TechTalk

Young Scholar TechTalk – Chip-scale Sensing: From Classical to Quantum Regime

Miniature optoelectronic sensors which have features of convenient, reliable, economic, ultra sensitive, and capable of real-time measurement are highly desirable nowadays. However, currently reported optical and electronic sensing devices are still hindered with complex optical components and bulky equipment. Hence, we hope to further minimize the volume of the sensing system and get rid of the dependence on complex, expensive and bulky sensing components. In particular, we demonstrate a micro-scale III-nitride chip that integrates a light emitter (LED) and a photodetector (PD) together, realizing the emission and detection of signals in a single miniature chip. Thus, we have applied the device into some classical sensing, such as pressure, salinity content and cell activities sensing. Additionally, we also conduct integration on the diamond based quantum sensing system, and demonstrate a compact chip architecture (sub ~mm3 volume) being capable of on-chip quantum sensing.

TechTalk – Biomimetic Soft Materials for Bio-Integrated Smart Devices

Biological tissues are soft, dynamic, and water-rich, while abiotic tools are typically rigid, static, and dry. These differences in physical properties have presented challenges for the development of advanced biomedical systems that require interfacing with the human body. In this presentation, I will introduce our recent work on biomimetic soft composites as a platform for engineering bio-integrated devices that can potentially bridge this gap. These synthetic materials capture important structural features of natural soft tissues and exhibit tissue-mimetic reconfigurability, robustness, and functionality, making them advantageous for constructing bio-interfaces. Soft electronic components were also integrated into the biomimetic materials platform, enabling multifunctional systems for physiological sensing and targeted stimulation. Examples of these smart biomedical tools include artificial cartilage and tendons, electroconductive hydrogels, and organ-integrated 3D electronics, which create exciting opportunities in advanced biomedicine.

TechTalk – A “Programmable” Cell Niche Engineering Platform – Multiphoton Microfabrication and Micropatterning (MMM) Technology

In native tissues, cells reside in a complex microenvironment (niche) consisting of factors including neighbor cells, soluble factors, extracellular matrices, topological and mechanical signals. Cell niche is critical in maintaining their phenotype and determining their fates and functions. Reconstituting complex cell niche factors in vitro, either individually or in combinations, in a quantitatively and spatially controllable manner, is critical for investigating the interactions between cells and their niches and hence deriving designing strategies for optimal conditions during cell culture applications and optimal scaffolds for tissue engineering applications. Our lab has developed a multiphoton microfabrication and micropatterning (MMM) technology. Here, the technical capability of the MMM platform in fabricating complex protein microstructures and micropatterns with pre-designed topological features, mechanical properties, extracellular matrix, cell interaction molecules and soluble factors, and biomedical applications including cell niche factor screening for phenotype maintenance and engineering cell niche for cell fate determination will be discussed.

TechTalk – AI for Science: From Scientific Discoveries to Platform Engineering

Artificial Intelligence (AI) has been revolutionizing numerous fields within science and engineering, giving rise to “AI for Science” – a new paradigm for both academia and industry. In this seminar, we will explore how AI algorithms and tools empower researchers to tackle intricate scientific challenges, strengthen collaboration, and expedite the discovery process. We will also envision the future of this field in the era of cloud-native infrastructures and large language models, emphasizing the crucial role of platform engineering in nurturing the growth and development of the entire scientific community. Lastly, we will provide examples to illustrate the potential appearance of such platforms and discuss the path towards their realization.

Young Scholar TechTalk – HOF2 – Interact with Device through Simple and Robust Hand-Over-Face Gesture

Mobile devices have been like an extended part of ourselves, but can we really operate a mobile device just as naturally as how we control our fingers or body? We present HOF2, a novel input modality that uses simple gestures over your face to interact with your device. Unlike other gesture-based modalities, HOF2 is highly robust and can avoid false triggering caused by many unconscious gestures like scratching or wiping, while is still easy, comfortable and natural to use. Moreover, HOF2 is highly available and can be implemented on any mobile phone/tablet/computer with a single camera and without remote servers. In this TechTalk, we will present a live demo on iOS/iPadOS demonstrating the performance of HOF2 scheme in practice and explore some real-life use cases such as virtual conferencing, selfie, or TV controller. We believe there are far more possibilities waiting to be explored with this novel interaction scheme.

TechTalk – Learning Optimal Auctions from Data

The design of optimal auctions for revenue maximization is a central topic in Economics. Classical optimal auction theory assumes that bidders’ values are drawn from a known distribution. In reality, the source of such prior information is really past data. Cole and Roughgarden (2014) modeled past data as i.i.d. samples from the value distribution and asked: How many samples are sufficient/necessary to learn a near optimal auction? This TechTalk will introduce a unified theory that yields sample-efficient algorithms with optimal sample complexity for auctions with homogeneous goods, and state-of-the-art sample complexity for auctions with heterogeneous goods. Unlike conventional statistical learning theory which focuses on the complexity of hypothesis classes, our new theory relies on the simplicity of data distributions and a monotonicity property of these problems.

Young Scholar TechTalk – High-throughput Cell Mechanics Characterization with Microfluidics

Cells can sense mechanical stimuli and convert them to biochemical signals for various specific cellular responses, such as stem cells differentiation, initiation of transcriptional programs, and cell migration. Cell mechanics focuses on the mechanical properties and behaviours of living cells and how cell mechanics relates to various cell functions. Currently, traditional cell mechanics measurement methods are cumbersome, low-throughput, and expensive to deploy. By exploiting microfluidic technology, Dr. Johnson Cui is investigating the cancer cell mechanics and developing an accurate, easy-to-use cell mechanics measurement platform for cell mechanics research and also for cancer diagnosis and therapeutics in the future.

TechTalk – Robotics and AI for Real-world Challenges

Current AI cannot provide a complete solution for robotics, although AI is a useful tool for real-world challenges that cannot be solved by traditional methods. We will discuss how AI can be applied to solve real-world problems using robotic systems developed by our team so far. Inspired by a dance partner robot developed for the Aichi Expo in 2005, a co-worker robot “PaDY” was developed for the automotive assembly process. Intention estimation was a key to these collaborative robots. AI has also led to the development of robotic applications in manufacturing, such as computer vision for bin picking, grasp planning, robot motion planning, and assembly of textureless industrial parts using visual servoing. Recent advances in AI are making it possible to tackle the manipulation of soft materials. The JC STEM Lab of Robotics for Soft Materials funded by the Hong Kong Jockey Club Charities Trust covers this new field.

TechTalk – IoT and Machine Learning for Smart Water Auditing

The Artificial Intelligence of Things (AIoT) is the combination of Artificial intelligence (AI) with the Internet of things (IoT) to enable autonomous decision-making, data analytics, and system optimization. AIoT for smart cities allows the collection of enormous sensor data for a better understanding of the environment, human behaviors, and city operations, which leads to more efficient resource management and promotes a sustainable and healthier society. The Smart Water Auditing project aims to use IoT and machine learning to provide insights into how water is being used in the households of Hong Kong to reduce the consumption of water and raise awareness of people’s water consumption habits. Our talk will present our design workflow, IoT infrastructures, machine learning algorithms, and experimentation for water end-use disaggregation in Hong Kong.

Young Scholar TechTalk – Learning to Control and Coordinate Hybrid Traffic Through Robot Vehicles at Complex and Unsignalized Intersections

Intersections are essential road infrastructures for traffic in modern metropolises; however, they can also be the bottleneck of traffic flows due to traffic incidents or the absence of traffic coordination mechanisms such as traffic lights. Thus, various control and coordination mechanisms that are beyond traditional control methods have been proposed to improve the efficiency of intersection traffic. Amongst these methods, the control of foreseeable hybrid traffic that consists of human-driven vehicles (HVs) and robot vehicles (RVs) has recently emerged. We propose a decentralized reinforcement learning approach for the control and coordination of hybrid traffic at real-world, complex intersections–a topic that has not been previously explored. Comprehensive experiments are conducted to show the effectiveness of our approach. We show that using 5% RVs, we can prevent congestion formation inside the intersection under the actual traffic demand of 700 vehicles per hour. When there exist more than 50% RVs in traffic, our method starts to outperform traffic signals on the average waiting time of all vehicles at the intersection.