Projects + Proposals

Initiation is the most regulated step of translation and is mediated by a host of protein initiation factors. We focus on an initiation factor called eukaryotic translation initiation factor 3, or eIF3. eIF3 is the largest and most complex of the initiation factors and has recently emerged as an important player in the regulation of translation. And yet, its precise molecular roles are not well understood.

Our research is focused around three principal avenues of inquiry. First, we are leveraging next-generation sequencing technologies to explore the role that eIF3 plays in the translation of mRNA transcripts across the genome in living cells. Second, we are employing biochemical tools to interrogate the molecular workings of eIF3 and its interaction with the ribosome. Finally, because eIF3 is in fact not one protein but a larger complex of several proteins, we are designing tools to dissect the specific contribution of each of these constituent proteins to translation initiation. Students working in my lab gain experience with a variety of approaches, including molecular biology techniques, protein expression and purification, in vitro biochemical assays, next-generation sequencing approaches, and the computational analysis of large datasets.

Prerequisites:

• BIOL 107 & 108
• Internal Motivation
• Accountability
• Excellent attention to detail
• Willingness to try, fail, and try again

How students should express interest: Students should directly address why they are interested in my research and how it is connected to their academic interests at Vassar and/or their plans after graduation. Students should also describe any research experience they have had, any relevant courses they have taken, as well as any obstacles that have previously prevented them from acquiring research experience.

Students should not contact me directly. I will review all applications and reach out to potential candidates.

Project length: 10-week URSI: May 22–July 28

The gut microbiome is a complex and dynamic community of microorganisms that impacts systems throughout the human body. Gut microbes produce tryptophan metabolites that regulate inflammation, maintain the integrity of the gut lining, and are known to be important in inflammatory and autoimmune diseases. A change in the gut microbiome, termed dysbiosis, is often associated with disease. The purpose of this study is to investigate the production of, and response to, microbial tryptophan metabolites in people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and Long COVID. These complex post-infection chronic diseases have similar symptoms and may have a similar underlying biological basis. Several studies have described dysbiosis and leaky gut in people with Long COVID and ME/CFS, suggesting possible alteration in microbial regulation of body systems. In addition, the symptoms and affected systems in Long COVID and ME/CFS are consistent with disrupted microbial regulation. We hypothesize that the microbiomes of people with Long COVID and ME/CFS produce smaller amounts of regulatory metabolites, contributing to pathological inflammation and disrupted gut homeostasis. In this project, we will be using reporter cell lines, qPCR, metabolomics, and other assays to measure microbial metabolite function from stool samples from patients and controls.

Prerequisites: Students must have Biol 107 and 108. It is strongly preferred for students to also have one of Biol 205, Biol 272, Biol 238, Biol 244, or Biol 248. Work in the lab requires the handling of human stool samples, so vaccination against hepatitis B before beginning work is required.

How students should express interest: Outstanding candidates will be contacted for an interview. It is not necessary to reach out to me by email to express your interest.

Project length: 8-week URSI: May 22–July 14

In this project, we will sample for local insect and other arthropod fauna across the diverse ecosystems around Vassar College. Using a broad array of collection methods such as sweep netting, pitfall, and malaise trapping, we will measure species richness and insect abundance across different environments local to Vassar College. Insects will be collected, identified, and preserved. Using our collected specimens, we will compare insect species richness and evenness between environments such as developed landscaped areas on campus, forest preserve, and agricultural fields. Additionally, students will collaboratively develop a museum-quality teaching collection for generations of future Vassar students and faculty to learn from.

Prerequisites:

• Willingness to perform regular outdoor fieldwork
• Handling live/dead insect specimens

How students should express interest: Interested students feel free to reach out to Professor Lampasona at tlampasona@vassar.edu.

Project length: 10-week URSI: May 22–July 28

In dye-sensitized solar cells, dye molecules are bound to nanocrystalline semiconductors such as TiO2 using one or more anchoring functional groups. The most commonly used anchoring groups are carboxylic acids and their derivatives, due to their stability and easy synthesis. Phosphonic acid groups have also been used as a more stable linking group. A more novel alternative is boric acid and its derivatives, which have thus far been a limited focus of study. In a previous project, we examined how the stability of boronic acids anchored on the clean TiO2 rutile (110) surface can be optimized by introducing various functional groups. In this project, we plan to model boronic acid adsorption on the hydroxylated TiO2 rutile surface, which is a more physically meaningful model of the surface in experimental conditions. This study is entirely computational, using density functional theory calculations run on high-performance computing clusters.

Prerequisites: Chem 125 (required prerequisite)

How students should express interest: I will contact students after applications have been submitted.

Project length: 10-week URSI: May 22–July 28

The magnetic behavior of transition metal porphyrin complexes make them attractive for potential applications in the field of molecular spintronics. In molecular spintronics, it is crucial to have a good understanding of the energy level alignments between the molecules and electrodes, and consequently, an accurate description of the molecular energy levels and their character. Density functional theory (DFT) using the optimally-tuned range-separated hybrid (OT-RSH) functional has been shown to yield accurate energy levels in many organic molecules. In this study we use DFT with the OT-RSH functional to analyze the energy levels in cobalt (II) octaethylporphyrin (Co-OEP). Additionally, we examine the effect of a metal substrate on the energy levels of Co-OEP in a hybrid architecture.

Prerequisites: Chem 125 (required prerequisite)

How students should express interest: I will contact students after applications have been submitted.

Project length: 10-week URSI: May 22–July 28

The microtubule associated protein tau has a variety of important cellular functions, most notably stabilizing and organizing microtubules in axons. Abnormal tau behavior is also prevalent in several neurodegenerative disorders such as Pick’s disease, frontotemporal dementia, parkinsonism linked to chromosome 17 and Alzheimer’s disease, which are all characterized by abnormal aggregation of the protein. Tau is an intrinsically disordered protein and its interactions with microtubules are dynamic, so it has been especially difficult to study the structure of tau-bound to microtubules. Thus, the overall goal of this project is to build a better understanding of tau’s behavior when it is bound to microtubules, including changes in structure and function that precede pathological aggregation. To achieve this end, this project will investigate the properties of tau when it is bound to solid supports in physiologically-relevant conformations, applying an atomic force microscopy (AFM) based assay that interrogates the protein at the nanoscale. Both AFM force spectroscopy and imaging will be used in order to conduct physical-mechanical characterization of normal tau and pro-aggregant mutants, and to examine heterogeneity in assemblies of the protein. The behavior of surface-bound tau will be compared to its behavior in solution, with an eye toward a better understanding of its varied physical behaviors.

Prerequisites: Required courses: CHEM-125, and/or BIOL-107/108.

Other related (recommended) courses: BIOL/CHEM-272, CHEM-244/245, PHYS-113/114 or 107/108

How students should express interest: Please write a BRIEF one-paragraph description that includes: why you're interested in this project, how it fits into your overall academic track at Vassar, and how it fits into your long-term (post-Vassar) plans. I will reach out to some students for in-person interviews.

Project length: 10-week URSI: May 22–July 28

Daphnepapytone A is a sesquiterpenoid natural product first isolated in 2021 with a uniquely caged carbon skeleton, containing a 4 membered ring within a 6 membered ring within a 7 membered ring. It shows α-glycosidase inhibitory activity, which has potential implications for management of type 2 diabetes mellitus. The goal of this project is to synthesize Daphnepapytone A in the laboratory, using two different photochemical reactions as key synthetic steps: rearrangement of a bicyclic dienone, and intramolecular [2+2] cycloaddition. In total, the synthesis should require between 6 and 8 synthetic steps and other members of the daphnepapytone family should be accessible through a divergent synthesis strategy.

Prerequisites: CHEM245 required, CHEM342 and CHEM372/373 preferred. Strong laboratory skills and an ability to digest scientific literature are necessary. Experience with acquiring and interpreting NMR data is preferred.

How students should express interest: Students should contact me directly via email (ehoward@vassar.edu) and set up an in-person appointment to discuss their interest in the project.

Project length: 10-week URSI: May 22–July 28

A common practice in medicinal chemistry is to synthesize non-natural analogues of existing natural products in order to improve their biological activity. Based on recent literature, the natural product Brazilin has recently been demonstrated to induce apoptosis in U87 glioblastoma cells, which is a particularly aggressive form of brain cancer. The goal of this project is both to shorten/improve the existing synthetic methods towards Brazilin, and to use this improved method to synthesize non-natural analogues for testing against U87 cells. The project is primarily based in organic synthesis and methodology development, but if enough analogues are synthesized, biological assessment may be a possibility.

Prerequisites: CHEM245 required, CHEM272, CHEM342, CHEM372/373 preferred. Strong laboratory skills and an ability to digest scientific literature are necessary. Experience with acquiring and interpreting NMR data is preferred.

How students should express interest: Students should not contact me directly, I will contact potential candidates for an in-person interview after all applications have been reviewed.

Project length: 10-week URSI: May 22–July 28

Humans and microbes have a complex relationship. The advent of antibiotics allowed humans to fight pathogenic bacterial infections that threatened our livelihood. However, microbiome dysbiosis, the imbalance of symbiotic microbial populations in the body, can be caused by lifesaving antibiotics. We will use biochemical and biophysical techniques to characterize proteins from various pathogenic or symbiotic microbes, for example, ones that aid in the spread of antibiotic-resistant genes. These studies help to provide further understanding of essential microbial processes at the molecular level. Students working in the lab will gain experience with gel electrophoresis, protein expression and purification, in vitro enzyme assays, and protein crystallization.

Prerequisites:

• Chem 125 (required);
• Bio 107 (or equivalent intro bio course) and Bio 272 (preferred)
• OR related previous lab work (describe in application)

How students should express interest: In their application, students should describe briefly 1) why they are interested in this project, and 2) what unique or interesting aspect of their background/perspective they can bring to science.

Students do not need to contact me directly. After reviewing the applications, I will contact selected candidates about setting up an interview.

Project length: 8-week URSI: May 22–July 14

The human gut microbiota is required for degradation of otherwise undigestible dietary polysaccharides, often known as fiber. The Bacteroidetes are prominent contributors to polysaccharide degradation in the gut and the model organism for understanding this process is the bacteria Bacteroides thetaiotaomicron (B. theta). Each type of fiber is targeted by a distinct protein complex encoded by a polysaccharide utilization locus (PUL). Each PUL is regulated by a transcriptional regulator that allows the protein complex to be expressed only the presence of the target polysaccharide. This project focuses on characterizing two types of transcriptional regulators. Using fundamental biochemical techniques, students will express and purify 1-2 transcriptional regulators and then use techniques such as x-ray protein crystallography and curricular dichroism to characterize the structure of these proteins. This understanding of the structure of various transcriptional regulators will allow us to better understand how to manipulate expression of polysaccharide targeting proteins. This is an ideal project for a student interested in biochemistry and protein structure.

Prerequisites: Chem125 and Bio108 or strong high school experience preferred

How students should express interest: Students should indicate their specific interest in this project. What are your career goals and how does this work fit into those goals? An acceptable answer is that you do not have specific career goals at this time but you should consider how this experience will help you explore potential careers. If students have not completed Chem125 and Bio108 they should address this, either by describing their previous experience or explaining when they plan to complete these courses.

Students will be selected for an interview based on initial applications. I will contact you to set up an appointment and provide topics of discussion for the interview.

Project length: 10-week URSI: May 22–July 28

This URSI project continues our lab's long-term project of exploring the phenomenon of learned categorical perception and the claim that learning new categories changes the way we perceive stimulus differences and similarities. The work will include evaluating current research, visualizing and analyzing data, developing new stimulus materials and experiments, collecting data via online experiments, applying meta-analytic techniques to relevant research literature, and preparing material for conference presentation and/or publication.

Prerequisites: Interest in the project, knowledge of how to use R and enthusiasm for learning a lot more about how to use it, and a willingness to learn and program in JavaScript are required. Intermediate level coursework in cognitive science, coding experience, knowledge of research methods and statistics, prior experience with jsPsych, and familiarity with R for data analysis and graphing are very desirable.

How students should express interest: Students do not need to contact me with regard to their application but are welcome to email questions. Applications should address what the student finds interesting about this particular project and what they hope to gain from the experience. I will contact students for interviews after applications are submitted.

Project length: 10-week URSI: May 22–July 28

Eye tracking is a popular method for studying human cognition, but it typically requires expensive laboratory hardware. This makes the method inaccessible for many researchers and makes it difficult to collect large datasets that are needed for robust scientific inference. The goal of this URSI project is to develop a machine learning model that can predict where someone is looking on their screen using only webcam images. With this kind of model, researchers could conduct eye tracking studies over the internet without any specialized hardware.

This project began last summer. We have collected a large video dataset of people looking at different points on their screens and explored some basic machine learning models for predicting gaze locations. This summer, we will work on (1) finding appropriate models for this kind of data, (2) training and fine tuning these models at scale using Vassar's high-performance computing system, and (3) creating a researcher-friendly way of using the final model in behavioral experiments.

We will primarily explore deep neural network models, implemented in tensorflow/keras using python.

Prerequisites: Comfort working with one or more programming languages is necessary for this project. Python experience is ideal, but not required. No prior experience with machine learning is needed, but is helpful.

How students should express interest: You do not need to contact me before submitting your application. In your application, it is very helpful to share an example of previous programming work that you have done (e.g., through a link to a GitHub repository, or a description of a project and what your contributions were). I will contact students for interviews after applications are submitted.

Project length: 10-week URSI: May 22–July 28

Collectively, researchers who study behavior generate an enormous amount of data each year. Most of this data is only ever seen and used by the researchers who generated it. While publishing and sharing raw data is becoming more common, there are challenges to working someone else's data. Data file formats vary from lab to lab, there are no standard naming conventions, and important information about the data, like what each column in a spreadsheet means, is often missing. Working with a raw data set is often a time consuming process that requires investment in the particulars of the data set.

Imagine the world in which these problems were solved. If behavioral data were recorded using a basic standard, then you could open a data set from another lab and have enough information to easily understand how to work with the data. This is great, but the real impact of this work (and this is where boring talk about "data standards" start to get exciting) is that with the right kind of standards in place, data becomes machine-readable. This means that we could begin to develop software that can automatically parse the raw data of a wide-range of behavioral experiments, spurring technological innovation. We could potentially augment and automate many of the steps that are needed to work with raw data and facilitate scientific discovery at larger scales.

This URSI project will work on the development and implementation of a data standard for behavioral data. We will be collaborating as part of the Psych-DS (https://psych-ds.github.io/) team and working towards implementing the Psych-DS standard in datasets generated by jsPsych (https://www.jspsych.org/). The project will involve tool development and creating instructional content for researchers to explain the Psych-DS specification.

Prerequisites: This project is a good fit for students who have some experience with research methods and some experience with programming. We will be doing programming work in JavaScript. Strong programming skills are not required.

How students should express interest: You do not need to contact me before submitting your application. In your application, it is very helpful to share an example of previous programming work that you have done (e.g., through a link to a GitHub repository, or a description of a project and what your contributions were). I will contact students for interviews after applications are submitted.

Project length: 10-week URSI: May 22–July 28

Last summer we completed the build of a human-scale humanoid robot torso to be used as a basic research platform. The project is currently being used in projects that include human-machine interaction studies, development of VR systems for robot control, and exploration of neural network control architectures for solving the problem of recovering perceptual depth from binocular disparity. The goals for this coming summer include (1) further refinement of both hardware and software for execution of perception-action control loops for basic actions (e.g., reaching and grasping, gesturing, etc.) and (2) incorporation of some basic speech perception and generation capabilities, integrated into simple control architectures.

Prerequisites: The following are all highly desirable. These are not all absolute requirements, but combinations of as many of them as possible will be highly advantageous on the project and thus strengthen an application. They are listed in their rough order of importance.

1. Some background in Cognitive Science, especially in areas related to perception and action systems
2. A solid coding background in C or a C-based programming language
3. Computing hardware and electronics experience
4. Familiarity with 3D printing software and hardware
5. Good mechanical assembly skills

How students should express interest: Applicants should contact me directly by email (livingst@vassar.edu) to arrange an appointment to speak about the project.

Project length: 10-week URSI: May 22–July 28

Over the past 12 months we have completed construction of a humanoid robotic torso that is currently being used in a variety of research applications and will continue to be used for the foreseeable future. However, this first humanoid robot construction project has revealed a number of areas for fundamental improvement in the initial design and construction details. In particular, it is clear that the robot can and should be slightly smaller, constructed of more robust materials, and requires different kinds of motor actuation for some subsystems in order to be as robust and flexible as possible. The latter includes the desirability of adding mobility to the platform. This project will be focused on the design and construction of this upgraded version of a humanoid robotic platform, including basic electronics and programming as well as mechanical systems.

Prerequisites: The following are all highly desirable. These are not all absolute requirements, but combinations of as many of them as possible will be highly advantageous on the project and thus strengthen an application. They are listed in their rough order of importance.

1. Some background in Cognitive Science, especially in areas related to perception and action systems
2. Familiarity with CAD software for component design
3. Strong mechanical skills
4. Familiarity with 3D printing software and hardware
5. Computing hardware and electronics experience
6. A solid coding background in C or a C-based programming language

How students should express interest: Applicants should contact me directly by email (livingst@vassar.edu) to arrange an appointment to speak about the project.

Project length: 10-week URSI: May 22–July 28

This project will explore the application of computational methods to model thematic variation in a large corpus of literature, across dimensions of time (when books were written) and space (where the author was from). In particular, we will use unsupervised topic modeling and modern data science visualization to produce an interactive thematic map. This will allow a rough empirical estimate of the importance of different literary themes (e.g., domestic life, travel, love, war) to books produced during particular bounds of time and geography.

Prerequisites: Required: CMPU 101 or equivalent experience; an interest in natural language processing, digital humanities, or data science.

Preferred: Additional coursework in computer science (especially CMPU 203, 240, and 366), data science, or literature, and experience using Python toolkits for natural language processing or visualization.

How students should express interest: In the application, state any relevant coursework, experiences, or skills. Students don’t need to contact me before submitting an application but are welcome to email questions.

Project length: 10-week URSI: May 22–July 28

Vassar’s Earth Science department recently got a new scanning electron microscope (SEM), which is an instrument that allows us to image the surface of tiny objects and is widely used in Biology, Chemistry, Earth Science, and Physics. These images present a way to see our world in astounding detail, helping us to feel awe at our natural world- an emotion that promotes resilience and connectedness in difficult times. However, access to scientific instruments is often allowed only for restricted groups and using them can be intimidating to students in learning contexts. For students who did not have access to lab experiences in high school, this can be a systemic barrier to inclusion in college STEM fields. In this project, students will work to create public- or Vassar- facing outreach programs that aim to broaden the access to the SEM for the broader Poughkeepsie and/or Vassar community. The students in this project will be encouraged to explore the contexts and outcomes that are most meaningful to them. One option is to create outreach programming and initiatives for Vassar’s Geology Museum aimed at local school communities or environmental organizations. Another is to continue the work of a previous Grand Challenges project, where past students envisioned a lab methods course for Vassar students who didn’t have access to practicing these skills in high school. Both of these ideas are aimed at creating welcoming scientific experiences for our community members. Throughout, we will consider the power of combining science and art and explore ways that SEM imaging can be used in other fields such as Art History. Students in this project will also gain skills in microscopy and geochemistry techniques.

This Summer Catalyst project is part of the collaboration between URSI and HHMI Grand Challenges.

Prerequisites: There are no course prerequisites to participate in this project, but experience in an introductory level STEM course at Vassar would provide helpful context. Prospective students should have an interest in science communication.

How students should express interest: Students will be selected for an interview based on their URSI applications.

Project length: 10-week URSI: May 22–July 28

Earth's history of climatic change is recorded in a variety of geological and biological proxies for parameters such as temperature and precipitation. In this URSI project, we build on the work of the fall 2022 ESCI/ENST 335: Paleoclimatology seminar by using diatoms, pollen grains, and plant macrofossils in a sediment core collected from Zipfeldberg bog to uncover the climatic history of Dutchess County and to trace the evolution of this ecologically very interesting site. The bog hosts a number of unique species, such as the carnivorous pitcher plant, bog cranberries, and sphagnum moss. The site likely started out as a lake, however, and the timing of when it transitioned to a bog is unknown. Covered by the Laurentide ice sheet until as recently as 15,000 years ago, the area has experienced several climatic oscillations, including wetter intervals and drought, that are recorded in changes in vegetation both surrounding and within the bog. Understanding the nature of these climatic changes, what caused them, and how long they lasted is very important for our comprehension of what the climate system is capable of doing in the absence of human activities and provides the baseline against which anthropogenic climate change can be measured. In addition, some earlier intervals in Earth history may provide insights into how the vegetation in the bog will respond to future warming.

Prerequisites: This project is best suited to students who have taken ESCI/ENST 335: Paleoclimatology, but students who have not taken this course will also be considered. Students will preferably have some familiarity and comfort with using compound and dissecting microscopes as most of the work will involve identifying and counting pollen grains, diatoms, and plant macrofossils under the microscope.

How students should express interest: Interested applicants should send an email to Kirsten Menking (kimenking@vassar.edu) expressing what about the project sounds interesting to them and why, outlining their previous experience with or enthusiasm about learning how to work with microscopes, and providing their current class schedule and suggested times for an interview.

Project length: 8-week URSI: May 22–July 14

Characterization of the magma plumbing beneath explosive volcanoes is essential for monitoring activity and forecasting eruptions. This project will investigate the nature of the magma system beneath the Momotombo-Monte Galán volcanic system in northwestern Nicaragua. We will use geochemical and thermodynamic techniques to coax the memory out of the crystals erupted during two large eruptions - the caldera-forming eruption of Monte Galán (age unknown) and the largest historical eruption of Momotombo in 1605. The eruption deposits of these volcanoes overlap both temporally and spatially and our work will explore if their plumbing does as well. Tasks will include: sample preparation, computer modeling, and analysis using the new electron microscope housed in Ely Hall.

Prerequisites: Completion of ESCI 151

Completion of ESCI 201 or ESCI 351 (preferred)

How students should express interest: Please email me if you have any questions or would like to discuss the project before submitting an application.

Project length: 10-week URSI: May 22–July 28

If you hold a thin rectangular ribbon of paper by its ends, what shape will the ribbon have? If you move the ends of the ribbon slightly, will the shape also change slightly, or will it jump to a very different shape? Why is the ribbon's surface smooth in some shapes and creased in other shapes? In this project, we will use a mix of mathematics and computer programming to describe the behavior of thin flexible ribbons. We will focus on questions about the ribbon's geometry (e.g., how do we describe its shape?), the ribbon's stability (e.g., when will the ribbon jump or snap?), and its mechanical properties (e.g., when will creases form?). The answers to these questions have applications in many area, including automated manufacturing, where a robot might need to manipulate a ribbon-like object, in medicine, where a surgical robot might need to handle flexible materials like suture, and in modeling of nano-structures such as graphene ribbons.

Prerequisites: Students participating in this project should have completed MATH 220 - Multivariable Calculus and MATH 221 - Linear Algebra. Completing MATH 228 - Methods of Applied Mathematics and having previous experience with computer programming will be helpful, but are not required.

How students should express interest: If you have any questions about this project or would like to learn more, please feel free to reach out by email and we can schedule a time to chat.

If you plan to apply for this project, please let me know by email so that we can schedule a time to meet and discuss your interests, background, and more details about the project.

Project length: 10-week URSI: May 22–July 28

What does a random knot look like? Because the collection of all knots is infinite, difficulties arise when attempting to answer this question. Moreover, the way we choose to represent each knot may affect the answer. In this project, students will study a specific class of knots called rational knots. For the class of rational knots, we will study several knot invariants and attempt to study the typical behavior of those invariants over the entire set.

Prerequisites: Math 221 required. Some exposure to proof writing is preferred.

How students should express interest: Students should apply through the URSI form. I will contact some of the applicants for interviews.

Project length: 10-week URSI: May 22–July 28

This 10 week project is divided into two parts. In the first half, we will learn the fundamental methods for constructing and analyzing mathematical models of phenomena from fields such as ecology, epidemiology, biology, etc.. These skills will be both pencil & paper in nature as well as work done with computers via Matlab. Throughout this time, and in the latter half, we will develop a model of a phenomena derived from the participants’ interest. A technical report will detail findings based on our work and computer simulation results.

Prerequisites: Calculus skills are required. Some exposure to differential equations is a plus. No previous experience with computer programming required. A deep-seated interest or study in the life sciences is strongly encouraged.

How students should express interest: When applying to URSI projects please email me directly with a SHORT statement of interest that details what you're excited about with respect to the project. Use the subject line "URSI 2023 Statement of Interest".

Project length: 10-week URSI: May 22–July 28

Cosmologist and particle physicists join efforts to uncover the origin and behavior of dark matter, known to be an abundant yet elusive portion of the universe's matter budget. In parallel to the quickly advancing developments in Earth- and orbit-based detectors, we in the community continuously develop hypothetical explanations for dark matter interactions with ordinary matter (beyond gravity) and test them against data.

In this project, the URSI student(s) will have the opportunity to learn 1) how dark matter is modeled as a particle that, although mostly inert, would display scattering with ordinary matter, 2) the evolution of the abundance of dark matter as the Universe ages, and 3) numerically calculate such evolution via specialized software.

Student(s) will acquire a degree of familiarity with:

• A broad-stroke picture of unsolved problems in particle physics and cosmology.
• The requirements imposed by data for a successful modeling of dark matter.
• Algebraic and numerical tools to assist such modeling.
• The creation of publication-level plots showing how the proposed matter-dark matter interactions are controlled by distinct parameters.

The project offers a glimpse into the frontier of the area and an entry-level set of skills to contribute, within the undergraduate experience, to larger collaborations.

Prerequisites: Classical Mechanics (specially Lagrangian formulation), Quantum Mechanics (mostly the harmonic oscillator), Modern Physics (focus on Special Relativity), and Mathematical Methods (Linear Algebra and matrix manipulation).

Basic coding experience and astronomy skills are not prerequisites but are welcomed.

How students should express interest: I would like to choose students after having had a short conversation with them. This way we can chat about the project and their background/interest (call it an informal “interview”.)

After reading the project's description and prerequisites, students can express interest by contacting me through email during the semester or telling me in person (101.2 Sanders Physics Building). Afterward we can set a Friday to talk about it (after 3:00 p.m. if possible) at the Physics Department.

Project length: 10-week URSI: May 22–July 28

Student(s) will work with me to create a workshop, or series of workshops, focused around implicit bias and how it can negatively influence fields within science, technology, engineering, and mathematics, as well as ways to recognize and promote positive interactions. I will bring my prior experience and knowledge from having gone through and co-founded multiple workshops in this realm of things. This idea was born out of a recent town hall meeting with students in the Physics and Astronomy department as many voiced a desire for such an event. The student(s) and I will work out the best format suited for the Physics and Astronomy department, how to best incorporate faculty, students, and staff while also addressing power dynamics, all leading up to creating the proper programming and assessments to gauge its effectiveness.

This Summer Catalyst project is part of the collaboration between URSI and HHMI Grand Challenges.

Prerequisites: Students must have good communication skills (and/or be willing to improve them). It would also be helpful for the student(s) to have experience within a STEM field or field related to sociology. Experience in various social interactions and how to navigate them when issues arise is not necessary but would be great to have.

How students should express interest: I would like to interview students (either in-person or via zoom) to ensure they possess the skills necessary to progress on the project and talk about expectations. If students are interested in this project, they may email me and I will promptly respond.

Project length: 10-week URSI: May 22–July 28

Ultrafast lasers produce pulses of light that are less than 1 picosecond (A millionth of a millionth of a second) in duration. These remarkable light sources allow for investigations of extremely short-lived phenomena in solid materials. Of particular interest to my research group are the conduction of heat and the propagation of ultrasound in novel nanostructures. We have several goals this summer. First, we have an ongoing project to study very thin semiconducting solids that we sometimes grow thin enough to call them “2-D materials.” Second, in specially designed nanostructures we can generate and detect surface acoustic waves at their highest possible frequencies-near 50 GHz. Techniques will include laser experiments, the growth of thin metal films, and computational modeling of vibrational and electromagnetic waves.

Prerequisites:

• Required: PHYS 114
• Recommended: PHYS 200, 202/203, 210 and MATH 220, 221, 228

How students should express interest: Other than this application, students do not need to contact me in order to express their interest.

Project length: 10-week URSI: May 22–July 28

Multi-Channel Measurement of Largest Lyapunov Exponents using Dynamic Optical Diffraction

Dynamic optical diffraction (DOD) has been employed to measure the largest Lyapunov exponent (LLE) associated with the locomotory pattern of a nematode. In this work, we examine the LLE from multiple time-series by sampling various locations (channels) in a diffraction pattern, which is recorded by a high speed CMOS camera. The optical intensity fluctuations in the DOD are a superposition of the light from every point on the worm and correspond directly to the locomotion. We will confirm the consistency of LLEs from various channels. In addition, the increased accuracy of the averaged LLEs in one diffraction pattern allows for a more accurate comparison of individual microorganisms. We will confirm that these results are consistent with previously published work that used a single photodiode (PD) to measure the LLE of freely swimming C. elegans. These microscopic worms are a widely studied, fully developed model microorganism with a digestive system and ability to learn, whose neural network of 302 neurons is fully mapped (http://www.wormbook.org/). Further studies examining the effects on the LLE by various characteristics of the worms, most notably age, must be performed to understand variations in dynamical invariants.

Prerequisites: Introductory physics and calculus.

Good fine motor skills as required for optical alignments and patience.

How students should express interest: It is fine to reach out to me via email and/or stop by during office hours.

Project length: 10-week URSI: May 22–July 28

Topological insulators are a type of material that permits unidirectional quantum-scale currents to exist. These currents, known as edge states, are unaffected by material defects, making topological insulators an interesting research topic with potential quantum computing applications. Recent research has proven protected edge states, akin to the unidirectional current of electronic topological insulators, not just with electrons but also with photons, sound waves, and mechanical waves. We will use the Haldane model for the mechanical topological insulator in this project. This model allows the observation and measurement of unidirectional edge modes. We will employ two methods: 1) the 3D printing of models and 2) the building of models utilizing piezoelectric plates. It is anticipated that this project will yield sufficient data for a scientific publication.

Prerequisites: The student must have the following knowledge:

• Quantum mechanics (desirable but not critical)
• Linear algebra
• Mechanics

How students should express interest: I will contact by email those students that I believe could be a good fit for the project.

Project length: 10-week URSI: May 22–July 28

Chaos in the colloquial English sense is very broadly defined and is synonymous to “very hectic and disorganized.” In the mathematical sense, Chaos is defined by David Feldman to be situations that are deterministic, aperiodic, bounded, and have a sensitive dependence on initial conditions (D. Feldman, Chaos and Fractals: An Elementary Introduction (2012), p. 85). Mathematical techniques to determine if data is chaotic include lag plots, largest Lyapunov exponents, and correlation dimension. Other powerful techniques to quantify Chaos are Recurrence Plots (RP) and Recurrence Quantification Analysis (RQA), which are the techniques this project will focus on. A properly embedded data set with low noise generates diagonal lines in the RP. Those lines give information about the determinism, periodicity, and sensitive dependence on initial conditions. Quantifying those diagonal lines through RQA include calculating values such as divergence and entropy. We will investigate the relationship between divergence and largest Lyapunov exponents in the locomotion of C. elegans and how it relates to the density of data and noise present in the data set.

Prerequisites: Basic Programming Experience - Matlab experience a plus

How students should express interest: Email me to set up an interview.

Project length: 10-week URSI: May 22–July 28

Rarely do environmental stimuli occur in the same place or form across time. An essential mechanism that allows for the transfer of learned experience to other stimuli and contexts is known as stimulus generalization. While the ability to generalize stimuli is adaptive, overgeneralization of stimuli is maladaptive, and has been linked with clinical disorders such as anxiety and post-traumatic stress disorder. In particular, there is some evidence to indicate that those with high degrees of anxiety tend to overgeneralize stimuli. This indicates a potential mechanistic link between anxiety-like behavior and stimulus generalization. Surprisingly, no preclinical work has directly tested this link. This URSI project tests the relationship between individual differences in anxiety-like behavior and fear memory generalization using a mouse model. The URSI project requires interest in behavior, psychology, cognition, and/or neuroscience. Courses in Introduction to Neuroscience & Behavior (Neuro 105), Research Methods in Physiological Psychology (Psyc 249), and Principles of Physiological Psychology (Psyc 241) are desirable, but not required. Basic animal handling skills, chemistry lab skills, and data analytic skills are also desirable. The project will involve working with a team that will include fellow URSI students and faculty. See the Memory Neuroscience Lab website for more information about our research.

How students should express interest: Prof Bergstrom will reach out to students for interviews.

Project length: 10-week URSI: May 22–July 28

One of the most pervasive approaches to discussing diversity is known as "colorblindness". The colorblindness ideology hypothesizes that deemphasizing category boundaries (i.e., disregarding categories such as race, culture and/or ethnicity) can be effective in reducing intergroup bias (Dovidio et al., 2009); however, research suggests that individuals spontaneously employ the physical appearance of others as a heuristic for categorizing them by race (Cosmides et al., 2003; Hamilton et al., 1994). Given the automatic and often unconscious process of racial categorization (Ito & Urland, 2003), achieving “pure” colorblindness in terms of not perceiving markers of racial identity seems unlikely. Yet, this is an empirical question. Research has yet to explore whether individuals who endorse a colorblindness approach to diversity or are primed to adopt this ideology do actually perceptually process race differently. The current research proposal investigates whether people with motivations (or who are primed) to “not see race” may process information about race fundamentally differently than people who takes a more “race-conscious” approach. Additionally, this proposal investigates whether the link between “not seeing race” and opposition to race-based social policies (like affirmative action) is mediated by differential perception of the number of racial minorities present in contexts implicated by these policies.

This Summer Catalyst project is part of the collaboration between URSI and HHMI Grand Challenges.

Prerequisites: Must have completed Introduction to Psychological Science (PSYC 105) and have a strong interest in research related to diversity and racial identity.

How students should express interest: Professor Small will reach out to every student who completes an application via the portal and set up an interview. Students will be provided with interview questions they should be expected to answer during the initial email exchange.

Project length: 10-week URSI: May 22–July 28

Schools throughout the United States rely heavily on property taxes for funding and differences in tax revenues have resulted in disparities in resources between schools in low versus high-income neighborhoods. Moreover, previous research has shown a strong correlation between school resources and student performance (Graddy & Stevens 2005) in that students with less resources perform relatively lower than those students with access to more resources. In addressing the question of how this practice persists, it is proposed that the American value of meritocracy has contributed to its maintenance. Meritocracy is the idea that those who work hard will invariably succeed. While on the surface this ethic appears to provide hope for all, evening the playing field, it has been found to lead both high and low-status groups to justify inequality (McCoy & Major 2006). Specifically, based on a meritocratic ideology, success and social status are tied to the effort and abilities of the individual which often leads to justification of status differences (Augustinos 1998; Kluegel & Smith 1986). This study evaluates whether priming meritocracy leads individuals to justify differences in academic outcomes, attributing lower versus higher academic success to the work habits of students, despite knowing differences in resource accessibility.

This Summer Catalyst project is part of the collaboration between URSI and HHMI Grand Challenges.

Prerequisites: Must have completed Introduction to Psychological Science (PSYC 105) and have a strong interest in research related to diversity and racial inequality.

How students should express interest: Students should contact me at psmall@vassar.edu to express interest in URSI. In their email, they should provide a 2–3 sentence summary of why they are interested in the proposed project. I will set up an interview with every student who expresses interest in working with me and will provide them with interview questions they should be expected to answer during the initial email exchange.

Project length: 10week URSI: May 22–July 28

Background: Resilience is characterized by effective coping, emotional agility, and the capacity to adapt and recover from stress (Bonanno, 2004; Masten, 2007; Skodol, 2010, Tugade, 2011). It is further defined as the ability to thrive despite personal and social stressors (Steinhardt & Dolbier, 2008). My program of research on resilience examines the components of resilience, including the acquisition of personal skills to achieve positive outcomes for mental health.

The Project: URSI Scholar(s) will work on a collaborative study that examines age-related differences in markers of resilience. Research shows cognitive attention can be diminished with age. Interestingly, similar cognitive impairments can be seen in young adults experiencing various levels of stress (including emotional distress, lack of sleep, or fatigue).

The current project will involve lab-based studies to investigate whether mindfulness techniques can help protect against cognitive impairments – thereby facilitating resilience in the midst of stress. Examining young adults, this URSI team will help to validate new technology that measures neural health that has previously been studied in older adults. The overall aim is to provide science-based strategies to improve mental health and well-being across the lifespan. There will be opportunities for work with off-campus collaborators virtually or via local visits.

Prerequisites:

• Research skills (data collection, data analysis, coding of narrative responses)
• Organization
• Interview skills
• Graphic design skills (e.g., Canva, web layout, data visualization)
• Writing skills

How students should express interest: Applicants to my project should submit their resume/CV and unofficial transcript. Selected candidates will be contacted via email for interviews.

Project length: 8-week URSI: May 22–July 14

Data from various animal models shows that prenatal maternal exercise programs offspring metabolic function and also reduces her stress, thus reducing prenatal stress-related neurodevelopmental changes in her offspring. Much less is known, however, about possible effects of postnatal maternal exercise on offspring development. Our lab has found that adult offspring of dams with postpartum access to a running wheel were more resilient to acute stress than offspring of “sedentary” dams. This stress resiliency was associated with increased BDNF in ventral hippocampus and structural changes in dendritic spines of pyramidal cell neurons of the same region. This URSI project is a continuation of this work and will test the causal relationship between maternal running and offspring stress resiliency. Furthermore, we will assess whether wheel running alters maternal behavior, one possible mechanism of such programming. The project will involve extensive animal handling, behavioral testing, biochemical assays, and data processing.

Prerequisites: Previous rodent handling and research experience as well as successful completion of Research Methods in Physiological Psychology preferred.

How students should express interest: Students should submit an application using the online portal. Professor will reach out to candidates for interviews.

Project length: 10-week URSI: May 22–July 28