Skip to content
View deshmukhvs23's full-sized avatar

Block or report deshmukhvs23

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
deshmukhvs23/README.md

Hi, I'm Vedant Deshmukh 👋

M.Tech Computational & Data Science @ NIT Karnataka · Applied AI Engineer · Siemens Industry Software Intern


About me

I build rigorous, production-oriented AI and engineering systems — not just demos. My work spans automated validation pipelines, ML-driven trading engines, and GenAI applications. I care about understanding why something works, not just that it works.

Currently finishing my MTech thesis on automated 3D PDF validation at Siemens Industry Software, and actively looking for Applied AI / SDE roles.


Projects

Automated 3D PDF export validation pipeline built during my MTech thesis at Siemens Industry Software.

  • Stage 1 — Orthographic STL rendering (8 NX standard views)
  • Stage 2 — C2W matrix extraction from 3D PDF and view reconstruction
  • Stage 3 — Silhouette comparison with SSIM + IoU, color-coded diff maps, HTML report
  • Deployable on CI servers — no NX license or Adobe Acrobat required
  • Python OpenCV pikepdf SSIM IoU trimesh matplotlib

Binary classification pipeline predicting next-day stock direction for 10 high-liquidity stocks.

  • 14+ technical features across momentum, volume, volatility, and trend categories
  • Chronological train/test split to prevent data leakage
  • Confidence-threshold three-zone strategy (Buy ≥0.55, Short ≤0.45, Hold)
  • Honest finding: AUC ~0.51 — marginal but consistent edge, aligned with EMH
  • Python XGBoost AdaBoost CatBoost AUC-ROC Pandas yfinance

Retrieval-Augmented Generation pipeline built from scratch — no framework magic hidden.

  • PDF ingestion → chunking → embedding → FAISS index → retrieval → LLM answer
  • Every design decision documented: chunk size trade-offs, why cosine similarity, flat vs IVF index
  • Evaluation layer with retrieval quality scoring
  • Python sentence-transformers FAISS pypdf Anthropic

Experience

Siemens Industry Software — Intern, NX Software (Jun 2025 – Present)

  • Delivered Image Comparison Autotest POC — integrated 3rd party APIs into NX C++ core
  • Developed Edge Transition Symbol (ETS) backend logic for MBD annotation workflows
  • Resolved critical defects in NX 3D PDF workflows — Viewport APIs, Digital Signature APIs

Skills

Languages     Python · C/C++ · Java · SQL
ML / AI       XGBoost · CatBoost · OpenCV · scikit-learn · NumPy · Pandas
GenAI         RAG · Embeddings · Vector DBs · Prompt engineering · LangChain
Backend       FastAPI · REST APIs · Git · Docker
AI Engineering SSIM · IoU · Morphological processing · C2W matrix reconstruction

Education

  • M.Tech Computational & Data Science — NIT Karnataka, Surathkal (2024–2026)
  • B.Tech Instrumentation and Control Engineering — Vishwakarma Institute of Technology, Pune (2019–2023)

Connect

LinkedIn GitHub Email

Pinned Loading

  1. Image-Comparison-Autotest Image-Comparison-Autotest Public

    Automated 3D PDF export validation pipeline · STL rendering · C2W matrix reconstruction · SSIM · IoU · Python

    Python

  2. ML-Driven-Trading-Signals ML-Driven-Trading-Signals Public

    Binary classification pipeline predicting next-day stock direction using technical indicators

    Python