10月12日下午，系统枢纽署理院长李世玮教授、生命科学与生物医学工程学域署理主任齐众教授、智能交通学域署理主任杨柳青教授、机器人与自主系统学域署理主任刘明教授、智能制造学域署理主任汤凯教授齐聚系统枢纽会议室，共同开启系统枢纽2023年博士招生宣讲会直播。此次直播共吸引超8000人在线收看，获得4461人按赞。

In recent years, with the implementation of thenational marine development strategy and theconstruction ofa number l of cross-seainfrastructures such as the Hong Kong-Zhuhai-Macao Bridge, the inadequacy of China’ s basicmarine engineeringresearch hasbecomeincreasingly apparent. In the long run, marineengineering is an important link to a maritimepower and an infrastructure for the developmentand utilization of marine resources. Enhancing thebasic theoretical research aroundmarineengineering has a bearing on the effectiveness ofmarine development and is very important to thelong-term development of China's undertakingsTo this end, the team of Prof. Quanke SU from theInstitute of Cross-sea Engineering and IntegratedTransportation of HKUST(GZ) organized a surveyand visited eight units in Nanjing, Tianjin, andQingdao from August 15 to 23,including

In recent years, along with rapid advancements inhigh-performance computing hardware andalgorithms,computer vision-based approacheshave been extensively explored and developed forthe analysis, modeling, and optimization of civiland transportation infrastructure systems. Thisseminar presents the research outcomes by DrZhou, which are focused on automated structuradefects identification. and condition assessmentthrough computer vision and deep learning, andLight Detection and Ranging (LiDAR)-basedapplications for vehicle recognition tasks

Robots play significant roles in reducing human labor costs, increasing work efficiency and improving product quality. As the speed of product renewal accelerates, the demand for flexible lines is becoming more and more evident for small batches or multi-types production. However, most current robots still have large gaps in mechanism, perception and control capabilities compared with humans, making it difficult to adapt to the varying scenarios or tasks. In contrast, humans are better at handling incomplete, contradictory and ambiguous information. Therefore, communion with humans and the environment is an important approach to solving the problem of insufficient robot intelligence.

Plastic waste poses an ecological challenge and enzymatic degradation offers a green and sustainable route for plastic waste recycling. Poly (ethylene terephthalate) (PET) accounts for 12% of global solid waste, and a circular carbon economy for PET is theoretically attainable through rapid enzymatic depolymerization followed by repolymerization or valorization into other products. However, the practical application of PET hydrolases has been hampered by their lack of robustness, slow reaction rates and inability to directly use untreated postconsumer plastics.

Herein, we report the use of a structure-based, machine learning algorithm to engineer a robust and active PET hydrolase. Our best resulting mutant (FAST-PETase: Functional, Active, Stable, and Tolerant PETase) exhibits superior PET-hydrolytic activity relative to both wild-type and engineered alternatives. We demonstrate that whole, untreated, post-consumer PET from 51 different plastic products can all be completely degraded by FAST-PETase within one week, and in as little as 24 hours. FAST-PETase can also depolymerize untreated, amorphous portions of a commercial water bottle and an entire thermally pretreated water bottle at 50 ºC. Moreover, we demonstrate a closed-loop PET recycling process by using FAST-PETase and resynthesizing PET from the recovered monomers. Collectively, our results demonstrate a viable route for enzymatic plastic recycling at the industrial scale.

Materials featuring three-dimensional microarchitectures exhibit various extreme functional properties, including negative thermal expansion, high-efficiency electromechanical conversion, ultrahigh stiffness and damage tolerance. Their remarkable properties are dominated by both the parent material and their microarchitecture and thus, they are commonly referred to as architected metamaterials. The rapid progress in 3D printing techniques has enabled the creation of architected metamaterials and unfolded many potential applications. However, the characterization and applicability of these metamaterials are significantly limited by the manufacturing scalability. Additionally, most currently available 3D printing methods only handle single structural materials, and it remains a challenge to 3D print multifunctional architected metamaterials. This presentation will focus on 3D printing techniques that address these key challenges, the investigation of elusive metamaterial properties, as well as the design and manufacturing of multifunctional architected metamaterials. The talk will first introduce a large-area projection stereolithography system capable of manufacturing submeter scale objects with micro-scale architectures, which enables the investigation of size effect in high-temperature ceramics and fracture toughness of mechanical metamaterials. This talk will then demonstrate the design and multi-material additive manufacturing of a series of robotic metamaterials that seamlessly integrate piezo-active, structural and conducting architectures. These robotic metamaterials can directly serve as micro-robots and achieve multi-degree-of-freedom motion, proprioception as well as responses to remote stimuli. All these works contribute to the understanding of the process-structure-property relationship of architected metamaterials as well as the creation of future intelligent materials and devices.

DNA double strand breaks (DSBs) are highly toxiclesions that can lead to genomic instability. Preciseregulation of DSBs repair is crucial to preserve genomeintegrity, as failure to repair DSBs properly is known todrive tumorigenesis and several human geneticsyndromes. In this seminar, Dr. Liang will describe newhigh throughput genomics and animal modelingapproaches to study the DSBs occurrence and repair.He has developed neural blastocyst complementation(NBC) system, which allows the introduction of geneticalterations into embryonic stem (ES) cells that used togenerate a complete mouse forebrain. He has alsoexploitedhighthroughputgenomicanewtranslocation sequencing method (HTGTS-JoinT-seq)to capture DNA ends arising from a solitary DSBs athigh resolution. Finally, Dr. Liang has applied thesenew methods to elucidate the implications of DSBs andunderlying mechanisms of genomic instability.

我们处理机器人的感知，我们的使命和努力的方向是创建智能系统，同时使用多种感知方式，让它们可以在一个复杂和多样的环境中自主运行。我们专注于那些最适合在大规模和动态的环境、不同的地形中活动的新机器人概念。我们还更热衷于给他们提供在具有挑战性的环境中自主导航的智能。这包括用于人机交互、感知、认知、知识抽象、映射、学习、表示、规划和执行的新方法和工具。在这次演讲中，我将介绍从自动驾驶到交付机器人的感知系统的最新发展。

目前大部分芯片厂商都感觉到遵循摩尔定律之途愈来愈难以为继时，业界一直努力在芯片中以实现更大更复杂的系统来满足市场需求。然而，将如此巨大规模的系统在单一的半导体芯片上实现是非常困难的，整个半导体产业目前也仍在为这种必须跨越工具、制程、设计端并加以整合的技术类别思考适合的解决方案。其中3D IC和异构集成技术能够将来自不同制造者的部件构建在一个芯片系统中，从而解决上述问题，成为了相关产业寻求持续发展的出路之一。为此，香港科技大学（HKUST）于2022年4月26日至28日在线举办为期3天的《3D IC与异构集成国际研讨会》（International Symposium on 3D IC and Heterogeneous Integration），研讨会云集顶尖大学和世界领先企业的科技精英，通过12场讲座和2场小组讨论，分享他们对异构技术最新趋势、机遇和挑战的看法，以期加强国际间的学术交流。

Today's transportation system is rapidly growingin scale and complexity, in terms of both theinfrastructure and transportation participants. Thisrenders safety and efficiency more challenging toachieve than ever before, and thereby posesunprecedented urgency on the intelligence ofthe overall transportation system. Fortunately.the increasingsensingdeploymentofcommunications and computing devices at thetransportation infrastructure,vehicles,andpassengers provide an abundance of data thatrecord the spatial, temporal, environmental andemotional status of the transportationevensystem and its participants. Such data possess thepower of fueling the intelligence in autonomousdriving,systemmodelingtransportationfactorsintransportation economics,humantransportation,and traffic flow modelingandcontrol