AMBRISH BIREDAR
Summary
Analyst at MBRDI with a strong academic background in Applied Mechanics from IIT Madras. Experienced in sheet metal forming simulations for Body-in-White (BIW) components and applying AI for springback prediction. Currently researching MeshGraphNets for deep learning applications on varying geometries. Actively contributing to the Quantum Computing group to explore its potential in CAE.
Overview
9
9
years of professional experience
Work History
Analyst
Mercedes-Benz Research and Development India
08.2021 - Current
- Conducted manufacturing feasibility simulations for prototype BIW components, providing design modifications for feasibility
- Springback Prediction Using AI: Implemented traditional ML methods, later pivoting to GNNs, inspired by DeepMind’s MeshGraphNets research
- Key member of the Quantum Computing for CAE working group—conducted research, technology landscaping, and awareness programs for leadership
- AR/VR in Manufacturing: Conceptualized an AR-based plastic trim fitting system for enhanced precision
Analyst
EASi
08.2016 - 07.2018
- Conducted structural mechanics simulations, including pothole and jacking analysis, on General Motors vehicles for the North American market
Education
Master of Science - Applied Mechanics
IIT Madras
Skills
- Python
- BASH
- Deep Learning
- Machine Learning
- Pytorch
- Miniconda
- Cuda
- FEM
- Numerical Methods
- LSDYNA
- Autoform
Published Research
- Biredar, A., Kambhammettu, S.K.S., Chebolu, L.R., Design of Experimental Setup for Investigation of Leakage in O-Rings, Recent Advances in Applied Mechanics, Springer, 2022, https://doi.org/10.1007/978-981-16-9539-1_38
- Biredar, A., Kambhammettu, S.K.S., Chebolu, L.R., Numerical Investigation of Leakage in Elastomeric O-rings, Advances in Applied Mechanics, Springer, 2024, https://doi.org/10.1007/978-981-97-0472-9_44
Timeline
Analyst
Mercedes-Benz Research and Development India
08.2021 - Current
Analyst
EASi
08.2016 - 07.2018
Master of Science - Applied Mechanics
IIT Madras
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