M.Sc. Student • ML / Data Science • Koblenz, Germany
Machine Learning Developer with 1.5+ years of experience in ML/AI, analytics, and production-ready Python solutions. Currently working on time series classification using Optimal Transport with GPU acceleration.
I am a Machine Learning Developer and Master’s student in Mathematical Modelling, Simulation and Optimization at Universität Koblenz, Germany. I have over 1.5 years of experience working on machine learning, data analytics, and AI-driven systems.
My work focuses on building production-ready ML solutions — from data pipelines and exploratory analysis to model development, optimization, and deployment. I enjoy combining strong mathematical foundations with practical engineering to solve real-world problems.
Currently, my master’s thesis explores time series classification using Optimal Transport methods, leveraging GPU acceleration (PyTorch + CUDA) to achieve significant performance gains over classical techniques.
Academic background focused on mathematical modelling, ML/AI, and data-driven methods.
Universität Koblenz • Germany
Vellore Institute of Technology • Vellore, India
Internships focused on ML engineering, analytics, automation, and turning data into production-ready insights.
Shree Ram Agriculture • Gujarat, India
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Featured research project combining Optimal Transport, GPU acceleration, and real-world time-series classification.
Universität Koblenz
Built a GPU-accelerated Optimal Transport Warping (OTW) approach for efficient, accurate time-series classification and benchmarking against DTW on UCR datasets.
Key Results
A selection of personal projects focused on ML, ETL, analytics, and real-world evaluation.
Machine Learning • Personal Project • Jan 2025 – Mar 2025
Built an end-to-end recommendation workflow with ETL, EDA, feature work, and evaluation for better ranking and personalization.
Data Engineering • Personal Project • Jul 2024 – Sep 2024
Created ETL pipelines and dashboards for epidemiological data to extract insights and visualize trends interactively.
Machine Learning • Personal Project • Mar 2024 – Apr 2024
Developed and compared multiple models on an imbalanced dataset to detect fraud with strong evaluation and tuning.
Want to see more? I can add dedicated pages for each project later, but this section is intentionally kept static and recruiter-friendly.
Tools and technologies I use to build ML systems, data pipelines, and production-ready applications.
Modeling, deep learning, and applied AI
Core ML + data stack
Dashboards and storytelling
Platforms, delivery, and collaboration
Statistics and experimentation
Primary + supporting languages
Day-to-day ML workflow
Certifications in scalable ML, Spark, analytics, and Python fundamentals.
Databricks
Databricks
Udemy
Udemy
If you want, share certificate links (Databricks/Udemy) and I’ll add a “View credential” button for each.
Languages I use for academic, professional, and everyday communication.
Currently improving
Feel free to reach out for internships, working student roles, research collaboration, or ML/AI projects.
The fastest way is email. You can also connect via LinkedIn or check my work on GitHub.
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