With over half a billion years of evolutionary history, fishes swim with high efficiency, great agility, and surprising stealth in the three-dimensional aquatic environment. Therefore, it is undoubtedly natural for engineers to turn to fish as a source of new ideas on underwater propulsive systems.

Over the past decades, roboticists, inspired by these biological systems, have constructed various fish-like robots that copy real fish morphology, locomotion, and movement.

Recently, the direction of bio-inspiration has started to flip to bio-understanding----using robotics in engineering to help answer questions in biology.

In this talk, I will first introduce how we construct and control the robotic fish following the paradigm of bio-inspiration. Then, I will give examples of applying real and virtual robots to help us explore why and how do fish school. Finally, I will briefly introduce my ongoing and future work in bio-inspiration and bio-understanding.

Rail is safe, efficient, and environmentally friendly formoving large volumes of passengers and freight overlong distances. Safety is the top priority for global railsystems. In the age of Industry 4.0 empowered by theuse of the Internet of Things (loT), advancedcommunications technologies, artificial intelligence(Al),andautomation technologies, the railtransportation system is stepping onto a new phase ofrapidproactive,digital,developmenttowardintelligent safety and risk management. Thispresentation will introduce several cross-disciplinary.rail-centric A and data analytics-related studiesconducted at the Rail and Transit Program at RutgersUniversity, in close collaboration with the U.S. railindustry. Particular examples include predictivemodeling of rail infrastructure degradation, as well asreducing fatalities and injuries on railways through theuse of Al and communications-based advanced traincontrol technologies.

The performance of semiconductor integrated
circuits can be improved through 3Dintegration
of additional layers in the post-Moore era.
However，3Dintegrationofoptoelectronics
remains a technological challenge.3Dprinting
has been emerging as a disruptive approach to
manufacturing due toitssimpledesign-friendly
manner. Over the past decadesscientistsand
engineers have continually developed methods
for a diverse selection of materialshigh
precision and throughput that are essential for
3D optoelectronic devices but so far this still
remains a great challenge. In this talkIwill
introduce my
study
of
developing
high-performance 3D nanoprintingtechniques
for advanced 3Doptoelectronics.Thestudy
consists of two parts:(1)developmentof
advanced 3D printing techniques for functional
semiconductor materialswhere nanopipette
confined supersaturation is localized for creating
freeform perovskites 3D nanostructures as3D
nanopixels
and
heterostructures.(2)
Development of parallel 3D nanoprinting in a
liquid meniscus or a droplet form todeliver
materials ink that improves the throughputThis
study will enable a true manufacturing platform
for next-generation 3D optoelectronic devices.
making a great impact oninterdisciplinary
manufacturing and materials science fields such
as stretchable electronicsphotonicsand
biomedical engineering.

Neuromuscular junctions (NMJs) are synapses formedbetween motoneurons and muscle fibers, andcharacterized with high density of acetylcholinereceptors (AChRs) at postsynaptic membrane. Rapsyna postsynaptic adaptor protein, anchors AChR to thecytoskeleton and induces AChR cluster formation. Ourrecent result shows that rapsyn is an E3 ligase whichneddylates subunits of AChR and promotes AChRclustering. However, how these processes are regulatedremains unclear. To this end, we firstly focus on rapsynmutationsidentifiedin congenital myastheniasyndromes (CMSs)，a group of heterogeneous NMJdisorders characterized with muscle weakness andfatigues. Through studying disease-related mutation.we found that rapsyn become tyrosine-phosphorylatedin response to upstream signaling. Phosphorylation ofrapsyn promotes its self-association and E3 ligaseactivity and thus promotes AChR clustering, suggestinga signaling molecule of rapsyn. Moreover, we combinedbiochemical assay with cellular culture and in vivoassay and found that rapsyn undergoes liquid-liquidphase separation (LLPS) and condensates intoliquid-like assemblies. Such assemblies can recruitAChRs, cytoskeletal proteins, and signaling proteins forpostsynapticdifferentiation, revealing a novelmechanism of rapsyn in postsynaptic assembly.

A mircoLED display is a self-emissive display
comprising millions of micrometer-scale LEDsIt
potentially outperform LCD and OLED display not
only because its higher power efficiency, better
image quality, wider color gamut but also due to its
good scalability, transparency, flexibility and other
characteristics. lt is an emerging technology
expected to disrupt the display market. For
manufacturing microLED displays, tens of millions
of microscopic LED chips need to be transferred
and assembled at a high through-put with an
ultra-high yield. There is significant investment
across both industry and academia, and the
technology is advancing very quickly in this field;
however, there is no existing approach that has
demonstrated a cost-effective way of doing it. in
this talk, I will introduce the background of the
application and review state-of-the-art mass
transfer development for microLED display
manufacturing. Methods including elastomeric
stamping, fluidic assembly, laser printing, etc. will
be discussed and assessed in details.

Visual localization refers to the recovery of theposition and orientation of cameras in known orunknown scenes, using only visual data. We humansuse vision as our primary source of informationfor localization, navigation, and exploration in ourenvironments. Similarly, a high-quality image with awide view of the surroundings often capturessufficient information to represent a locationuniquely. Therefore, using images to localize agentsin a map is an important research area of computervision and robotics. lmmediate consequences ofsolving the visual localization problem leads toexciting and potentially revolutionarymanyapplicationsincluding; humanassistance,autonomoussystems,andaugmented reality.Intuitively, by answering questions such as "Wheream lin the scene?”or “ How to render objects foraugmented reality? ”In this talk, I will present theproblem of visual localization in large scale scenesand recent progress in this direction. The talkcontentswill include,scenereconstruction.understanding,abstraction,andalgebraicframeworks to exploit them forlocalization.Different applications of the visual localizationsystems will also be demonstrate

The problem of verifying whether a high levespecification can be decomposed into localspecifications is of fundamental importancein top-down distributed supervisory controlbut unfortunately the state-of-art verificationalgorithm is of exponential time complexityIn this seminar, we talk about an approachfor reducing its verification complexity andsupporting its parallel verification by usingdivide-and-conquer reductions. We addressthe problemof generatingoptimalreductions automatically. A (partial) solutionto this problem is provided, which consists of1) an incremental algorithm for theproduction of candidate reductions and 2) areductionvalidationprocedure.Astrengthenedsubstitution-basedprooftechnique is used for automatic reductiona fixedvalidation,whiletemplate ofexamples is used forcandidate counterreduction refutation.

In the context of robotics and autonomous systems, theiterative linear quadratic regulator (iLQR) is known to bean effective approach to deal with the nonlineardynamical models in motion planning problems.However, it is the major shortcoming of the iLQR that themethod is not efficient when other complex constraintsare involved, such as the collision avoidance constraintTo overcome this rather significant impediment, a fastand efficient optimization algorithm is developed basedon the alternating direction method of multipliers(ADMM), such that the optimization problem is separatedinto severalmanageable sub-problems and theoptimization process can be accelerated to realizereal-timecomputation. In addition, leveraging thearchitecture of iLOR and neural network, another motionplanning algorithm is developed that avoids the priorknowledge of the system model. Depending solely onmeasurement data, it yields a completely non-parametricroutine for the establishment of the optimal policy. Asclearly indicated from the results attained in severalillustrative examples, these significant merits of theproposed algorithms are demonstrated rather evidently.

Visualizing the flow physics and structural dynamics
is critical to our comprehension of fluid-structure
interaction phenomena, which are pervasive in
engineering and biological systems. Traditional
measurement techniques relyon single-input
sensors and optical diagnostic tools, which often fail
to capture fluid-structure interactions that are
transient in nature, hindering our understanding
of their physical underpinnings. In this talk, i will
present my recent effort in the manufacturing of
multi-input smart sensors that are capable of
capturing velocity and pressure of an airflow, and
quantifying the deformation and UV damage of a
structure. This effort is complemented by the
development of a multi-input optical measurement
technique, which can accurately capture highly
transient fluid-structure interactions. Finally, I will
briefly discuss other techniques I have employed
for the study of fluid-structure interactions, ranging
from evolutionary algorithm-based optimization of
highway infrastructures, to
continuum
mechanics-based modeling of soft active sensors
and actuators, and data-driven modeling of animal
swimming.

The COVID-19 outbreak exposed the vulnerability ofthe global supply chain to a wide audience. Fromtransport and logistics perspective, port congestionshave seriously disrupted the cargo flows in the globalsupply chains. This talk will focus on containershipping industry. Firstly, l will present a few studiesthat we conducted to enhance operation efficiency atport yard and landside that help reduce portcongestion and emissions. This includes optimizingoperations at seaport rail terminals, optimizingcontainer retrieval and reshuffling, and smart stackingat container yard. Secondly, taking the supply chainviewpoint, I will explain the challenging issues incontainer shipping supply chain (CSSC) by focusing ondigitalization and decarbonization. Possible pathwaytoward digitalization andpathwaytowardsdecarbonization in CSSC will be discussed includingfuture research opportunities.