Katika Harikrishna

About

I am a Ph.D. graduate from NIT Warangal. Currently, I am a Post-Doctoral Fellow at IIT Madras, working in the Laboratory for Mechanics of Microstructures. My primary research interests lie in powder metallurgy, metal forming, machine learning, hydrogen diffusion, and corrosion science. Throughout my academic journey, I have gained extensive hands-on experience with advanced manufacturing processes and tools. My Ph.D. research focused on microstructural evolution using EBSD, dynamic recrystallization, and the simulation of hot deformation behavior in aluminum alloys using Deform 3D. In my postdoctoral work, I am currently involved in two projects: one on hydrogen diffusion in dual-phase steels, and another on crystal plasticity simulation combined with a machine learning framework to predict local stress–strain fields.

Employment

• Indian Institute of Technology Madras Post Doctoral Researcher
  2025 - Present
• Shri Vishnu Engineering College for Women Assistant Professor
  2024 - 2025

Education

• National Institute of Technology Warangal Ph.D
  2019 - 2024
• National Institute of Technology Warangal M.tech
  2017 - 2019
• Padmasri Dr BV Raju Institute of Technology B.Tech
  2012 - 2016

Projects & Funding

Projects & funding information is unavailable.

Publications (24)

• The Relationship Between Deformation Parameters and Corrosion Parameters of the Al-5.6Zn-2Mg Powder Metallurgy Alloy During Hot Upsetting
  2026 DOI: 10.1007/978-981-95-2547-8_10
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• A METAL MATRIX COMPOSITE AND A METHOD OF MANUFACTURING THEREOF
  2026
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• Advanced computer vision algorithm for extraction of microstructural features from BSE images of powder metallurgical microstructures
  The International Journal of Advanced Manufacturing Technology 2025 DOI: 10.1007/s00170-025-16493-9
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• A novel sintering approach for interface diffusion layer control in Al–Al₄CrFeMnTi₀.₂₅ high-entropy alloy composites: Microstructure, strength, and corrosion resistance
  Journal of Alloys and Compounds 2025 DOI: 10.1016/j.jallcom.2025.183254
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• Automated microstructural segmentation and grain size measurement of Al plus SiC nanocomposites using advanced image processing techniques on backscattered electron images
  Materials Characterization 2025 DOI: 10.1016/J.MATCHAR.2025.114845
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• Evaluation of Machine Learning Models for Predicting the Hot Deformation Flow Stress of Sintered Al-Zn-Mg Alloy
  Journal of Engineering Materials and Technology, Transactions of the ASME 2025 DOI: 10.1115/1.4067131
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• Microstructure and Mechanical Behavior of Various Solution Treated Biomedical Superelastic NiTi Shape Memory Alloy: An Experimental Investigation
  Journal of Materials Engineering and Performance 2025 DOI: 10.1007/s11665-025-10701-z
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• Modeling, dislocation pinning and softening mechanism in Al7150-B4C-graphene hybrid nanocomposite with identified safe processing parameters during hot deformation
  Materials Characterization 2025 DOI: 10.1016/J.MATCHAR.2025.115632
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• New Method for Microstructure Segmentation and Automatic Grain Size Determination Using Computer Vision Technology during the Hot Deformation of an Al-Zn-Mg Powder Metallurgy Alloy
  Journal of Materials Engineering and Performance 2025 DOI: 10.1007/s11665-023-09025-7
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• Segmentation Studies on Al-Si-Mg Metallographic Images Using Various Different Deep Learning Algorithms and Loss Functions
  Engineering Reports 2025 DOI: 10.1002/eng2.70119
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