Skip to content
View TejasManjunath's full-sized avatar

Highlights

  • Pro

Block or report TejasManjunath

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
TejasManjunath/README.md

Tejas Manjunath

MSc Data Science student in Dortmund. Working on automotive safety simulation and statistical forecasting — most of what's here is real project work, not tutorials. Currently restudying deep learning fundamentals toward a planned thesis on Bayesian Neural Networks for uncertainty-aware driver monitoring.

🔬 Research

Published first-author paper on AEB failure modes — 100,000-scenario Monte Carlo simulation in CARLA, validated across 1.54M German crash records. → Read the paper

📈 Forecasting

Built a time series pipeline (ARIMA / SARIMA / Holt-Winters) that matched Germany's official VDA registration forecast using only public data — backtested across 76 expanding-window origins.

🌳 Applied ML

5-horizon bankruptcy prediction pipeline (Random Forest, XGBoost, SMOTE) — AUC 0.903, built around a €28.5M cost-of-error argument.


Core stack: Python SQL CARLA KNIME

Also comfortable with: Java, C/C++, React/Node (full-stack internship background), SAP S/4HANA, Power BI

LinkedIn · Email

Pinned Loading

  1. aeb-blind-side-study aeb-blind-side-study Public

    CARLA simulation study quantifying the lateral detection blind zone in production ADAS. 100k-scenario Monte Carlo analysis of AEB response to motorcycle and vehicle lateral departure at highway spe…

    Python

  2. adas-validation-gap-analysis adas-validation-gap-analysis Public

    Data-driven analysis of 1.53M German crash records to identify high-severity scenarios missing from Euro NCAP ADAS validation protocols.

    Python 1

  3. Self-Driving-Car-Control-System-CARLA-9.10 Self-Driving-Car-Control-System-CARLA-9.10 Public

    Python