David Helmbold received PhD in Computer Science from Stanford University in 1987 where he worked on parallel algorithms and the debugging of parallel programs. He joined the Computer Science Department at UC Santa Cruz where he has been a faculty member for over 25 years. At Santa Cruz his research interests shifted to theoretical Machine Learning, with an emphasis on boosting methods and on-line learning algorithms. He is a long-standing member of the computational learning theory community, having hosted the COLT conference and served on the COLT steering committee. David Helmbold's current research centers around machine learning and computational learning theory. In addition to theoretical work, he has applied learning algorithms to practical problems such as determining when to spin down a disk drive in a portable computer to save power.