I am a software engineer, machine learning engineer, and distributed systems researcher with a strong interest in intelligent systems, adaptive computing, and secure, scalable software. I am currently completing an M.Sc. in Computer and Systems Science at Stockholm University, following a B.Sc. in Software Engineering and Management from the University of Gothenburg.

My research interests lie at the intersection of machine learning, distributed systems, edge-cloud computing, optimization, cybersecurity and trustworthy AI.

My master’s thesis, “Adaptive AI Task Partitioning and Offloading in Heterogeneous Edge-Cloud Networks”, investigated how deep neural network workloads can be dynamically distributed across end, edge, and cloud devices. As part of this work, I designed and implemented an adaptive framework that selects execution strategies based on measured latency, communication overhead, and energy consumption. The research has strengthened my experience in algorithm design, distributed communication, performance modelling, experimental evaluation, and scientific writing.

My bachelor’s thesis focused on enhancing a deep learning camera-based approach for contactless heart-rate detection in vehicles. The study examined how non-functional requirements such as explainability, robustness, and reliability can be used to evaluate and improve machine learning systems beyond conventional accuracy measures.

Alongside my research, I have experience building machine learning services, distributed applications, and full-stack systems using Python, Java, C, C++, JavaScript, PyTorch, TensorFlow, Docker, Kubernetes, and modern web technologies. I have also worked as a Teaching Assistant at the University of Gothenburg, where I supported students in systems development and team programming through technical guidance, project supervision, and mentoring.

My long-term goal is to contribute to research in machine learning systems, distributed computing, and AI security. I am especially motivated by research that combines rigorous technical foundations with practical systems development and real-world impact.