The free-form surface, also termed manifold, is a
smooth 3D skin that contains aesthetic value and
presents functionalities. With the integration of
mathematics, computer-aided design, and
construction techniques, people can bring the
free-form surface into reality. However, how to
achieve an optimal layout on the free-form surface is
still an open topic. In this talk, I will first introduce
my research efforts on topology optimization on the
freeform surface using the extended level set method
and conformal mapping theory. Next, I will present
my work on optimizing a typical adaptive surface- the
origami structure, which can transform from
flattening 2D status to a complex 3D design at a given
crease pattern. In terms of fabricating thin shell
surfaces, I will briefly introduce our surface weaving
method, which can directly construct a 3D surface by
weaving two groups of computed strips. The future
research directions and applications will be discussed
at the end.

The diffraction limit is a fundamental barrier inoptical science and engineering. lt restricts theimaging resolution for both fundamental researchand applications in biology, chemistry, and materialscience industry. Microspheres have beendemonstrated as a powerful platform to challengethe diffraction limit. Microspheres can manipulatelight in a novel way that conventional opticalcomponents cannot achieve. In this presentation.Dr. Chen summarizes his contribution to thefundamental physics,system development,andpotential applications of this technology. The ~20nm observation power was demonstrated forlabel-free samples, which forms the foundation ofopticalsuper-resolutionimaging to observenano-structures in water, oil, and ambient air.

The mission of my research is to answer the question: howcan we provide people with cyber-physical systems (CPSs)they can bet their lives on? Many CPSs are safety-criticalsuch as self-driving cars and critical infrastructures. In thistalk, I will present how my research tackles this problemtowards the goal to enhance the security and safety ofsafety critical CPSs whilst deployed in dynamic, uncertain,and adversarial environments. I will discuss two applicationcases: one is safety assured planning and control for selfdriving cars, the other one is intelligent intrusion detectionfor a water treatment system. For the first application caseI rigorously verify the safety properties of learning-enabledcomponents in autonomous systems and combine formalmethods and optimal control to design safety-guaranteedplanning and control. For the second application case, ldeveloped interpretable symbolic machine learning calledautomata learning to learn hybrid dynamics from dataduring my Ph.D. study. The learned model for a real watertreatment system and intrusion detection results areunderstandable and verifiable for system operators.

Automatically understanding the body posefrom camera inputs promotes many real-lifeapplicationssuchactivityashumanrecognition, autonomous driving,assistantrobotics and sport analysis. This highlydemanding task has seen extraordinaryprogress over the recent years. The success canbe credited to two main factors: effectiveappearance modeling by deep neural networksand the accessibility of large-scale annotateddatasets. However, the current systems are notflawless that still many challenging issues areleft to be alleviated especially when peopleare in complex articulations or several instancesstay close, occluding each other. We argue thatincorporating prior knowledge like the inherentstructure of our body into the network design isequally essential. To this end, in this work, westudy how to design efficient algorithms tojointly optimize the parameters of deep featureextractors and also the probabilistic inferencemodels which encode priors.

介绍轨道交通、道路交通、水运交通以及航空交通等行业的科技发展现状、成就和短板，对国内外交通科技的需求态势和发展趋势进行分析，在总结目前创新发展的基础上，提出交通科技未来发展的目标和总体思路以及各种交通方式的科技发展需求;探讨十四五期间我国交通领域科技创新的主要任务。

This talk will present our projects as examples
which demonstrate the use of a "art to science"
research methodology. Our team adopts a
creative-driven interdisciplinary approach in their
fundamental and applied research on wearable
technologies and its applications to effectively
enable knowledge transfer and realize market
applications. In short, these topics are centered on
understanding the customer experience, social
needs, and the past to shape the future. Aesthetic
research method (or Design thinking research) thus
provides a creative approach try to solve complex
problems in a user-centric manner. These research
works have contributed to discoveries, inventions
and developments which have been adopted by
some of the largest textile manufacturers and
implemented into their products, deriving concrete
financial gains. Yet, we believe there is still room for
improvement and we hope we can do better in the
future.

As indicated in a famous adage "A picture isworth a thousand words, images usually conveya lot of information. It is desirable to separateinput images into multiple layers via imageperception algorithms for people to understandthem easily. In this talk, I will present our imageperception works, which benefit outdoor visionsystems, multimedia, and healthcare. First, I willpresent our innovative methods to addressadverse weather image restoration for outdoorvision systems. Then, I will talk about our works onthe multimedia era, which separates input photosinto layers with textures, shadows, lanes, saliency.and so on. Lastly, l will also describe our Al-basedhealthcare algorithms.

Using robot arms, or a collection of them, to performvarious tasks is becoming increasingly popular inboth industry and our daily life. Recent advances inmachine learning provide us with an opportunity toemploy innovative learning to reach autonomouscontrol. Most existing neural network based robotcontrol methods are designed based on statisticalcriteria with reasonable average performance, butlacks amechanismtoensureworst-caseperformance. This talk will introduce our research onconstructing neural networks based on knowledge ofthe robot model and apply it to solve robot armmanipulation problems. This approach inherits theadvantage of neural networks in adaption andsatisfies guaranteed stability. It provides a tractablesolution using neural networks to address safetycritical tasks with certified performance

Many cities worldwide are embracing electric vehicle(EV) sharing as a flexible and sustainable means ofurban transit. However, it remains challenging forthe operators to charge the fleet because of limitedor costly access to charging facilities. We focus onanswering the core question-how to charge the fleetto make EV sharing viable and profitable. Our work ismotivated by the setback that struck San DiegoCalifornia, where car rental company car2go ceasedits EV-sharing operations. We integrate charginginfrastructure planning and vehicle repositioningoperations that were often considered separatelyMore interestingly, our modeling emphasizes theoperator-controlledchargingoperationsandcustomers' EV-picking behavior. With advancedoperations research models, we find that the viabilityof EV sharing can be enhanced by concentratinglimited charger resources at selected locations. Boththe high-level planning guidelines and operationalpolicies can be useful for practitioners.

Civil aviation is one of the drivers of global growth. It increasesat around 4.4% per annum and is poised to maintain thisgrowth for the next 20 decades. On the other hand, aviation isresponsible for 5% of total anthropogenic radiative forcing andis expected to increase substantially in the future. In the face ofthe continuing expansion of air traffic, mitigation of aviation'sclimate impact becomes challenging but imperative