Kaushik Koneripalli
Machine Learning Engineer at Shell
Karnataka, India
Summary
👤
Senior🎓
Top SchoolKaushik Koneripalli is a Machine Learning Engineer with eight years of experience applying deep learning, computer vision, and scientific ML to business and government problems. He currently develops graph neural network surrogates to accelerate reservoir simulation at Shell and builds automated literature-scraping workflows to discover scientific novelties. Previously at SRI and Siemens he translated generative modeling and ML research into production-relevant solutions across diverse domains. Kaushik’s background in signal processing and geometric media research underpins a practical focus on disentangled representations and surrogate modeling. Based in Abu Dhabi, he combines academic rigor—documented on Google Scholar—with hands-on engineering that spans prototypes to deployed pipelines.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Telecommunications Engineering, Bachelor's degree, Telecommunications Engineering at PES UniversityMS in Electrical Engineering, Signal Processing, MS in Electrical Engineering, Signal Processing at Arizona State University
English, Kannada
Github Skills (32)
hierarchical7
python7
cuda7
nlp6
deep-learning6
graph6
variational-autoencoder6
machine-learning6
autoencoder6
devkit6
knowledge-graph5
spotlight4
vtk4
regl3
meshlab3
Programming languages (1)
Github contributions (5)
kaushik333/S2-graph-based-Active-Learning
Feb 2019 - Sep 2019
Contributions:28 commits, 11 pushes, 1 branch in 7 months
Contributions:12 commits, 8 pushes, 1 branch in 5 months
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