Tajana Rosing

Tajana Rosing is a Professor at the University of California, San Diego, specializing in hyperdimensional computing, neural network acceleration, and edge AI systems. Her work bridges hardware-software co-design for IoT, biomedical applications, and security-enhanced computing.

• University: University of California, San Diego
• Research Focus: Hyperdimensional Computing, Edge AI, IoT Systems, Neural Acceleration, Secure Machine Learning

Her recent publications focus on energy-efficient neural network acceleration (e.g., Processing-in-Memory architectures), few-shot learning for edge devices, and hyperdimensional methods for sensor data and biomedical applications. She explores robustness against adversarial attacks and federated learning frameworks.

Key trends include hyperdimensional computing for multimodal sensor fusion, transformer optimization via hardware-software co-design, and privacy-preserving edge AI. Collaborations often involve co-authors like Xiaofan Yu, Minxuan Zhou, and Onat Güngör.

Her work impacts domains such as healthcare (glucose prediction, ECG analysis), cybersecurity (intrusion detection), and bioinformatics (mass spectrometry, viral sequence analysis).