Title: Software-Defined Underwater Acoustic Networks Committee Members: Prof. Tommaso Melodia (Advisor) Prof. Stefano Basagni Prof. Kaushik Chowdhury Dr. Emrecan Demirors Abstract: The exploration, monitoring, and understanding of oceans play a crucial role in addressing climate change, overseeing underwater pipelines, and preventing maritime warfare attacks. To achieve these significant objectives, it is vital to utilize networks […]
Title: Effective and Efficient Continual Learning Committee Members: Prof. Jennifer Dy (Advisor) Prof. Stratis Ioannidis Prof. Yanzhi Wang Abstract: Continual Learning (CL) aims to develop models that mimic the human ability to learn continually without forgetting knowledge acquired earlier. While traditional machine learning methods focus on learning with a certain dataset (task), CL methods adapt […]
Title:Decoupling Efficiency-Performance Optimization for Modern Neural Networks Date: 7/20/2023 Committee Members: Yanzhi Wang (Advisor); Prof. David Kaeli; Prof. Sunil Mittal; Prof. Jennifer Dy Abstract: Deep learning has achieved remarkable success in a variety of modern applications, but this success is often accompanied by inefficiency in terms of storage and inference speed, which can hinder their […]
Title: Real-Time Spectrum Sensing for Inference and Control Committee Members: Prof. Tommaso Melodia (Advisor) Prof. Kaushik Choudhury Prof. Francesco Restuccia Abstract: Through growing cellular innovations, the usage and congestion of the wireless spectrum is increasing at incredible speeds. High demand and limited supply pose a resource issue known as the "spectrum crunch". With the high […]
Title: Leveraging Deep Learning on Multimodal Sensor Data for Wireless Communication: From mmWave Beamforming to Digital Twins Committee Members: Prof. Kaushik Chowdhury (Advisor) Prof. Hanumant Singh Prof. Josep Jornet Dr. Mark Eisen Abstract: With the widespread Internet of Things (IoT) devices, a wide variety of sensors are now present in different environments. For example, self-driving […]
Title: Towards Efficient Deep Learning in Computer Vision via Sparsity and Distillation Committee Members: Prof. Yun Fu (Advisor) Prof. Octavia Camps Prof. Zhiqiang Tao Abstract: AI, empowered by deep learning, has been profoundly transforming the world. However, the excessive size of these models remains a central obstacle that limits their broader utility. Modern neural networks […]
"Synthetic Data Generator: Understanding Human Face & Body via Image Synthesis" Committee Members: Prof. Yun Fu (Advisor) Prof. Sarah Ostadabbas Prof. Ming Shao Abstract: The community has long enjoyed the benefits of synthesizing data, as it provides a reliable and controllable source for training machine learning models while reducing the need for data collection from […]
Title: Securing FPGA as a Shared Cloud-Computing Resource: Threats and Mitigations Committee Members: Prof. Xiaolin Xu (Advisor) Prof. Yunsi Fei Prof. Xue Lin Abstract: With the widespread adoption of cloud computing, the demand for programmable hardware acceleration devices, such as field-programmable gate arrays (FPGA), has increased. These devices benefit the growth of efficient hardware accelerators, […]
Title: Advances in Modelling, Control, and Perception for Soft Robotics and Autonomous Vehicle Systems Location on Campus: Snell Room Committee Members: Advisor: Prof. Milad Siami Prof. Bahram Shafai Prof. Rozhin Hajian - University of Massachusetts, Lowell Abstract: In this research project, we investigate the distributed consensus and vehicle platoons control problem. We first investigate the performance […]
Title: Deep Learning for the Physical Layer: From Signal Classification to Decoding Location: ISEC 532 Committee Members: Prof. Kaushik Chowdhury (Advisor) Prof. Stratis Ioannidis Prof. Robert Nowak Abstract: The growth in wireless spectrum usage has created new physical layer applications and intensified the importance of the existing ones. Physical layer applications ranging from device authentication […]