including audio, image and video data. I am proficient in programming languages such as Python, C, and C++, and I am well-versed in deep learning frameworks such as PyTorch and TensorFlow, as well as machine learning framework scikit-learn.