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A&S Undergraduate Student Lightning Talks

Wednesday, September 21, 2022
11:00 am to 12:30 pm
Floor/Room #: 
Odeum A&B

Join us as the Arts & Sciences undergraduate Summer research students present lightning talks on their projects.

 

 

 

 

 

 

 

 

 

 

 

 

Summer 2022 STAR & DraftKings Research Projects

Lauren Abraham

Class of 2024
Major: Biology & Biotechnology
Advisor: Professor Natalie Farny - Biology & Biotechnology

Together with Kylie Hoar & Alexis Rock

Title: Isolation of Soil Bacteria and Co-Culturing with Genetically Engineered Pseudomonas putida

Abstract: This research explores the relationship between genetically engineered microbes (GEMs) and soil bacteria from the environment. GEMs can be used for a variety of different functions in the soil, but the relationships these GEMs have with their competitors are largely unknown. By conducting competition assays with a flow cytometer, it is possible to observe these relationships between isolated soil bacteria from the environment and genetically engineered Pseudomonas. These discoveries motivate further research into the relationships P. putida has with certain soil conditions and with naturally-occurring soil bacteria.

Abigail Boafo

Class of 2024
Major: Society, Technology & Policy
Advisors: Professor Crystal Brown & Professor Hermine Vedogbeton -  Social Science & Policy Studies

Title: The Black Student Experience in Colleges/Universities and its Relation to WPI

Abstract: The Black student experience in the United States has been overall a negative one. With many students reporting feeling high levels of stress and racial discrimination while attending four- year institutions. This research aims to highlight the relationship between race and education to understand the adversities of BIPOC students. It also highlights the institutional practices Worcester Polytechnic Institute (WPI) can use to ensure that Black students have the proper resources to succeed in completing their degrees and obtaining jobs in the future.

Sydney Gardner

Class of 2023
Major: Interactive Media & Game Development
Advisors: Professor Farley Chery - Interactive Media & Game Development

Together with Conor Dolan & Juliet Morin

Title: Modeling Diversity - Rigs of Color

Abstract: The majority of 3D models that are easily accessible online appear Caucasian, and those that aren’t are often inaccurate or insensitive. The purpose of this research is to combat the limited and false representation of ethnic identities in 3D animated mediums by developing characters with varying race, ethnicity, and body types. Throughout this summer, we have each gone through the process of creating two diverse characters from start to finish. Once completed, our characters are passed onto a group of technical artists who prepare them for animation, and these characters are then made easily accessible online. We started out by doing plenty of research on anatomy as well as gathering concepts for our characters. We used this research to make mood boards, creating detailed character concepts, all while being careful to exaggerate rather than stereotype. Finally, we went through the process of creating our characters in ZBrush.

Thomas Kneeland

Class of 2024
Major: Computer Science/Music
Advisors: Professor Ben Young - Director of Jazz History Database

Title: Correlating Sound and Intent in Rudd's Numatik Swing Band

Abstract: This JHDb initiative examines composer Roswell Rudd's 1971-73 masterwork Numatik Swing Band. This research crossmatches the gestures prescribed in the written music with the audible outcomes on the definitive recording--analyzing in particular Rudd's innovative approach to organizing non-standard playing techniques for a custom instrumentation. The project will generate a listen-and-view digital experience that synchronizes the score image and recorded sound, annotated with live-action demonstration on brass instruments.

Daniel Larabee

Class of 2023
Major: Bioinformatics & Computational Biology
Advisors: Professor Scarlet Shell - Biology & Biotechnology

Together with Junpei Xiao, Opeyemi Ibitoye and Hilario Cafiero

Title: Identifying Targets of Putative Small Regulatory RNAs in Mycobacterium Smegmatis

Abstract: Mycobacterium tuberculosis kills 1.2 million people every year. To find ways to treat it, we must understand how it regulates its own gene expression to survive in the harsh conditions of the human body. sRNAs are known to regulate translation and mRNA degradation in other organisms. The Shell lab and their collaborators identified 34 putative sRNAs in M. smegmatis. However, their effects on mRNA degradation are unknown. 2 putative sRNAs were chosen for further investigation. I will determine the effects that these candidates have on mRNA degradation by deleting the sRNAs, followed by quantitative PCR to find any changes in target mRNA abundance. Additionally, specific parts of the candidate sRNAs will be mutated so that the sRNA can no longer bind to its target mRNA. This would reveal whether there is a direct interaction between an sRNA and mRNA, or if their relationship involves mediators.

Cole Parks

Class of 2024
Major: Robotics Engineering/Computer Science
Advisors: Professor Carlo Pinciroli - Robotics Engineering

Title: How Do Robot Swarms Learn Collective Transport?

AbstractCollective transport is a compelling robotics coordination problem. Solutions can be found by using deep reinforcement learning (DRL) methods in which robots are physically constrained to the object being transported. However, the DRL process is difficult to analyze due to the black-box nature of the deep neural networks. Being able to uncover the logic of these networks would further our understanding of how DRL works in multi-robot settings. To investigate this, we sample the robots’ learning curve at critical points. For each point, we derive a human-readable equation that matches the neural network using a novel symbolic regression method. Preliminary results are promising.

Allison Rozear

Class of 2024
Major:  Human and Machine Communication 
Advisor: Professor Yunus Doğan Telliel - Humanities and Arts

Title: RI/FoW: Research Impact for the Future of Work

Abstract: This is an ongoing study which investigates the relationship between researchers and the broader impacts of the work they are carrying out with the goal of the creation of a digital tool. This tool is designed with the objective to guide researchers, specifically STEM researchers, through concepts related to broader impacts. Unlike other Broader Impacts support tools used for proposal writing, this tool has a focus on the future of work, workers, and the workplace, as well as an explicit goal to prioritize social justice concerns. The tool is being designed with a close engagement with the North American community of Broader Impacts professionals and researchers, as well as STEM researchers with funded projects on the future of work.

Rachel Swanson

Class of 2023
Major: Chemistry and Chemical Engineering 
Advisor: Professor Patricia Zhang Musacchio - Chemistry and Biochemistry

Title: Development of a C-H Acylation Reaction in Batch and in Flow

Abstract: This project investigates C(sp3)-H functionalization for the direct formation of a ketone functional group in both adaptations in batch and flow chemistry. This is a newly developed mechanism to turn chemicals derived from petroleum, hydrocarbons, into more useful compounds, ketones, to extend their potential for chemical transformation. This reaction uses photochemistry to begin the reaction and more specifically, relies on blue light. Through optimizing conditions such as amounts of reagents and wavelengths of light, this reaction has achieved approximately a 40% product yield in batch. Currently, this reaction is being adapted from a batch reaction in test tubes to a small-scale flow system in order to take advantage of the efficiency of flow chemistry.

 

Camille Williams

Class of 2025
Major: Mathematics / Physics
Advisor: Professor Vadim Yakovlev - Mathematics

Title: Machine-Learning Optimization of Microwave Plasma Parameters

Abstract: Microwave-assisted plasma (MAP) technology has several practical applications. In accordance with small scale experiments, it is a promising alternative to time-, energy-, and space-intensive autoclave curing of carbon fiber reinforced polymers. Advanced computer-aided design can help upscale this technology for industrial use. With this consideration, this research addresses the current lack in clarity of means to computationally characterize microwave plasma in electromagnetic models of MAP systems. The reported project outlines a progression from Lorentz-Drude model expressions for the complex permittivity of microwave plasma to a realistic conductivity-based modeling approach focused on plasma frequency and the frequency of electron collisions. An electromagnetic model of a simple MAP system containing carbon fiber and plasma is developed and thoroughly tested. A decomposed artificial neural network backed by the finite-difference time-domain electromagnetic simulator is proposed for determining plasma frequency and the collision frequency corresponding to the most energy efficient performance of the MAP system.

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