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 Fall Quarter 2017 has closed. For those interested, please be on the lookout for our Winter Quarter Application in mid-November.

Available Mentors & Projects


Sarah Alamdari – Chemical Engineering

Research Topic: Molecular dynamic simulations on enzymatic reactions

Research Interest(s): Data science

Project Description: Molecular Dynamics (MD) simulations are a computational method used to study system dynamics on the atomic scale by iteratively solving Newton’s equations of motion. Many important processes, like chemical reactions, can be characterized by different metastable states (i.e. reactants, products, and transition states). We are interested in understanding the underlying minimum energy reaction pathways that connect these states. These metastable states converge very slowly on the time scales accessible by computers, however enhanced sampling techniques can be applied to overcome these problems. You will apply enhanced sampling techniques to MD simulations to explore the reaction coordinate of a sample reaction system.

Project Requirements: Mentee must have taken a Chemistry course


Aakash Sur – Bioinformatics/Genomics

Research Topic: Genome assembly and structure

Research Interest(s): Web development for scientific data visualization, signal processing, statistical analysis

Project Description: One of several 1) Run and analyze a GPU based genome assembler in the cloud. 2) Integrate web visualization tools to explore and understand high dimensional genomics data 3) Explore/Implement/Develop peak detection algorithms for genomics data (signal processing)


Arushi Prakash – Chemical Engineering

Research Topic: Understanding the assembly of proteins on surfaces

Research Interest(s): Computational Chemistry, Molecular Simulations, Unsupervised Machine Learning (Clustering Methods)

Project Description: In order to understand the structure of proteins, the mentee would have to cluster the structure from data(already generated). The mentee would be required to use existing clustering tools and write their own clustering scripts in Python.

Project Requirements: Python proficiency (preferred), comfortable with bash


Andrew Wildman – Chemistry

Research Topic: Electronic Structure Theory (Quantum Chemistry)

Research Interest(s): Data Science

Programming Langauges: Python, C++, FORTRAN

Frameworks: Gaussian, MatLab


Joe Kasper – Chemistry

Research Topic: Spectroscopy and Relativistic Quantum Chemistry

Research Interest(s): Mathematics, Machine Learning, Physics

Programming Langauges: Python, C

Frameworks: Gaussian, MatLab, Mathematica


Sharon Solis – Applied Math

Research Interest(s): PDEs, Dynamical Systems, Predator-Prey models, Machine learning

Programming Langauges: R, Python, SQL, C++

Frameworks: MatLab, Mathematica


John Schaefer – Chemistry and Applied Mathematics

Research Topic: Excited State Chemistry / Numerical LA

Research Interest(s): Games Theory, Epidemiological Modeling

Programming Langauges: Python, Java, C

Frameworks: Gaussian, MatLab, Mathematica


Alicia Clark – Mechanical Engineering

Research Topic: Mechanical/Biomedical Engineering

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

Programming Langauges: Python

Frameworks: MatLab


Will Kearns – Biomedical and Health Informatics

Research Topic: Conversational Agents for Consumer Health Question Answering

Research Interest(s): Bayesian Networks, Disease Modeling, Genetics

Programming Langauges: Python, C, Javascript

Frameworks: Spark, Pytorch, Tensorflow, Keras


Torin Stetina – Computational Chemistry

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

Research Topic: HIV evolution and spread with network models

Research Interest(s): Network Modeling, Infectious Diseases

Programming Langauges: R

Frameworks:


Arshiya Hoseyni Chime – Mechanical Engineering

Research Topic: Combustion of alternative and pure fuels

Research Interest(s): CFD, Combustion, Renewable Energy, HPC

Project Description: The mentee will be running CFD simulation of a combustion chamber to compare against experimental data.

Frameworks: STAR-CCM+


Christopher Fu – Chemical Engineering

Research Topic: Developing methods for studying complex reactions through molecular dynamics simulations

Research Interest(s): Molecular Dynamics Simulations, Complex Reacting Systems, Data Science

Programming Langauges: Python

Frameworks: Gaussian, MatLab, Mathematica, GROMACS, AMBER, PLUMED, CP2K