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Computational materials scientist with a strong background in research and industrial software engineering and a keen interest in leveraging the predictive capability of molecular scale materials modeling at an industrial scale with the goal of reducing manufacturing cost and improving materials performance. 

Work experience

Manager, Modeling Scientist, Drug Product Development

Jun 2019Present
Bristol-Myers Squibb (Previously Celgene Corporation), Summit, NJ, USA
  • Leveraged state-of-the-art crystal engineering techniques such as ADDICT and CSD python to address challenges in crystalline drug substance development
  • Leveraged state-of-the-art thermodynamics modeling techniques such as PC-SAFT to optimize properties of amorphous drug substance developed through spray dried dispersion (SDD)
  • Developed new methods to analyze particle morphology distribution (size and shape) characterized using static image analysis and related them to bulk powder properties such as powder flow
  • Developed analysis pipelines for computational fluid dynamics models of drug development processes such as fluidized bed drying and mixing tanks
  • Implemented data ingestion strategies for collecting data from materials profiling experiments and simulations into data lake to develop a digital twin of drug product development
  • Developed mechanistic models and machine learning (ML) models for optimizing oral solid formulation development

Post Doctoral Research Associate

Aug 2018May 2019
University of Tennessee at Knoxville
  • Preparing molecular dynamics (MD) simulations for the exascale (1e18 FLOPS) computing machines of the future. This is achieved by developing tools that mitigate the issue of MD simulations producing data at a higher rate than it can be written to disk for analysis as a result of the dichotomy in the rate at which FLOPS and I/O OPS capability of high-performance computers is growing. These tools allow in-situ analysis of the MD data at a higher resolution than was possible using traditional post-hoc analysis and saving only necessary data that will be required for further analysis or for continuing simulations
  • Responsible for coordinating an NSF funded multi-university collaborative project (

Graduate Assistant

Aug 2013Jun 2018
Boise State University
  • Developed CUDA capable coarse grained molecular simulations of epoxy resin cure in collaboration with Boeing Research and Technology. Using this model, 2 million particle simulations in cubic volumes of side length 100 nm  can reach 95 % curing in under 10 hours of compute time. This level of computational performance is key to being able to do ensemble averaging and represents the state-of-the-art of polymerization models
  • Improved the performance of the a concrete micro structure model called "Anm" by a factor of 5 using thread parallelization. This enabled the creation of highly densely packed virtual cement models which led to the quantification of the structure of cement particles around irregular shaped aggregates for the first time

Senior Systems Specialist

May 2010Jul 2013
General Electric Company, Bangalore, India
  • Developed a new thin client-based assay development framework for a confocal high content analysis instrument (HCA) used in life sciences which vastly improved the accessibility of the legacy platform
  • Conducted Scrum methodology training for over 35 team members to aid the team transition from a waterfall model of software development to the Agile model

Senior Software Engineer

Oct 2008May 2010
Sasken Communication Technologies, Bangalore, India
  • Achieved 80%+ automation of the test cases for the Bluetooth stack on the Nokia S40 series mobile phones. This drastically reduced the manual test effort and increased productivity by 50%
  • Identified and designed effective test cases for Bluetooth Low Energy (BTLE) specifications

Senior Software Engineer

Aug 2004Oct 2008
Microview Technologies Pte Ltd, Singapore
  • Developed hardware interfacing components for industrial cameras, servo motors and high speed I/O cards for a graphical programming framework which enabled the rapid development and deployment of machine vision applications for inspecting fasteners and image sensors
  • Implemented an extremely reliable machine vision-based measurement tool for the fastener industry using the six sigma Gage Repeatability and Reproducibility  (GRR) method
  • Optimized the garbage collection mechanism to keep the cycle time to be reliably under 60 ms for the fastener inspection system


PhD in Materials Science and Engineering

Boise State University, Boise, ID, United States of America


MS in Materials Science and Engineering

Boise State University, Boise, ID, United States of America

BE in Computer Science

Periyar University, Salem, TN, India


  1. Gamble et al. "Morphological distribution mapping: Utilisation of modelling to integrate particle size and shape distributions ". International Journal of Pharmaceutics (2023)
  2. Wadams et al. "Particle Property Characterization and Data Curation for Effective Powder Property Modeling in the Pharmaceutical Industry". AAPS PharmSciTech (2022)
  3. Thomas et al. "Data-smart machine learning methods for predicting composition-dependent Young’s modulus of pharmaceutical compacts". International Journal of Pharmaceutics (2021)
  4. Thomas et al. "General-Purpose Coarse-Grained Toughened Thermoset Model for 44DDS/DGEBA/PES". Polymers (2020)
  5. Thomas et al. "A novel metric to evaluate in situ workflows". International Conference on Computational Science (2020)
  6. Lu., Y et al. "Three-dimensional mortar models using real-shaped sand particles and uniform thickness interfacial transition zones: Artifacts seen in 2D slices". Construction and Building Materials (2020)
  7. Jankowski, E. et al. "Perspective on coarse-graining, cognitive load, and materials simulation". Computational Materials Science (2020)
  8. Thomas, S., Wyatt, M., Do, T. M. A. , Pottier, L.,  da Silva, R. F., Weinstein, H., Cuendet, M. A., Estrada, T., Deelman, E., Taufer, M. "Characterizing In Situ and In Transit Analytics of Molecular Dynamics Simulations for Next-generation Supercomputers". eScience (2019)
  9. Thomas, S., Alberts, M., Henry, M., M., Estridge, C., and Jankowski, E. "Routine million-particle simulations of epoxy curing with dissipative particle dynamics." The Journal of Theoretical and Computational Chemistry (2018)
  10. Yano, K.H., Thomas, S., Swenson, M.J., Lu, Y., Wharry, J.P. "TEM in situ Cube-Corner Indentation Analysis Using ViBe Motion Detection Algorithm." Journal of Nuclear Materials (2018)
  11. Thomas, S., Lu, Y., and Garboczi, E. (2015). “Improved Model for Three-Dimensional Virtual Concrete: Anm Model.” Journal of Computing in Civil Engineering, American Society of Civil Engineers, 4015027
  12. Lu, Y., Thomas, S., and Garboczi, E. J. (2015). “Nanotechnology in Construction: Proceedings of NICOM5.” K. Sobolev and P. S. Shah, eds., Springer International Publishing, Cham, 301–308
  13. Lu, Y., and Thomas, S. (2015). “Anm Model Approach for Lunar Soil Simulant Properties Study.” Earth and Space 2014, American Society of Civil Engineers, 76–83

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