Projects

The cornerstone of the Ohio Supercomputer Center's Summer Institute is the projects. The students work together in small teams on diverse and challenging research-level projects. Teams are comprised of a project leader (staff member who conceived and designed the project) and three or four students.

View past projects

This year's project options are:

1) Networking Design and Engineering

The Ohio Academic Resources Network (OARnet) was created in 1987 to provide Ohio researchers with their first "online" access to the high performance computing resources of the newly established Ohio Supercomputer Center. Map of OARnet ommunitiesExponentially increasing demand from college and university researchers for statewide connectivity and increased bandwidth led to the acquisition of dark fiber to create a highly scalable, fiber-optic communications infrastructure, launched in November 2004. The new network was referred to as the Third Frontier Network and, later, OSCnet, both for a period when OARnet operated as the networking division of the Ohio Supercomputer Center. Today, the OARnet network consists of more than 1,850 miles of fiber-optic backbone, with more than 1,500 miles of it operating at ultrafast 100 Gbps speeds. The network blankets the state, providing connectivity to Ohio's colleges and universities, K-12 schools, public broadcasting stations, academic medical centers, government agencies, and partnering research organizations (read more at https://oar.net/about/history).

In this project we will investigate the components and technologies used to build and maintain large-scale, high performance, data networks. The project team’s goal is to design and implement a ‘Summer Institute’ (SI) network, Fiber opticswhich will interface with the OARnet backbone for connectivity to both the Internet and Internet2 (http://www.internet2.edu/). The team’s network will be a redundant, multi-vendor environment (built using both Juniper and Cisco equipment), similar in architecture to many higher education campuses or research group infrastructures that connect to OARnet. Once the SI network is in place, the team can perform end-to-end tests between machines in their environment and test remote points located throughout OARnet’s backbone, to ‘baseline’ their network’s performance. This testing will give the project team an opportunity to explore a range of different network technologies (10Mbps-10Gbps Ethernet & DWDM) and dynamic routing protocols (OSPF & BGP). The team can observe the impact of link failure on a high-availability network, measure the characteristics of a fiber-optic cable, and gain hands-on experience with many of the tools and components used to build and maintain OARnet’s 100Gbps backbone.

2) The Physics of Addicting Video Games

Physics Game
                    Click here to play the game.

Some of the most entertaining video games and smartphone apps incorporate surprisingly realistic physics models. Games like Angry Birds, for example, have spring models and projectile motion not unlike the kind of physics problems that students encounter in introductory courses. In this project you will work through a tutorial on how to program simple but very fun games that include realistic physics. After finishing these tutorials, you can look around the internet at sites like www.physicsclassroom.com, simbucket.com and phet.colorado.edu to see other examples of the kind of physics-inspired games that are out there. Students will choose to try and emulate one of these “interactives” or design something entirely new. OSU physics professors Chris Orban and Annika Peter will be on hand to help, as will graduate students from the department of physics. These tutorials are designed for absolute-beginner level programmers. But more experienced programmers will also have a fun time with this project (which uses the processingjs.org framework).

At OSU the physics and astronomy departments work closely together and as an added bonus, participants in this project will receive a tour of the astronomy department including the instrument fabrication lab.

3) Intracellular Traffic Jams

A biological cell is like a city, and it has an internal transportation system that connects different parts of the cell. Nearly all cellular functions rely on the active transport of various cargoes, including proteins and organelles, inside the cell. Microtubules are long, dynamic polymers that serve as highway tracks for intracellular transport (Figure 1). Kinesin and dynein are motor proteins that move cargoes back and forth along microtubules. Disruptions of intracellular transport in nerve cells can cause local swelling of the axon, similar to a traffic jam that we see in real life, leading to nerve cell degeneration in severe situations. These phenomena have been found in many neurodegenerative diseases, such as ALS, Alzheimer’s and Parkinson’s.

In this project, the team will use mathematical models to investigate how intracellular traffic jams arise under abnormal conditions. Students will first be exposed to stochastic processes that are used to describe cargo transport along microtubules and computational methods to simulate these processes. Students will then be asked to investigate how motor-microtubule interaction and cargo-cargo interaction affect cargo transport along microtubules using computational models. Students will finally test hypotheses for focal cargo accumulations motivated by recent experimental studies.  Students involved in this project will have the opportunity to interact with graduate students and postdocs in Professor Chuan Xue’s group who are working on related research problems and may have the opportunity to tour the cell biology lab of Professor Anthony Brown.

Sponsored in part by NSF CAREER Award 1553637.

 

Intracellular Traffic Jams

Figure 1: A motor protein transport a big organelle along a microtubule inside a cell. The figure was extracted from the video Inner Life of the Cell created by BioVisions at the Harvard University. A full narrated version of the video is available at YouTube. The clip during 3’40’’ and 3’57’’ illustrates microtubule-based intracellular transport.

4) Dark Matter in Galaxies

One of the biggest mysteries in modern astrophysics is that the overwhelming bulk of matter in the universe is "dark," made up of unknown particles and visible to us only through its gravitational influence. In this project, students will use modern data from the U.S.'s biggest radio telescope - the Karl G. Jansky Very Large Array in New Mexico (pictured) - and the Spitzer Space Telescope to try to prove the existence of dark matter.

The team will begin with observations of the motions gas in galaxies like the Milky Way, recently observed by the Very Large Array. Using these data, they will write python programs to measure how fast the galaxy spins, and then to solve for the mass needed to hold together a galaxy spinning so quickly. After "weighing" galaxies in this way, the students will compare their masses to the amount of light in stars and gas. In this way, students will use modern data to recreate one of the most fundamental astronomical results of the last century using data from some of the best telescopes in the world.

Very Large Array Radiotelescope

5) Galaxy Hunting

Galaxies, which are gravitationally bound collections of stars and gas clouds, are among the most beautiful objects in the universe.  They come in many shapes and sizes, from large spiral galaxies like our own Milky Way to tiny, diffuse puffballs of stars.  Not only are these galaxies fun to look at, but we can learn a lot about the universe by counting them and studying their properties.  In the standard theory of cosmology (=the study of the universe), we expect that there are many, many tiny galaxies.  Many more than there are spiral galaxies like the Milky Way.  A discovery of many tiny galaxies would be a confirmation of the model.  But tiny galaxies are hard to find.

In this project, you will hunt for tiny galaxies in astronomical data.  You will learn how to use the tools astronomers use to find and characterize galaxies, which includes the very versatile python programming language.  You will apply these tools to real data!  You will work with OSU Prof. Annika Peter, Dr. Anna Nierenberg, Ph.D. student Bianca Davis, and other students from OSU’s Center for Cosmology and AstroParticle Physics.

Galaxy hunting

6) The Effects of Visual Attention on Choice

Think of a recent experience you had while buying a t-shirt at the store.  If it was a tough decision, you probably remember comparing the shirt to other options.  You may even remember looking back and forth between the options while you decided which one to buy. This looking behavior is linked to attention, which shifts between the options you’re considering. Research has shown that attention can actually influence which item you will choose, and we have developed mathematical models that can show just how much each person is influenced by attention when making their decisions. Our model says that during the decision process you accumulate evidence in favor of one option or the other until hitting a fixed boundary. When looking at an item you accumulate more evidence for it than you would otherwise.  The stronger this boost in evidence, the more influenced by attention you are in your choices.  What this means is that items that hold your attention longer are more likely to be chosen.

In this project, you will track your own eye movements while you make decisions between snack foods, using an eye tracker. The eye tracker uses infrared light reflected off of the pupil and recorded by a camera to determine where you are looking on the computer screen at each moment in time. Using this data, the choices you made, and your decision times, you will fit the model to your choices to see how well we can explain your behavior and how influenced by attention you are. 

This project is designed for both experienced and inexperienced programmers. OSU Psychology & Economics professor Ian Krajbich, who developed the model, and one of his graduate students, will be present to help with running the experiment, any programming questions, fitting the model, and visualizing the results.  

Visual Attention and decision making