As a senior software engineer with the IN-MaC project at Purdue University, I work on these projects:
  • Technical cost modeling: Lead developer and architect for a web application for calculating costs of manufacturing lines. The lines can be graphically configured and connected to sensors in physical equipment for an Industry 4.0 approach to cost analysis. The software architecture also exposes REST and Python APIs for use in Jupyter notebooks, ML, and optimization of manufacturing systems. Industrial partnerships use this software in automotive, bio-tech, and eletronics industries. Co-PI on grants using this software. Developed proposals and reports for funding agencies. Supervised multiple graduate students.
  • Industry 4.0 software integration: Lead developer of a system to connect various PDM and MES systems to each other and to manufacturing equpiment to support construction of Digital Twins
  • Sport data analytics: Lead developer of tools for predictive capactity planning for International Olympic Committee (IOC) efforts to provide software tools for Olympic hosts

Other projects I have worked on include:

  • Technical cost modeling: Lead developer for a GUI desktop application (wxPython) for calculating costs of manufacturing lines.
  • nanoHUB@home: Co-leader of project to extend nanoHUB simulation capabilities with volunteer computing using BOINC. Supported 209 simulation tools, volunteer base of almost 800 volunteer hosts providing 450 GFLOPs. []
  • Speculative exploration: Sole developer of a "bot" to systematically explore the input parameter space of all nanoHUB tools supported by nanoHUB@home, generating input files in both random and targeted explorations.
  • nanoHUB_remote: Sole developer of a Python library and Jupyter notebook to run nanoHUB simulation tools via REST API. Python API hides the details of JSON manipulation and OAuth authentication. [][]
  • HPC support: Built, deployed, managed HPC simulation tools like LAMMPS, Quantum Espresso, ABINIT on Purdue clusters. Automated batch job submission from nanoHUB simulation tools. Handled support tickets related to computational physics, both science and infrastructure issues.


  • chifig: Publication quality plotting tool, written in Ruby, using LaTeX. []
  • DLA: Diffusion Limited Aggregation cluster growth simulator, written in C++ with Boost, using MPI and OpenMP for embarassingly parallel ensemble assembly. []


  • Lorena Alzate-Vargas and Michael E Fortunato and Benjamin Haley and Chunyu Li and Coray M Colina and Alejandro Strachan. Uncertainties in the predictions of thermo-physical properties of thermoplastic polymers via molecular dynamics. Modelling and Simulation in Materials Science and Engineering, 26, 6, 065007, 2018.
  • Martin Hunt and Benjamin P. Haley and Michael McLennan and Alejandro Strachan. PUQ: a code for non-intrusive uncertainty propagation in computer simulations. Computer Physics Communications, 194, 2015.
  • Benjamin P. Haley and Gerhard Klimeck and Mathieu Luisier and Dragica Vasileska and Abhijeet Paul and Swaroop Shivarajapura and Diane L. Beaudoin. Computational nanoelectronics research and education at Journal of Computational Electronics, 8, 124, 2009.
  • Benjamin P. Haley and Niels Grønbech-Jensen. Vacancy-assisted Arsenic Diffusion and Time-dependent Clustering Effects in Silicon. Phys. Rev. B, 71, 195203, 2005.


  • Ph.D. Engineering - Applied Science University of California, Davis 2005
  • M.S. Engineering - Applied Science University of California, Davis 2001
  • B.S. Physics (Honors) Purdue University 1998