Mentorship Program

The High Performance Computing Club sponsors a mentorship program for undergraduate students interested in high performance and/or distributed computing methods. Our mentors come from diverse fields in physical, life, and social sciences.

The application session for Winter Quarter 2018 is now Open for Mentors. Mentors are encouraged to submit applications prior to December 22th. Applications are now open for Mentees are open as well and are due Jan. 5, 2018.

Available Mentors & Projects


Mentor: Andrew Wildman – Chemistry

Past Participant: Yes

Mentee: Isaac Pang

Research Topic: Electronic Structure Theory (Quantum Chemistry)

Research Interest(s): Data Science

Programming Langauges: Python, C++, FORTRAN

Frameworks: Gaussian, MatLab


Alicia Clark – Mechanical Engineering

Past Participant: Yes

Research Topic: Mechanical/Biomedical Engineering

Research Interest(s): HPC projects related to Python/MatLab

Programming Langauges: Python

Frameworks: MatLab


Mentor:Torin Stetina – Computational Chemistry

Past Participant: Yes

Mentee: Paula Garcia

Research Topic: Quantum chemical simulations of light-matter interactions

Research Interest(s): Physics, General Data Science

Programming Langauges: Python, C

Frameworks: Gaussian, MatLab, Mathematica


Sarah Stansfield – Anthropology/Epidemiology

Past Participant: Yes

Research Topic: HIV evolution and spread with network models

Research Interest(s): Network Modeling, Infectious Diseases

Programming Langauges: R

Frameworks:


Lucy Lu Wang – Biomedical and Health Informatics

Past Participant: Yes

Research Topic: Biomedical knowledge representation

Research Interest(s): Natural Language Processing, Machine Learning, Pathway Analysis

Programming Langauges: Python, Java

Frameworks:


Adam Moyer – Computational Protein Design

Past Participant: No

Research Topic: Geometric hashing design methodology

Research Interest(s): Generative adversarial network ligand design

Project Description: I have a design/evaluation methodology for speeding up protein design by orders of magnitude which involves computational geometry and hashing. I have already demonstated the effectiveness of the method on a subset of the applicable space. I would work with my mentee to scale up application while building benchmarks to evaluate performance.

Project Requirements: Python and C++ proficientcy are important. Some understanding of proteins would also be helpful but not necessary. GPU programming could be applicable.

Programming Langauges: Python, C, C++

Frameworks: Pybind11


Brad Perfect – Mechanical Engineering

Past Participant: No

Research Topic: Computational Fluids (oceanography application)

Research Interest(s): Algorithm design, postprocessing in parallel.

Project Description: Computational fluids is a significant component of the HPC world. My simulations of ocean currents past an underwater mountain will typically output 400GB of data that must be post-processed. On a serial machine, this process typically takes several days. We will discuss data types and RAM limitations for large datasets, and then refactor pre-existing Matlab code into Python, Matlab, Fortran, or C to run on Hyak/Mox. Afterwards, we will have the opportunity to explore the mesmerizing field of flow visualization and use HPC resources to make compelling graphics and/or movies for use in publications.

Project Requirements: Proficient in Matlab or Python, understanding of ordinary differential equations, some knowledge of partial differential equations, taken a fluids class

Programming Langauges: R, Python, C

Frameworks: MatLab


Will Kearns – Biomedical and Health Informatics

Part Participant: Yes

Research Topic: Personal Health Dialog Systems

Research Interest(s): Question Answering, Machine Learning, Natural Language Processing, Knowledge Representation

Project Requirements: Biology/Clinical experience preferred, Python and/or Javascript experience a plus

Programming Langauges: Python, Java, C

Frameworks: Spark, Pytorch, Keras, Tensorflow


Kurt Sansom – Mechanical Engineering

Part Participant: Yes

Research Topic: Patient Specific Modeling of Blood Flow in Arteries

Research Interest(s): Cardiovascular physiology, image processing, image segmentation, Numerical simulation of blood flow, Numerical methods, Reduced order methods, fluid structure interaction, Spectral h/p methods, visualization, python, c/c++, data analysis

Project Description: Currently patient specific modeling requires manual pre-processing to go from medical images to blood flow models as well as post-processing. The objective would be to contribute to the creation of a robust automation framework of model development and analysis. This will be accomplished by using a combination of open source software and the mentor/mentee code to automate parts of the workflow. The outcomes will be exposure to medical imaging, segmentation methods, writing code, testing code, computational fluid mechanics, visualization, data analysis, cardiovascular anatomy and physiology, and executing simulations on hyak. The focus can be adjusted to the time and interest of the student.

Project Requirements: Prior exposure to some coding is helpful but not required.

Programming Langauges: Python, C, c++

Frameworks: VTMK, VTK, ITK, Slicer, jupyter, fluent, nektar++


Arshiya Hoseyni Chime – Mechanical Engineering

Part Participant: Yes

Mentee: Anmol L. Purohit

Research Topic: Computational Fluid Dynamics

Research Interest(s): Energy and Fluids

Project Description: Continue running CFD simulations in parallel on the cluster using the CFD file that my mentee has created.

Project Requirements: Prior exposure to some coding is helpful but not required.

Programming Langauges:

Frameworks: MATLab


Sarah Stansfield – Anthropology & Epidemiology

Part Participant: Yes

Research Topic: HIV virulence evolution

Research Interest(s): Network modeling or epidemiology topics in general (such as disease spread)

Project Description: I would prefer a mentee who wants to develop a project together

Project Requirements: Use R

Programming Langauges: R

Frameworks: