Bragadesh Srivatsan
Angestellt, Intern, Bosch Gruppe
Student, Computational Mechanics of Materials and Structures, University of Stuttgart
Stuttgart, Deutschland
Über mich
A highly motivated data scientist with a background in engineering and one year of industry machine learning and data science experience. With my strong problem-solving and analytical skills, I'm looking for an opportunity to innovate product development. I also have solid structural and material mechanics knowledge and a few years of experience in FE vehicle crash modeling.
Werdegang
Berufserfahrung von Bragadesh Srivatsan
As an intern in the digitization and innovation team: - Working on the development of software for data-sensing and data-acquisition of stresses in GPUs - I4.0 development - Fatigue evaluation of GPU's Ball Grid Array solder joint, using FE simulations and Machine Learning Skills acquired: - Working with SQL to create, retrieve and update data in a database built from experiments
Thesis topic: Solder Joint Fatigue Prediction under Dynamic Loading using Random Forests and LSTMs Skills acquired: -Employing python scripts to write ANSYS macros for input-output, data manipulation, visualization, regression, and time-series models -Working with libraries like TensorFlow, sci-kit learn, Numpy, and pandas -Conducting thermo-mechanical simulations of the QFN model in ANSYS APDL -Collaborated with ANSYS to develop a twin model for solder joint fatigue with ANSYS Twin Builder
8 Monate, Mai 2021 - Dez. 2021
Studentische Aushilfskraft
Institut für Flugzeugbau (IFB)
As a student assistant in IFB: - Engaged in replacing the ordinary Von-mises yield surface material with MAT_SAMP material in LS-Dyna for matrix for a statistical volume element of carbon fiber composite - Conducted coupon test simulations in tension, compression, and shear for material characterization - Modified ANSA scripts to define, assign and simulate the new material models in SVE Skills: LS-DYNA · ANSA
6 Monate, Apr. 2021 - Sep. 2021
Studentische Aushilfskraft
Institut für Materialprüfung, Werkstoffkunde und Festigkeitslehre (IMWF)
As a student assistant in IMWF: - Simulated three-point bending with cohesive zone modeling for rupture in Salome-meca - First-hand experience in FE rupture and cohesive zone modeling Skills: Salome-meca · FE Rupture Simulation
6 Monate, Okt. 2020 - März 2021
Studentische Aushilfskraft
Institute for Modelling and Simulation of Biomechanical Systems (IMSB)
As a student assistant in IMSB: - First-hand experience with THUMS human body model and LS-Dyna - Literature research Skills: Literature Reviews · LS-DYNA · Hypermesh
7 Monate, März 2020 - Sep. 2020
Studentische Aushilfskraft
HLRS - High-Performance Computing Center Stuttgart
As a student assistant in HLRS: - Designed a model of HLRS in Siemens NX and conducted an OpenFoam simulation of wind around the model - First-hand experience with CFD and OpenFoam Skills: OpenFOAM · Siemens NX
2 Jahre und 9 Monate, Nov. 2016 - Juli 2019
Modeler
Detroit Engineered Products
Skills acquired: - In-depth pre-processing techniques with Hypermesh and ANSA - Ability to manage team and workflow within the team - Experience in assembly management and CAD Study in Siemens Vismockup - Estimate hours for each assembly to ensure on-time delivery
Ausbildung von Bragadesh Srivatsan
Bis heute 5 Jahre, seit Okt. 2019
Computational Mechanics of Materials and Structures
University of Stuttgart
- With the main focus on Numerical methods for FEM, Nonlinear modeling of Materials, Geometry, and contacts. - Pursued courses in data processing and Artificial Intelligence to broaden my skill set. - Completed additional online courses via Coursera and Udemy to improve skill sets.
3 Jahre und 9 Monate, Aug. 2012 - Apr. 2016
Mechanical Engineering
Anna University
- Graduated with distinction - Acting captain of SAE competition (BAJA), - Learnt about the assembly line and production through in-plant training in Hyundai, Ashok Leyland, and Maruthi service masters - Bachelor thesis topic: Study of Characteristics of Hydrogen Boosted Internal Combustion Engine
Sprachen
Englisch
Fließend
Deutsch
Gut