ESE Fall Seminar – “Deep Latent Variable Models for Compression and Natural Science”
Latent variable models have been an integral part of probabilistic machine learning, ranging from simple mixture models to variational autoencoders to powerful diffusion probabilistic models at the center of recent […]
ESE Fall Seminar – “Reflections on learning about learning: A case study on where ideas come from in (In-)Secure Processor Design”
When it comes to security, hardware is the new software. Starting some years ago, this shift was made plain when a litany of attacks, such as “Spectre/Meltdown” and “Rowhammer”, shattered […]
ESE Fall Seminar – “Power to the People (and to the Datacenters)! Achieving the dream of a clean and reliable electricity supply”
Most of us think of electricity as a clean and reliable source of energy, which flows out of the plug whenever we need it. The reality is far more complex. […]
ESE Fall Seminar – “Beyond the Exit of the Device Miniaturization Tunnel”
For the past fifty years, researchers of semiconductor technology have felt like walking inside a tunnel. There was a single path forward – two-dimensional down-scaling of device sizes, also referred […]
ESE Fall Seminar – “Big AI for Small Devices”
As artificial intelligence (AI) transforms industries, state-of-the-art models have exploded in size and capability. However, deploying these models on resource-constrained edge devices remains a significant challenge. Smartphones, wearables, and IoT […]
ESE PhD Thesis Defense: “Aluminum Scandium Nitride Ultra-Wideband Resonator and Filter Systems”
Aluminum scandium nitride (AlScN), a ternary alloy by doping scandium into aluminum nitride (AlN), has circumspectly gained recognition through the last decade as one of the promised materials in forming […]
ESE Ph.D. Thesis Defense: “Integrating graphene Hall sensors with co-designed silicon circuits for high-throughput magnetic biosensing”
The limitations of silicon electronic devices increasingly constrain the performance of silicon integrated circuits (ICs) and their use in new applications. Next-generation devices with exceptional performance and new functionalities have […]
ESE Ph.D. Thesis Defense: “Fair and Generalizable Machine Learning for Neuroimaging”
Machine learning has been widely adopted to medical imaging research, yet it suffers from domain shift for real world applications. Due to the heterogeneity of medical data, machine learning-based diagnostic […]
ESE Ph.D. Thesis Defense: “Graph Machine Learning under Requirements”
Graphs are powerful mathematical tools that enable modeling of complex systems. Graph machine learning exploits possibly unknown data structures, which provides a unified approach to tackle a wide variety of […]
ESE Seminar: “Designing emerging computing systems with ferroelectric devices”
This talk will present a brief overview of advances in ferroelectric devices and their integration into computing systems to provide novel functionality and energy efficiency in various data intensive applications. […]