PhD Dissertation Defense: Real-World Applicable Deep Learning Techniques: From Efficient Modeling to Automated Model Optimization Ning Liu Location: Zoom Link Abstract: Recently, deep neural networks (DNNs) have been widely studied and achieved tremendous success in a variety of real-world applications, such as computer vision, medical diagnosis and machine translation. Deep reinforcement learning (DRL), as an […]
PhD Proposal Review: Design, Modeling and Operation of Plasmonic Devices for Smart Communication Systems in the Terahertz Band Arjun Singh Location: Teams Link Abstract: The terahertz (THz) band is an attractive spectral resource for future communication systems, for supporting very high-speed data rates and increasingly dense networks. However, the lack of a well-developed technology that […]
MS Thesis Defense: Allocating One Common Accelerator-Rich Platform for Many Streaming Applications Jinghan Zhang Location: Zoom Link Abstract: Many demanding streaming applications share functional and structural similarities with other applications in their respective domain, e.g. video analytics, software-defined radio, and radar. This opens the opportunity for specialization (e.g. heterogeneous computing) to achieve the needed efficiency […]
PhD Proposal Review: The perils of shared computing: A hardware security perspective Majid Sabbagh Location: Teams Link Abstract: The enormous computation power of modern processors and accelerators has rendered them shared computing resources for multiple users and applications, both in the cloud and on the edge. Despite software techniques for security such as virtualization and […]
PhD Proposal Review: Automation Design and DNN Acceleration Algorithms: From Software Implementation to Hardware Physical Design Hongjia Li Location: Zoom Link Abstract: Deep learning has been growing at a fast pace in recent years and has been expanded into many application fields, with a wide range from image recognition, object detection to medical applications. Meanwhile, […]
PhD Proposal Review: Towards Robust Image Classification with Deep learning and Real-Time DNN Inference on Mobile Pu Zhao Location: Zoom Link Abstract: As the rapidly increasing popularity of deep learning, deep neural networks (DNN) have become the fundamental and essential building blocks in various applications such as image classification and object detection. However, there are […]
PhD Proposal Review: Unsupervised Learning of Low-Dimensional Dynamical Representations from Spatiotemporal Data Amirreza Farnoosh Location: Zoom Link Abstract: Ever-improving sensing technologies offer a fast and accurate collection of large-scale spatiotemporal data, recorded from multimodal sensors of heterogeneous natures, in various application domains, ranging from medicine and biology to robotics and traffic control. In this proposal, […]
PhD Proposal Review: Towards Empirical Implementation and Theoretical Analysis in Adversarial Machine Learning Kaidi Xu Location: Zoom Link Abstract: Deep learning or deep neural networks (DNNs) have achieved extraordinary performance in many application domains such as image classification, object detection and recognition, natural language processing and medical image analysis. It has been well accepted that […]
PhD Proposal Review: Metamaterial Absorbers for Infrared Sensing Microsystems Sungho Kang Location: Zoom Abstract: Infrared (IR) spectroscopic sensing has become a key technique in multidisciplinary environments such as military applications, industrial safety control, and smart homes, by providing an accurate and non-disruptive analysis of the target objects. Recently the demand for high performance and compact […]
PhD Proposal Review: Robust Processing against Interferences in GNSS Navigation Haoqing Li Location: Zoom Link Abstract: Satellite-based navigation is prevalent as positioning applications among our lives, how-ever, this high reliance brings potential threats when different interferences and jamming signals are considered. Jamming devices, although illegal in many countries, can be easily to get. Those devices […]