PhD Dissertation Defense: Active Resource Partitioning and Planning for Storage Systems using Time Series Forecasting and Machine Learning Techniques Maher Kachmar Location: Zoom Abstract: In today's enterprise storage systems, supported data services such as snapshot delete or drive rebuild can result in tremendous performance overhead if executed inline along with heavy foreground IO, often leading […]

PhD Dissertation Defense: Can We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning Kaidi Xu Location: Zoom Link Abstract: Deep learning has achieved extraordinary performance in many application domains recently. It has been well accepted that DNNs are vulnerable to adversarial attacks, which raises concerns of DNNs in security-critical applications and […]

PhD Proposal Review: Towards Efficient Deep Neural Network Execution with Model Compression and Platform-specific Optimization Xiaolong Ma Location: Zoom Abstract: Deep learning or deep neural networks (DNNs) have become the fundamental element and core enabler of ubiquitous artificial intelligence. Recently, with the emergence of a spectrum of high-end mobile devices, many deep learning applications that […]