​My research interests lie in applying Machine Learning methods to combustion problems.

• Machine Learning To Predict Standard Enthalpy of Formation of Hydrocarbons
  K. K. Yalamanchi, V. C. O. van Oudenhoven, F. Tutino, M. Monge-Palacios, A. Alshehri, X. G...
  J. Phys. Chem. A, 123, 38, 83058313, (2019)
• Data Science Approach to Estimate Enthalpy of Formation of Cyclic Hydrocarbons
  K. K. Yalamanchi, M. Monge-Palacios, V. C. O. van Oudenhoven, X. Gao, and S. M. Sarathy
  J. Phys. Chem. A, 124, 31, 62706276, (2020)
• Screening gas‐phase chemical kinetic models: Collision limit compliance and ultrafast timescales
  K. K. Yalamanchi, EA. Tingas, H. G. Im, S. M. Sarathy
  Int J Chem Kinet., 52:599610, (2020)
• Effects of fuel composition variability on high temperature combustion properties: A statistical analysis
  M. K. Khandavilli, K. K.Yalamanchi, R. Huser, S. M. Sarathy
  Applications in Energy and Combustion Science 14, 100012, (2020)
• A functional-group-based approach to modeling real-fuel combustion chemistry – I: Prediction of stoichiometric para...
  X. Zhang, K. K.Yalamanchi, S. M. Sarathy
  Combustion and Flame, (2020)

• ​​M. Tech, Thermal Engineering, Indian Institute of Technology Madras, Chennai, India, 2017
  
• B. Tech, Mechanical Engineering, Indian Institute of Technology Madras, Chennai, India, 2017
  

• ​​Clean Combustion Research Center (CCRC)
  
• Division of Physical Sciences and Engineering (PSE)