Recent grad Pratham Joshi works on image processing for the Hubble Space Telescope

Recent Bennington graduate Pratham Joshi did a Research Experience for Undergraduates this past summer at the Space Telescope Institute, working on processing images for the Hubble Space Telescope. Pratham concentrated his Bennington studies on Computing, Astronomy, and Mathematics. Here is what he did in his own words:

Pratham Joshi

Pratham Joshi presents his work at the Space Telescope Science Institute

For my REU at the Space Telescope Science Institute this summer, I worked on an Image Processing Pipeline for the Hubble Space Telescope’s Wide Field and Planetary Camera 2 (WFPC2). The Hubble Space Telescope is primarily known for its images of far out galaxies (especially the Hubble Deep Field) and the institute has a robust image processing pipeline for this. The problem is that a small subset of Hubble images are solar system images and this pipeline might not be the most well optimized tool for it. I thus worked with my mentor Alex Viana on an image processing pipeline specifically for moving target solar system body images.

The moving target pipeline (which is open source and can be obtained/forked from github here) consists of four major steps: Cosmic Ray rejection, Single Image drizzling, slicing and Image creation. It was written primarily in Python and uses MySQL for database. Different in-house and third-party tools were optimized and automated to connect these into our pipeline. I also did automated testing of the system and used it to generate processed images for various solar system objects. The images obtained from our pipeline will be used for the CosmoQuest Citizen Science Project (the results of which will in turn be used to further optimize our system) as well as be stored in the Hubble archive for use by scientists and researchers. There are also plans to use/extend the pipeline for use with the Hubble cameras as well as the James Webb Space Telescope.

Mathfest at Science Workshop May 10!

We will be having a mathfest of sorts at Science Workshop on May 10. Three of our senior students will be talking on their advanced work:

  • Kian Ross: Rubik’s cube and Cayley graphs
  • Hannah Simmons: Congruent numbers and elliptic curves
  • Jiaying Liu: Proving Fermat’s last theorem for polynomials

The speakers will be making every effort to make their talks accessible without any special math knowledge. So come join us, celebrate their hard work, learn a little mathematics, and partake in some math snacks!

In evolution, when is less more?

On Tuesday, December 11, at 7pm, Dr. Katie Montovan of Cornell University will come to talk to us about her work in applying dynamical systems to ecology. Hopefully you can find time in your busy end of term schedule to make it! The talk will be in Dickinson 225. Here is her title and abstract:

Hyposoter wasp laying eggsWhen is less more? Combining experiments and mathematical modeling to explain why a wasp in Finland parasitizes the Checkerspot butterfly at a surprisingly low rate. Imagine you are a wasp that parasitizes butterfly eggs, and that you have found a cluster of 200 host eggs that are ready and unparasitized.Why would you choose (or evolve genetic behavior) to parasitize less than all of the eggs? This is a puzzling enough question, but add to it that the wasp avoids previously parasitized clusters and the motivation seems downright bizarre. I develop a set of all the plausible reasons it might be better for the wasp, Hyposoter horticola, to parasitize only a third of each host egg cluster. I then carefully integrate game theory models, field and lab studies, and spatial simulation models to test each hypothesis. My goal is to rule out all but one theory in order to explain this behavior.

Mathematics and oncology

Dr. Frank Brooks, of the University College at Washington University in Saint Louis, will be coming to talk to us Wednesday, December 5, 1-2pm, about his work applying mathematics and statistics to oncology. Frank Brooks is a physicist whose work has been concentrated in biophysics and statistics. He will be talking about the clinical implications of image noise. Given noisy, uncertain images of a tumor generated by PET, clinicians must make decisions about treatment. Dr. Brooks applies statistical analysis to assess current methods and suggest improvements. Dr. Brooks has also worked on problems in actin polymerization, and has worked with undergraduates on facilitated diffusion along DNA, hidden interconnectivity in environmental systems, and eukaryotic ruffling and motility. (Dr. Brooks is a candidate for the new open position in mathematics beginning Fall 2013.)