Email: chris (AT) $DOMAIN.com
Email: $DOMAIN (AT) cmu.edu
Github

Python, Computational Chemistry, Quantum, Machine Learning, UNIX, Parallel Computing, NetSec, Digital Logic, Fractals, Economics

Current Projects

Research

  • Distributed optimization of INDO parameters using machine learning
  • Predicting optoelectronic properties of various polymeric systems using Deep Learning
  • Coupling effects in polymeric systems of thiophene and phenyl
  • Developing new representations for interfacing machine learning and chemistry
  • Predicting atomic forces using deep learning

Programming

  • Chemtools
    • A collection of various utilities to make computational chemistry easier in the form of a Django application
    Includes:
    • Structure generator
    • Log file parser
    • Cluster job monitor
    • Molecular property predictor
    Demo Site

  • TorqueCluster
    • A virtual Torque Batch System cluster using Vagrant
  • Servers
    • A collection of various virtual web service backends using Vagrant based on this DigitalOcean article

Past Projects

Research

  • Optimizing optoelectronic properties of Benzobisazoles (substituents, ring types, chain lengths, push/pull systems)
  • Computational decomposition studies of Benzobisthiaphospholes
  • Using Machine Learning (Support Vector Machines) to predict optoelectronic properties of Benzobisazoles

Programming

Technologies

  • Python, C, C++, Javascript, Bash, SQL, C CUDA, Go, HTML/CSS, TI-BASIC, Matlab/Octave, Maple, Java
  • Scipy, NumPy, Matplotlib, SciKit-Learn, Django, Paramiko, PyCrypto, PIL, Cairo, Selenium, pyTest, DisPy, PyBrain, jQuery, Bootstrap, SDL
  • Gaussian, Logisim, LabVIEW, Vagrant, Virtualbox, PostgreSQL, GIMP, Inkscape