Electrical and Electronic Engineering

June 19, 2025 (Thursday) 4:30-5:30pm
With modern AI seemingly transforming all aspects of our modern society like magic, it is easy to forget the impacts such modern technology marvel is causing to our fragile environment. From massive industry-scale training of large neural networks of epic sizes, to the proliferation of folding AI inference in our everyday activities, AI applications are rapidly increasing the stress to our global energy and water infrastructure. The coming era of AI demands not only the smartest AI models, but also a new generation of sustainable AI mindset that rethinks the when and how to apply AI intelligence.
In this talk, Professor So will discuss one angle that addresses the “how” question with intelligent algorithm-architecture co-designed systems that reduce both energy consumption and computing latency using dynamic sparse processing. Sharing the same “more is less” principle, a series of works from a dynamic sparse processing system for event cameras to token-steering in modern diffusion models will be discussed. Together, these works illustrate that by doing a little bit more upfront intelligently, it is possible to drastically reduce the amount of work necessary to perform the same AI inference operation during run time without affecting the accuracy of a model. The results are solutions that not only are fast, but they are also orders of magnitude more energy-efficient than typical GPU-accelerated systems.

October 10, 2024 (Thursday) 4:30-5:30pm
Despite a half-century of advancements, global MRI accessibility remains limited, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using permanent 0.05 Tesla magnets and deep learning for electromagnetic interference elimination, we developed highly simplified 0.05 Tesla MRI systems that operate using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging both brain (Nature Communications 2021) and various anatomical structures at whole-body level (Science 2024). Furthermore, we developed three-dimensional deep learning reconstruction methodologies to boost image quality by harnessing extensive high-field MRI data (MRM 2023, Science Advances 2023, Science 2024). We hope these advances will eventually lead to a new class of affordable and computing–powered ultra-low-field MRI scanners for point-of-care applications, addressing unmet clinical needs in diverse health care settings.

June 27, 2024 (Thursday) 4:30-5:30pm
Speaker: Professor Leo Tianshuo Zhao, Assistant Professor, Department of Electrical and Electronic Engineering, Faculty of Engineering, HKU
This talk will highlight our previous works about developing heavy-metal-free NC materials and efficient surface modification for near-infrared optoelectronic devices and advancing scale-up fabrication of NC sensor devices for IoT technologies. The talk will also include our recent work on the nanoprinting of NCs to acheive multi-material and multi-functional devices.

June 06, 2024 (Thursday) 4:30-5:30pm
Humans live in a 3D world, continually acquiring diverse skills and engaging in various activities through perceiving, understanding, and interacting with it. Our long-term research objective is centered on simulating the 3D world and empowering AI systems with 3D spatial understanding capabilities. In this talk, I will start by discussing our recent research efforts in creating 3D interactive environments by reconstruction, decomposition, and generation. Subsequently, I will explore how we can equip machines with the ability to comprehend and reason within a 3D environment by adopting a data-centric approach. Lastly, I will examine the possibilities of integrating 3D environment simulation and understanding to facilitate the emergence of closed-loop active intelligence. In summary, this talk will encompass our latest efforts in 3D reconstruction, comprehension, and creation, ultimately aiming for AI systems that can effectively navigate and engage with our 3D world.

May 30, 2024 (Thursday) 4:30-5:30pm
Visual content generation has achieved great success in the past few years, but current visual generation models still lack controllability and compositionality. In real applications, we desire highly controllable visual generation models which allow users to control the generated contents in a fine-grained manner. We also desire models which can effectively compose objects with different attributes and relationships into a complex and coherent scene. In this talk, I will introduce our several works towards controllable and compositional visual content generation. I will introduce T2I-CompBench for benchmarking compositional text-to-image generation. I will also introduce our recent works on drag-based video editing, controllable 3D generation, and training-free massive concept editing in text-to-image diffusion models.

May 23, 2024 (Thursday) 4:30-5:30pm
Future power systems will need to accommodate a high penetration of renewables, new loads, and increased interconnections, which can make the system less resilient to changes and faults. However, traditional power system stability analysis methods may not be sufficient to ensure stable and robust operations in these new environments. To address this, network science is emerging as a promising area for developing new solutions. This seminar proposes a new framework for power system stability analysis that integrates network-based models with traditional power system theory. The focus will be on understanding how power network topology impacts the stability of the system, shedding new light on instability mechanisms.

April 18 2024 (Thursday) 5:00-6:00pm
Photonics has played a vital role in shaping information technology infrastructure. Now it is considered crucial for addressing the emerging bandwidth constraints and power consumption challenges in hyperscale datacenters and high-performance computing systems. Central to these photonic solutions are photonic integrated circuits (PICs) which have seen dramatic progress in the past decades. A heterogeneous silicon photonics platform that integrates materials with superior properties is projected to fully unlock the application potentials of PICs. Examples include combining novel light sources (e.g., optical frequency combs and narrow-linewidth lasers) with other functional components on a single chip, to construct PICs with complete optical functionalities and advantages in terms of integration density, energy consumption and performance. In this talk, I will introduce the recent progress of heterogeneous silicon photonic integrated circuits and outline the prospects.