I am currently Senior Data Scientist @ CARIAD SE (Volkswagen Group). We are building exciting tools for data scientists, computer vision, NLP, systems security, and beyond for the automotive industry.
My interest in both research and engineering cover the areas of: (1) deep anomaly detection, (2) intrusion detection, (3) AI for software engineering, (4) applications, primarily in terms of system data models, NLP, temporal models, and modeling data at scale, which is a great source of inspiration.
Biography
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I studied Computer Engineering at the Faculty of Electrical Engineering and Information Technology in Skopje, Macedonia, where I developed the most interest for machine learning and distributed systems. During 2016/17 I competed at several Kaggle competitions, working on variety of problems. In 2017, I receieved the Bachelor degree. In 2018, I received the Master degree in Computer Science at the Technical University Berlin. During that time I worked on several industry related research projects in collaboration with Huawei German Research Center. I obtained a Ph.D. in Computer Science at the Technical University of Berlin supervised by Prof. Dr. Odej Kao, in 2021. During that time I was working at the Berlin Big Data Center, and at the Berlin Institute for Foundations of Learning and Data (BIFOLD). I worked at the DOS Group at the Technical University of Berlin as Senior Researcher until 2023. During that time (2021-2023) I co-founded logsight.ai, where I was in lead of the technical areas. In April 2023, I joined the Volkswagen Group, at CARIAD Software Engineering, as a Senior Data Scientist to help build the next generation of vehicle software.
Research highlights
- Deep Anomaly Detection in Distributed Software Systems PhD Thesis @ TU Berlin paper
- Self-Attentive Classification-Based Anomaly Detection in Unstructured Logs ICDM 2020: IEEE International Conference on Data Mining (ICDM) paper
- Self-Supervised Anomaly Detection from Distributed Traces UCC 2020: IEEE/ACM International Conference on Utility and Cloud Computing paper
- Self-Supervised Log Parsing ECML-PKDD 2020: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases paper
- Anomaly Detection from System Tracing Data using Multimodal Deep Learning CLOUD 2019 : IEEE International Conference on Cloud Computing (affiliated with IEEE SERVICES 2019) paper
- Anomaly Detection and Classification using Distributed Tracing and Deep Learning The 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing (CCGrid 2019) paper