Omead Pooladzandi
Google ScholarLinkedInEmailGitHub
Omead Pooladzandi is a Ph.D. graduate in Electrical and Computer Engineering at the University of California, Los Angeles. His research focuses on deep learning, optimization, and generative modeling, with a particular interest in applications in speech synthesis, anomaly detection, and signal processing. Omead has published multiple papers in prestigious conferences and journals, including International Conference on Machine Learning (ICML), Neural Information Processing Systems (NeurIPS), and IEEE Statistical Signal Processing and has experience interning at prestigious institutions such as Meta and Jet Propulsion Laboratory. In his free time, he enjoys playing tombak and backpacking.