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- 🎓 Applied ML Engineer | MSc Data Science (TU Dortmund)
- 💻 Data Scientist with prior experience in full-stack software development
- 💡 Passionate about AI, Machine Learning, NLP, Deep Learning, and building impactful solutions
- 🌐 Portfolio: visheshsrivastava.com
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I’m happiest when turning messy, real-world data into clean, decision-ready apps and dashboards.
Python · SQL · PyTorch · TensorFlow · FastAPI · LangChain · Docker · AWS/Azure
Focus: Generative AI · NLP · ML Systems · Data Engineering
- IEEE IJCNN 2024 Publication — Autoencoder Optimization for Anomaly Detection: A Comparative Study with Shallow Algorithms.
- Journal of Composite Materials (2025) — Void content classification for acceleration sensor embedded glass-fiber reinforced components made by resin transfer molding.
- Hessen Ideen Stipendium (2023) — Six-month State of Hesse startup scholarship (projects.ai) for an AI-driven document-workflow automation prototype; completed workshops in mentoring, business model development, financing, marketing, and pitch training.
I contribute across my own repos and community projects. PRs/issues visible in the Contributions tab.
Coming soon on visheshsrivastava.com and Medium.
⭐ Thanks for dropping by! If something here sparks an idea, let’s build it. 🚀