Danushkumar Venkadesh
Machine Learning Engineer at HP (R&D)
Eindhoven, Netherlands
Joined April 2026
Summary
Applied machine learning researcher with peer-reviewed publications: Danushkumar has contributed to applied ML research in infrastructure and geosciences, with author roles that include data curation, formal analysis, methodology and software for published papers on rebar interval assessment (2024) and sinkhole grout volume prediction (2025). sciencedirect+2
Active Kaggle practitioner and dataset creator: publishes notebooks and datasets (MNIST classification notebooks, job-title analysis, Birds-200 dataset) indicating hands-on experience building and sharing ML experiments and curated data for the community. kaggle+2
Early-career ML engineer with diverse industry and research experience: roles listed include multiple machine learning engineering and research positions and internships across industry and academia, culminating in an R&D role at HP in 2024. theorg
Practitioner of hands-on projects and public tutorials: produces project videos and participates in hackathons, demonstrating practical engineering and outreach through maker-style tutorials and hackathon gallery submissions. youtube+2
Work
Education
Projects
Writing
Advancements in Sinkhole Remediation: Field data-driven Sinkhole grout volume prediction model via machine learning-based regression Analysis
January 1, 2025Study presenting a machine learning regression model to predict grout volumes for sinkhole remediation using CPT-derived indices and field data; includes data transformation methods and model evaluation.
Real-time assessment of rebar intervals using a computer vision-based DVNet model for improved structural integrity
January 1, 2024Paper describing a computer vision / deep learning approach (DVNet) for real-time detection and assessment of rebar intervals to improve structural inspections and integrity.