Neslihan Köse Cihangir, PhD - Zuse School ELIZA

Industrial Fellow
Foundations of ML: Computer Vision
Applications in Autonomous Systems
Alumni

Neslihan Köse Cihangir joined Intel in Germany in 2018 as an AI/ML research scientist. She received her Ph.D. from Multimedia Communications, Télécom Paris, France (2014), and her M.Sc. from Electrical and Electronics Engineering, Middle East Technical University, Türkiye (2009). Prior to joining Intel, Neslihan had worked as a post-doctoral researcher at EURECOM in France and Technical University of Munich in Germany. Neslihan’s research focus is mainly on computer vision, machine learning, and biometrics. Her projects at Intel focus diverse applications such as automated driving, smart manufacturing and trusted media that enable human-AI collaboration targeting efficient and reliable solutions. Her recent research is based on advancing AI technologies using vision LLMs, multimodal RAG, and their application in agentic framework. Her research in explainable AI and uncertainty estimation is pivotal in ensuring responsible AI deployment across various industries. She holds several patents and has authored numerous well-cited papers in top-tier journals and conferences.

Neslihan Köse Cihangir joined Intel in Germany in 2018 as an AI/ML research scientist. She received her Ph.D. from Multimedia Communications, Télécom Paris, France (2014), and her M.Sc. from Electrical and Electronics Engineering, Middle East Technical University, Türkiye (2009).

Prior to joining Intel, Neslihan had worked as a post-doctoral researcher at EURECOM in France and Technical University of Munich in Germany.

Neslihan’s research focus is mainly on computer vision, machine learning, and biometrics. Her projects at Intel focus diverse applications such as automated driving, smart manufacturing and trusted media that enable human-AI collaboration targeting efficient and reliable solutions. Her recent research is based on advancing AI technologies using vision LLMs, multimodal RAG, and their application in agentic framework. Her research in explainable AI and uncertainty estimation is pivotal in ensuring responsible AI deployment across various industries. She holds several patents and has authored numerous well-cited papers in top-tier journals and conferences.

Google scholar