Research Projects by Subject

Note: Each research project will involve background reading for the interns provided by their mentors. Each research project will involve a final presentation by the interns.

Interns are expected to work collaboratively on the same project and/or data set. This may preclude rising seniors from submitting papers based on such projects to the Intel Science Talent Search competition.

Astronomy & Astrophysics

Code Research Project Descriptions
AST-01 Title: Using Deep Learning Techniques to Classify Astrophysical, Atmospheric, and Instrumental Features in Keck DEIMOS Spectra
Primary mentor: Prof. Raja GuhaThakurta
Location: UCSC Main Campus
Number of interns: 1

Project description: The combination of the Keck II 10-m telescope and DEIMOS instrument is arguably the world's most powerful combination for spectroscopy of faint astronomical objects. Our research group at UCSC has access to a large set of high quality Keck/DEIMOS spectra of a variety of interesting sources ranging from different types of stars in our Milky Way galaxy to galaxies and quasars in the distant Universe. These raw Keck/DEIMOS spectra have been put through a standard data processing pipeline in an effort to remove the Earth's atmospheric signatures and instrumental signatures. The products of the pipeline include 2D and 1D spectra. The pipeline typically does an imperfect job and a handful of very experienced experts have been able to visually identify a range of residual atmospheric/instrumental artifacts in the pipeline processed data (e.g., cosmic rays, scattered light, bad sky subtraction, bad wavelength solution, telluric absorption, bad extraction windows, etc.) and subtle spectral features (e.g., emission and absorption lines) that allow for the distinction between different types of astrophysical sources. This project plans to employ machine learning/deep learning techniques to classify these astrophysical, atmospheric, and instrumental features in Keck/DEIMOS spectra thereby leveraging the huge investment of time and effort that has already gone into the visual inspection by experts.

Tasks: The SIP intern will assemble the training datasets required for supervised learning, and use tools like TensorFlow and AutoML to explore different network architectures. They will evaluate the performance and tune several hyperparameters to build the best-performing multi-class classifier. Depending on the initial results, there could be follow-on tasks like collecting more training data. Finally, we may integrate the learned model into the existing data processing pipeline to provide automated filtering of different types of astrophysical sources.

Required skills for interns prior to acceptance: Computer programming
Skills intern(s) will acquire/hone: Computer programming
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: ON ON ON ON REM REM ON ON ON ON


Code Research Project Descriptions
AST-02 Title: Spatial Substructure in the M87 Globular Cluster System
Primary mentor: Yuting Feng
Faculty advisor: Prof. Raja GuhaThakurta
Other mentors: Eric Peng
Location: UCSC Main Campus
Number of interns: 3

Project description: One of the main predictions of living in a Universe dominated by cold dark matter is that galaxies should form through the continual merging and accretion of other smaller galaxies. Galaxies that form in this way should not be smooth, but rather be full of stellar streams, which are the shredded remnants of the smaller galaxies that merged in a long time ago. Globular clusters (GCs; small clusters of old stars that orbit about a galaxy) come in with these merged components, and are a tracer of galactic structure. A new data set containing thousands of GCs around the nearby massive galaxy, M87, presents a new opportunity to test whether galactic halos are smooth or as "lumpy" as expected from galaxy formation simulations.

Tasks: The SIP interns will analyze the spatial distribution of GCs around M87 and compare their real distribution to a theoretical "smooth" distribution. They will use tools to measure the large-scale GC distribution, and use that information to simulate a mock data set containing no substructure ("lumpiness"). They will also use visual inspection to mask regions with no data, or regions of known structure, applying these masks to the mock data set. The interns will use existing data (images, catalogs), but write their own computer programs to make the mock data set and do the statistical comparison. The SIP interns will also identify clusters of GCs in the data to look for new, heretofore undetected low surface brightness galaxies.

Required skills for interns prior to acceptance: None
Skills intern(s) will acquire/hone: Computer programming; statistical data analysis
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: REM REM ON ON REM REM ON ON ON ON

Only out-of-area applicants will be considered for this virtually-mentored project.

Biomolecular Engineering

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Chemistry & Biochemistry

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Computational Media

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Computer Science/Computer Engineering

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Economics

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Ecology & Evolutionary Biology

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Electrical Engineering

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Environmental Studies

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Earth & Planetary Sciences

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Molecular, Cell & Developmental Biology

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Microbiology & Environmental Toxicology

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Ocean Sciences

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Other

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Physics

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.
 

Psychology

As of yet, no mentors have submitted projects for this field of research. Mentors are still in the process of submitting projects so please keep posted for more projects to be submitted.