Kiran Sasikumar

About

• Experienced in collaborative and independent research on heat transfer, thermodynamics, phase change, and reaction kinetics, with relevant applications in the fields of health, electronics, space and energy.

• Qualified mechanical engineer and materials scientist, with expertise in material interaction at nanoscale interfaces.

• 12+ years experience in programming with focus on computational techniques to simulate/characterize materials behavior.

• 9+ years experience in sifting through large text datasets (100 MB – 1 GB in size), extracting relevant information and presentation in human-readable form.

Employment

• Avant Garde Materials Simulation Deutschland GmbH
  2018 - Present
• Argonne National Laboratory Postdoctoral Researcher
  2015 - 2018
• Advanced Cooling Technologies, Inc. R&D Engineer - Intern
  2014 - 2015

Education

• Rensselaer Polytechnic Institute Ph.D
  2009 - 2014
• National Institute of Technology B.Tech.
  2005 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (26)

• Graphene overcoats for ultra-high storage density magnetic media
  Nature Communications 2021 DOI: 10.1038/s41467-021-22687-y
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• Slippery and Wear-Resistant Surfaces Enabled by Interface Engineered Graphene
  Nano Letters 2020 DOI: 10.1021/acs.nanolett.9b03650
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• Teaching an Old Dog New Tricks: Machine Learning an Improved TIP3P Potential Model for Liquid–Vapor Phase Phenomena
  The Journal of Physical Chemistry C 2019 DOI: 10.1021/acs.jpcc.9b06348
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• Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures
  Chemistry of Materials 2019 DOI: 10.1021/acs.chemmater.8b03969
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• Formation and Nature of Carbon-Containing Tribofilms
  ACS Applied Materials & Interfaces 2019 DOI: 10.1021/acsami.8b22496
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• Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data
  The Journal of Physical Chemistry C 2019 DOI: 10.1021/acs.jpcc.8b09917
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• Machine learning a bond order potential model to study thermal transport in WSe2 nanostructures
  Nanoscale 2019 DOI: 10.1039/c9nr02873k
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• Comparing optimization strategies for force field parameterization
  2018
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• Active site localization of methane oxidation on Pt nanocrystals
  Nature Communications 2018 DOI: 10.1038/s41467-018-05464-2
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• Quantitative Observation of Threshold Defect Behavior in Memristive Devices with Operando X-ray Microscopy
  ACS Nano 2018 DOI: 10.1021/acsnano.8b02028
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