Undergraduate Research Showcase

  • No tags were found...

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

Welcome to Columbia University’s 9th Annual<br />

<strong>Undergraduate</strong> <strong>Research</strong> <strong>Showcase</strong> organized by the Fu<br />

Foundation School of Engineering and Applied Science.<br />

Faculty in the Engineering School and throughout the University<br />

recognize the importance of research in enriching undergraduate<br />

education and strive to make opportunities available for our ambitious<br />

undergraduates. Similarly, our undergraduates recognize the value of<br />

the unique experiences they gain from conducting research and<br />

exploring the cutting-edge of science and engineering disciplines in<br />

world-class facilities. The <strong>Undergraduate</strong> <strong>Research</strong> <strong>Showcase</strong> provides<br />

a venue for undergraduate Columbia University students from<br />

Engineering to share their experiences, discoveries, and enthusiasm with<br />

their fellow peers, faculty, and administrators.<br />

This year, we have seven students participating in the <strong>Undergraduate</strong><br />

<strong>Research</strong> <strong>Showcase</strong> wanting to share their experiences with<br />

you. Projects cover a wide range of subjects that are as varied as our<br />

student-body.<br />

Although we cannot interact in person this year, through the tenacity of<br />

our students, faculty, and the Engineering School, we still have the<br />

opportunity to hear about our students’ cutting-edge research. I<br />

encourage you to partake in the online presentations this year to learn<br />

more about their exciting research - our students continue to do amazing<br />

things in these difficult times!<br />

Barclay Morrison<br />

Vice Dean of <strong>Undergraduate</strong> Programs<br />


Table of Contents<br />

Quantifying Myosin Networks and Their Roles in Morphogenesis 4<br />

Cole James Allan, Mechanical Engineering, SEAS ‘21<br />

Alternating Bubbles Emerging from Two Interacting Vertical Gas Jets in a Liquid 5<br />

Boyuan Chen, Chemical Engineering, SEAS ‘23<br />

Electricity Price Models in the Context of Increasing Renewable Energy Generation 6<br />

Felipe Aleixo dos Santos Couto, Mechanical Engineering, SEAS ‘22<br />

A Parametric, Ultrasound-Based Model of the Uterus in Late Gestation 7<br />

Arielle Feder & Divya Rajasekharan, Mechanical Engineering, SEAS ’22 & ‘21<br />

Automated Artery and Vein Classification of Pulmonary Vessels 8<br />

Anthony Luo, Computer Science, SEAS ‘23<br />


Quantifying Myosin Networks and Their Roles in Morphogenesis<br />

Cole Allan, cja2160@columbia.edu<br />

SEAS ‘21, Mechanical Engineering, Columbia University<br />

Supervising Faculty, Sponsor, and Location of <strong>Research</strong><br />

Dr. Karen Kasza, Bonomi Summer Scholar, Kasza Living Materials Laboratory,<br />

Columbia University<br />

Abstract<br />

Morphogenesis is a process during embryonic development in which cells and/or tissues<br />

develop their shape. These morphogenetic events utilize a network of motor proteins,<br />

non-muscle myosin II, to generate forces. Thus, being able to identify and characterize<br />

this network makes it possible to synthetically control tissue folding, and, potentially in<br />

the future, build robust tissue architectures out of 2-dimensional tissue sheets. The goal of<br />

this study, completed virtually in the Kasza Living Materials Laboratory, was to develop<br />

a software tool that would identify the myosin networks within Drosophila embryos at<br />

various stages of development and to quantitatively assess how the myosin networks<br />

influence the propensity of tissues to remodel. Using confocal microscopy, supracellular<br />

myosin networks were fluorescently tagged in high resolution movies. Some of the<br />

properties analyzed in the developed software include measuring the network<br />

connectivity, measuring the flexibility of each network edge, and identifying regions of<br />

rapidly changing myosin. These properties are essential to characterize the structure of<br />

myosin networks. Specifically, we found that myosin segments became less tortuous<br />

when there was tissue elongation in the same orientation. Additionally, the cell velocity<br />

was tracked to identify distinct regions of tissue that behaved more fluid-like. In the<br />

future, with this understanding of myosin networks and cellular movement, we are<br />

hopeful that we will be able to coordinate cell behavior and manipulate the mechanical<br />

properties within tissues.<br />

Keywords<br />

Morphogenesis, Drosophila melanogaster, Myosin Networks<br />


Alternating Bubbles Emerging from Two Interacting Vertical Gas Jets in a Liquid<br />

Boyuan Chen, bc2878@columbia.edu<br />

SEAS ’23, Chemical Engineering, Columbia University<br />

Supervising Faculty, Sponsor, and Location of <strong>Research</strong><br />

Dr. Christopher Boyce, Bonomi Summer Scholarship, Columbia University<br />

Abstract<br />

Optical imaging experiments of two vertical gas jets injected into a liquid demonstrate<br />

that bubbles pinch off from these jets in an alternating (180 degrees out of phase) pattern.<br />

Image analysis demonstrates that this alternating pattern occurs only at sufficiently high<br />

Froude numbers and sufficiently low ratios of the separation distance between orifices to<br />

the orifice diameter. Otherwise, the bubbles from the two jets breakoff at uncoordinated<br />

times relative to one another. A physical mechanism is proposed in which the alternating<br />

pattern occurs due to a growing jet pushing liquid between the two jets towards the<br />

second jet, such that the second jet pinches off, forming a bubble. This mechanism is<br />

used to formulate a simplified coupled harmonic oscillator model which predicts<br />

qualitatively the transition from uncoordinated to alternating bubble breakoff.<br />

Keywords<br />

Gas jets, asynchronous break-off, coupled oscillator<br />


Electricity Price Models in the Context of Increasing Renewable Energy Generation<br />

Felipe dos Santos Couto, f.couto@columbia.edu<br />

SEAS ’22, Mechanical Engineering, Columbia University<br />

Supervising Faculty, Sponsor, and Location of <strong>Research</strong><br />

Dr. Bolun Xu, <strong>Undergraduate</strong> <strong>Research</strong> Involvement Program, The Earth Institute,<br />

Columbia University<br />

Abstract<br />

Renewable energy is no longer an interesting possibility for the future but rather an<br />

urgent demand in the present to fight the climate crisis. Nevertheless, academia, industry,<br />

and public entities still face many challenges to increase penetration of renewable sources<br />

on the world energy mix. In this context, storing energy has risen as a key alternative and<br />

numerous storage solutions have been developed. The purpose of this study is to better<br />

understand how large-scale energy storage systems (ESS) impact electricity prices. We<br />

developed interpretable machine learning models and analyzed how supply and demand<br />

attributes correlate with price fluctuations – especially, price spikes, which are a major<br />

sign of market inefficiency. Optimal Regression Trees and Multiple Linear Regressions<br />

were applied to the Southwest Power Pool market data, shedding some light upon the<br />

attributes’ sensitivities. We then utilized the sensitivities to estimate price reductions due<br />

to energy storage. Results showed a potential reduction, on average, of 19.0% on price<br />

spikes. Further studies shall continue to investigate the effects grid-scale ESS on prices.<br />

By doing so, we hope to corroborate with the expansion of renewable energy generation<br />

and ESS on the grid.<br />

Keywords<br />

renewable energy, energy storage, interpretable machine learning, electricity price<br />

models<br />


A Parametric, Ultrasound-Based Model of the Uterus in Late Gestation<br />

Divya Rajasekharan & Arielle Feder, dr2940@columbia.edu & adf2153@columbia.edu<br />

SEAS ’21 & ’22, Mechanical Engineering, Columbia University<br />

Supervising Faculty, Sponsor, and Location of <strong>Research</strong><br />

Dr. Kristin Myers, Summer@SEAS, Myers Soft Tissue Lab, Columbia University<br />

Abstract<br />

Pregnancy poses an interesting mechanical problem, as the female body must evolve to<br />

accommodate a growing fetus. Since direct research into the mechanical environment of<br />

pregnancy is precluded for clear ethical reasons, 3D models provide a unique opportunity<br />

to study the mechanical properties of the uterus via simulation. In late pregnancy (LP),<br />

the geometry of the uterus changes distinctly: the elliptical shape of early pregnancy<br />

grows more tapered towards the cervix end, terminating in a V-like profile in the coronal<br />

plane. This shift raises the question of whether geometric changes are necessary to<br />

mediate important developments in the load-bearing properties of the uterus. To<br />

investigate this possibility, we built two uterus models to accommodate the late-gestation<br />

coronal shape with varying degrees of accuracy. The first is based on a limited number of<br />

ultrasound measurements, with overall shape informed by patient-averaged<br />

characteristics derived from MRI. The second is a highly parameterized model, driven by<br />

MRI measurements. Two additional models—a ground truth model segmented directly<br />

from MRI and the lab’s current, elliptical parametric model—were used as points of<br />

reference. By comparing these models’ behavior in a simple static load analysis for 5 LP<br />

patients, we evaluated the mechanical significance of the change in LP coronal shape. We<br />

found that the stress distribution was highly dependent on local fluctuations in uterine<br />

wall thickness. Models based on limited ultrasound measurements were not always<br />

sensitive enough to capture this variation. In the LP models, we observed that the<br />

tapering of the uterus had the effect of drawing pressure loads away from the cervical os<br />

and into the lower side walls, while the blunter coronal profile of early-gestation allowed<br />

stress to concentrate at the os. Finally, the first and second principal strain directions—<br />

oriented circumferentially and longitudinally, respectively—were consistent across all<br />

four models. In conclusion, the late pregnancy uterus exhibits load bearing properties<br />

distinct from earlier pregnancy, mediated by a change in coronal shape. Furthermore, a<br />

parametric modeling framework, which accounts for the coronal shape on a patientaveraged<br />

basis, may be a viable option to efficiently represent the load-bearing<br />

characteristics of the LP uterus when compared to higher resolution, but computationally<br />

intensive, MRI-driven models.<br />

Keywords<br />

pregnancy, biomechanics, 3D modeling, simulation, finite element analysis (FEA),<br />

ultrasound, magnetic resonance imaging (MRI)<br />


Automated Artery and Vein Classification of Pulmonary Vessels<br />

Anthony Luo, anthony.luo@columbia.edu<br />

SEAS ‘23, Computer Science, Columbia University<br />

Supervising Faculty, Sponsor, and Location of <strong>Research</strong><br />

Professor Andrew F. Laine, Summer@SEAS<br />

Heffner Biomedical Imaging Lab, Columbia University<br />

Abstract<br />

An accurate and automatic system for artery and vein classification of pulmonary vessels<br />

has the potential to drastically increase efficiency of medical diagnoses and analyses that<br />

require artery and vein labeling of pulmonary vessels. In particular, labeled arteries and<br />

vessels facilitate site isolation for vascular pathology, and assist inferences of causes of<br />

pulmonary vascular dysfunction. We present a software pipeline to perform automatic<br />

artery and vein classification up to a user specified diameter without the need for contrast<br />

enhanced CT or manual seed point initialization. The performance of this software<br />

pipeline is significantly faster than manual labeling by an expert analyst and provides<br />

additional flexibility through vessel diameter and branch length filtering options. Our<br />

pipeline uses an expert system based approach to classification by leveraging the<br />

closeness and co-orientation of pulmonary arteries and bronchi. Compared to prior art,<br />

our system introduces a novel combination of straight-line and per-voxel co-orientation<br />

and co-distance calculations. We plan to compare our pipeline against a semi-automated<br />

region growing approach and manually annotated ground truth.<br />

Keywords<br />

pulmonary vessels, artery vein classification, airways<br />


Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!