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rebelgiri/README.md

Resume

🚴‍♂️ Introduction

  • I'm Giri, an avid Artificial Intelligence enthusiast with a keen interest in crafting and implementing AI/ML-driven solutions, leveraging the agile and scrum software development life cycle. 😊

  • I hold a Master's degree in Embedded Systems from the Technical University of Chemnitz, where my research focused on Unsupervised Learning and Generative Adversarial Networks. https://github.com/rebelgiri/thesis-domain-adaptation-of-synthetic-document-images-using-neural-networks

  • I am presently employed at Fusionsystems GmbH in Chemnitz, Germany, where my role involves overseeing automotive software development and testing while ensuring compliance with ISO 26262 and ASIL standards. Concurrently, I am engaged in collaborative projects with automotive software companies such as Cariad, FD Tech, and Intenta in the Saxony region.

🚅 Projects and Experiences

  • Predictive Maintenance project using Deep Learning and Vibration data for Condition Monitoring of Industrial Machinary 😍. https://github.com/rebelgiri/predictive-maintenance-using-deep-learning
  • A research project in the area of Multi-Object Multi-Camera Tracking for Pedestrians 😍.
  • Atively contributed to numerous C++ projects with a primary focus on Sensor Data Fusion. One notable example includes utilizing Bayesian Networks to estimate the driving direction of lanes.
  • Extensive work in C and C++ programming for Cross-Platform application development. I possess a strong grasp of the GNU Linux operating system, having served as a Linux System Programmer at renowned companies like Huawei Technologies and UST Global (deputed at Intel).

⛷️ Skills

  • Languages : C, C++ and Python
  • Tools : Git, JIRA and Confluence
  • Frameworks : Google Test, TensorFlow, Keras and PyTorch
  • Libraries : OpenCV, Scikit-learn and NumPy

🧘‍♂️ Professional Interests

  • C++ software development and unit testing using Google Test & gMocks
  • Computer Vision
  • Deep Learning and Machine Learning (PyTorch, TensorFlow and Keras)
  • Algorithms and Data Structures
  • Bayesian Networks and Predictive Filters like Kalman
  • Sensor data fusion

giriraj.pawar2012@gmail.com

LinkedIn

Credits

😊 I have created my profile by referring an article created by Lakshmanan Meiyappan.

Pinned Loading

  1. predictive-maintenance-using-deep-learning predictive-maintenance-using-deep-learning Public

    In this work, we use the Deep Learning model to build a classifier for the classification of the 3D vibration data.

    Python 1

  2. thesis-domain-adaptation-of-synthetic-document-images-using-neural-networks thesis-domain-adaptation-of-synthetic-document-images-using-neural-networks Public

    Domain adaptation of synthetic document images using neural networks

    Jupyter Notebook 1

  3. image-retrieval-using-deep-learning image-retrieval-using-deep-learning Public

    Python 1

  4. snap_translate snap_translate Public