2015 Graduate Student Research Symposium
April 10, 2015 from 12:00 pm - 5:00 pm in Anderson Hall.
Event Location
Tufts University
Anderson Hall
200 College Avenue
Medford, MA 02155
Contents
Message from the GSC 3
Keynote speaker 4
Benjamin Hescott 4
Schedule 5
Abstracts 8
10-Minute Talks 8
3-Minute Talks 14
Posters 17
Our Judges 19
Our Volunteers 19
Graduate student council members 19
Research Resources at Tufts University for Graduate Students 20
Message from the GSC
Dear Presenters, Speakers, Judges, and Guests:
Welcome to the 19th Annual Graduate Student Research Symposium: Tufts Talks. This symposium highlights in-progress and published research results from students in the Arts, Sciences, Humanities, and Engineering.
This event is sponsored by the Graduate Student Council (GSC) of Arts, Sciences, and Engineering with support from the Graduate School of Arts and Sciences (GSAS) and the School of Engineering (SOE). This symposium represents one of the GSC's core missions: to promote communication between disciplines across the school. This is an opportunity for graduate students to further develop their public speaking skills, challenge the students to discuss their research to an audience of diverse academic backgrounds, and allow the Tufts community to appreciate the extent of scholarly work that takes place on our campus.
The theme of this symposium is effective communication. Graduate students will present in three different formats: 10-minute presentations, 3-minute presentations, and a poster session. The concise format challenges students to present their research to a general audience. Many of the presentations today will take place in parallel sessions. I encourage you to create a personal itinerary for the day by selecting presentations you most want to see from each concurrent session. I encourage you to stay the entire day to listen to as many presentations as you can. After the concurrent sessions, we have a wonderful keynote address from Professor Benjamin Hescott followed by the poster session during the reception, and of course the announcement of our winners.
Regards,
Michael Shah
Academic and Career Development Chair, 2014-2015
Graduate Student Council of Arts, Science and Engineering
Keynote speaker
Benjamin Hescott
Benjamin Hescott is a Professor in the Computer Science and Engineering Department who has done research in computational complexity, approximation algorithms, Kolmogorov Complexity and most recently computational biology. Professor Hescott is part of a team actively developing a model to better predict the function of proteins by studying their interactions. The work has resulted in publications in PLOS One, Bioinformatics, and the Journal of Computational Biology to highlight a few of the advances in this research.
Ben is an outstanding teacher who has worked hard to make sure all students have the chance to be successful in his class. Some of his teaching awards include: 2011 Lerman-Neubauer Prize for Outstanding Teaching and Advising, 2012 Leibner Award for teaching, and the 2012 Fischer Award for teaching. It is an everyday occurrence to see a line of students outside of his office eager to learn.
It is an honor to have Professor Hescott as our 2015 keynote speaker at this year’s graduate student research symposium. We have asked him to speak on the theme of the symposium this year, on effectively communicating research in an exciting and engaging way.
Schedule
Light Snacks at 12:00pm in Burden10-Minute Talks | 12:00pm-2:00pm
Panel A | 12:00pm-1:00pm in Anderson Room 306
Determinants of Carbon Intensity in US Electric Power Sector: A State Level Empirical Analysis
Wenfeng Qiu | Economics | Masters
Monetary Policy and Lending Distortion in China
Xiaozhou Ding | Economics | Masters
Asset pricing in a specialist market under heterogeneous information
Naijia Zhang | Economics | Masters
Measuring Electrolyte-Polymer Interactions for Energy Storage
Anthony D’Angelo | Chemical & Biological Engineer | Ph.D. Student
Panel A Judges: Shoshoni, and Martha
Panel B | 12:00pm-1:00pm in Anderson Room 309
Using brain-computer interfaces for implicit input
Dan Afergan | Computer Science Engineering | Ph.D. Candidate
Personality as a Predictor of User Search Strategies
Alvitta Ottley | Computer Science Engineer | Ph.D. Candidate
Rap Music and Stereotype Threat
Simon Howard | Psychology | Ph.D. Candidate
Something out of Nothing: A Brand-new Language
Rabia Ergin | Psychology | Ph.D. Student
Panel B Judges: Edward and Noah
Panel C | 1:00pm-2:00pm in Anderson Room 309
Geometry, Frustration, and Ice Cream: Arrested Relaxation of Emulsions
Christopher Burke | Physics and Astronomy | Ph.D. Student
Pressure-Time Profile Analysis to Select Surfaces that Effectively Redistribute Occipital Pressure in Pediatric Patients
Samantha Higer | Mechanical Engineering | Masters Student
Differential Thermal Analysis Based on Radiative Heat Transfer and Induction Heating
Francesca Minervini | Mechanical Engineer | Masters Candidate
Compress Vortex Analysis
Andrew Hubble | Mechanical Engineering | Masters Student
Panel C Judges: Martha, Noah, and Edward
3- Minute Talks | 2:00-2:35pm
Panel D | 2:00pm-3:00pm in Nelson Auditorium
Adjusting Ambient Air Pollution Exposure Estimates for Inhalation Rate
Laura Corlin | Civil and Environmental Engineer | Masters Student
Measuring Electrolyte-Polymer Interactions for Energy Storage
Anthony D’Angelo | Chemical and Biological Engineer | Ph.D. Student
Impact of an invasive bee (Anthidium manicatum) on foraging behavior in bumble bees (Bombus impatiens)
Kelsey Graham | Biology | Ph.D. Candidate
Protecting the Genome
Jennifer Nguyen | Biology | Ph.D. Candidate
Reactivity of Vibrationally Hot Methane on Ir(110)
Emily Nicotera | Chemistry | Ph.D. Student
Improvements to a Networked Toolkit for Teaching CS
Matthew Ahrens | Computer Science Engineering | Ph.D. Student
Panel D Judges: Shoshoni, Noah, Jordan, Edward, and Martha
Short Break | Judges Meeting 2:30-3:00pm
3:00-3:45pm: Plenary Session with Keynote Speaker in Nelson Auditorium (on the first floor)
3:45-5:00pm: Poster Session, Reception, and Awards in Burden Lounge (on the first floor across from Nelson Auditorium)
Visual Feature Similarity during Word Processing: a Masked ERP study
Helen Pu | Psychology | Ph.D. Student
Racial Differences in Women’s Leadership Experiences: Perceived Fit and Stereotype Threat for Intersectional Identities
Samantha Snyder | Psychology | Ph.D. Student
Reactivity of Vibrationally Hot Methane on Ir(110)
Emily Nicotera| Chemistry| Ph.D. Student
Towards More Natural Human-Robot Dialogue
Tom Williams | Computer Science Engineering | Ph.D. Candidate
Judges: Shoni, Noah, Jordan, Edward, and Martha
Abstracts
10-Minute Talks
Determinants of Carbon Intensity in US Electric Power Sector: A State Level Empirical AnalysisWenfeng Qiu | Economics | Masters
The U.S. Environmental Protection Agency recently announced the Clean Power Plan, a plan to reduce carbon dioxide emissions from existing electric power plants. The proposal will require states to reduce their carbon intensity (carbon emissions per megawatt hour of generation) below fixed caps. My research analyzes the drivers of carbon intensity in the electric power sector using a state-level data set from 1990-2012. I do this taking two approaches. First, I undertake a statistical analysis estimating linear regression models of state-level carbon intensity in the power sector focusing as a function of fuel prices, state-level policies, and other determinants of carbon intensity. I then further explore the determinants of carbon intensity by applying a Generalized Fisher Index decomposition of carbon intensity. The decomposition results show that recent reduction in carbon intensity mainly came from switching from coal to natural gas. The basic results, along with the decomposition results, show some evidence of the importance of relative fossil fuel prices. While a carbon tax would be an effective driver of reductions in carbon intensity, I argue that a coal tax would be even more effective in the short run given my regression and decomposition results.
Monetary Policy and Lending Distortion in ChinaXiaozhou Ding | Economics | Masters
The author investigates the effects of monetary policy in China in a distortionary economy consisting of heterogeneous firms: State-Owned Enterprises (SOEs) and Private-Owned Enterprises (POEs). They mainly differ in the ability of getting loans with real interest rate higher or lower than the benchmark (non-distortion interest rate). In the first simple case, the author builds a simple Real Business Cycle model to examine the effect of a monetary shock in an economy where interest rate subsidy is identical to all firms with or without an interest rate subsidy. In the second section, the author adds sticky price and the heterogeneity to the RBC model and the distortion is measured by that only SOEs could be able to get the interest rate below the benchmark rate. The simulation result shows that unless the subsidy is feasible to all firms, there exist uncertainty within an economy with distortion. In the final thought, the author tries to apply a dual-economy model with the above characteristics and test the impact of monetary policy.
Asset pricing in a specialist market under heterogeneous informationNaijia Zhang | Economics | Masters
Its has long been discussed the adjustment of classic CAPM model in real business world since the it was first developed in the early 1960s byWilliam Sharpe(1964), Jack Treynor(1962),John Lintner(1965) andJan Mossin(1966). This paper analyzes how heterogeneous information problem affects asset pricing in stock market. It first introduce a theoretical model based on unbalanced information among investors and how this affect equilibrium asset price. In the empirical part of this paper, it conducted an event study based on Target security breach. A three factor Fama French model is incorporated to analyzed the significance and impact of the security breach. Daily data and quarterly data are used to study the impulse impact; industrial fix effect and cross sectional difference in difference methods are used in evaluating spill over impact of the breach.
Measuring Electrolyte-Polymer Interactions for Energy StorageAnthony D’Angelo | Chemical & Biological Engineer | Ph.D. Student
Solid-state electrolytes formed by immobilizing an ionic liquid within a polymer-based gel framework (ionogels) offer many benefits for electrical energy storage devices such as supercapacitors and rechargeable batteries. Freestanding gel electrolytes are capable of replacing conventional liquid electrolytes, advantageously removing safety concerns of leakage and allowing for lighter, more flexible supercapacitors. Retaining the ionic conductivity of the pure ionic liquid when it is confined in a gel framework still remains a challenge. Various interactions between the ionic liquid and the polymer scaffold affect ion diffusion, hence altering the ionogel’s ionic conductivity. Possible polymer-ionic liquid interaction phenomena include: (i) ion dissociation, which creates more free ionic carriers and increases ionic conductivity, and (ii) ion obstruction, which occurs when polymer chains act as physical barriers for ion motion, leading to decreased ionic conductivity. In order to better understand these interactions, the activation energy of ionic conductivity, cation and anion diffusivities, and the physical cross-link density have been investigated in ionogels incorporating three methacrylate-based polymers with rationally-varied chemical functionality. Results show that the chemical identity of the polymer does indeed affect ion dissociation and obstruction, which may provide guidance for the future design of high performance ionogel electrolytes.
Using brain-computer interfaces for implicit input
Dan Afergan | Computer Science Engineering | Ph.D. Student
Passive brain-computer interfaces, in which implicit input is derived from a user's changing brain activity without conscious effort from the user, may be one of the most promising applications of brain-computer interfaces because they can improve user performance without additional effort on the user's part. I seek to use physiological signals that correlate to particular brain states in order to adapt an interface while the user behaves normally. My research aims to develop strategies to adapt the interface to the user and the user's cognitive state using functional near-infrared spectroscopy (fNIRS), a non-invasive, lightweight brain-sensing technique. While passive brain-computer interfaces are currently being developed and researchers have shown their utility, there has been little effort to develop a framework or hierarchy for adaptation strategies.
Personality as a Predictor of User Search StrategiesAlvitta Ottley | Computer Science Engineer | Ph.D. Student
Individual differences matter. While this has been the theme for many recent works in the Visualization and HCI communities, the mystery of how to develop personalized visualizations remains. This is largely because very little is known about how users actually use visualizations to solve problems and even less is known about how individual differences affect these problem-solving strategies. In this work, I provide evidence that strategies are indeed influenced by individual differences. I demonstrate how the personality trait locus of control impacts strategies on hierarchical visualizations, and I introduce design recommendations for personalized visualizations.
Rap Music and Stereotype ThreatSimon Howard | Psychology | Ph.D. Student
Past research suggests that awareness of negative stereotypes about Black people can psychologically threaten African Americans by impairing academic performance, a phenomenon known as “stereotype threat” (Steele & Aronson, 1995). This initial experiment aims to expand the stereotype threat literature by investigating the construct of stereotype threat in relation to exposure to music lyrics, specifically violent/misogynistic rap music. Certain rap lyrics (e.g., violent/misogynistic) can reflect negative cultural stereotypes of Black people, which in turn can activate the accessibility of other negative cultural stereotypes (e.g., unintelligent). Because of this stereotype activation we hypothesize that violent and misogynistic rap music will induce stereotype threat resulting in a decrease in Black participants cognitive performance. Preliminary results suggest that violent/misogynistic rap lyrics induce stereotype threat for Black men.
Something out of Nothing: A Brand-new LanguageRabia Ergin | Psychology | Ph.D. Student
Central Taurus Sign Language (CTSL) is a naturally emerging sign language with little/no influence of any other signed or spoken language in an isolated region in the mountains of Southern central Turkey. When there is an incidence of recessive deafness in such a closed community, the deaf members become obliged to develop their own language to be able to communicate their messages. These naturally developing languages help us understand a very important question in Cognitive Science: How does a language emerge and evolve without a language model? This question cannot be answered through spoken languages because the earliest written records of spoken languages date back to approximately 2000 years ago (e.g., Rosetta Stone, 196 BC). However, even in those days, human languages had pretty much the same complexity that they have today. Emerging village sign languages, on the other hand, are young by definition. Their linguistic and cultural histories can easily be traced. Therefore, we believe it is our privileged opportunity to study the linguistic properties of CTSL, and make modest generalizations on the capacity of human language faculty to develop language in the absence of a model.