Rutwik G. Profile

5.0

(1 review)

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$25 USD / hour

aachen,

germany

$25 USD / hour

It's currently 2:56 PM here

Joined February 21, 2014

0 Recommendations

Rutwik G.

@rutwikgulakala

5.0

(1 review)

0.0

100%

$25 USD / hour

aachen,

germany

$25 USD / hour

100%

Jobs Completed

100%

On Budget

100%

On Time

N/A

Repeat Hire Rate

PhD in AI-enhanced FE modelling (Vehicle crash)

Skilled in Python programming and AI. Published papers on Neural Network strategies. Highly skilled Mechanical engineer with experience in Abaqus, CATIA and Siemens NX. Ready to do a free sample to showcase my skills anytime.

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5.0

$14.00 NZD

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@billrutherfurd85

•

10 years ago

Experience

Institute of General Mechanics, RWTH Aachen.

Aug 2021 - Present

* Neural network-enhanced FE modelling. * Optimization of Crashworthiness using AI. * AI-based disease diagnosis using Radiological images. * AI-based robotic control for concentric tube robots.

Tachyon Hyperloop e.V

Oct 2010 - Aug 2022 (11 years, 10 months)

* Responsible for the design and simulation of an Aeroshell. * Managed an engineering and design team to achieve a sleek and aerodynamic design with a drag coefficient of 0.1.

Institute of General Mechanics, RWTH Aachen.

Jun 2019 - Aug 2021 (2 years, 2 months)

* Neural network-enhanced finite element modelling. * Structural simulations using Abaqus and LS-Dyna. * Autonomous driving and gait analysis.

Education

Masters in Science (M.Sc)

Rheinisch-Westfälische Technische Hochschule Aachen,

Germany

2018 - 2021

(3 years)

Publications

Graph Neural Network enhanced Finite Element modelling

Proceedings in Applied Mathematics and Mechanics

GNN based FE modelling.

Generative adversarial network based data augmentation for CNN based detection of Covid-19

Nature Scientific reports

In the present study, an Artificial Intelligence-based method is proposed, resulting in a rapid diagnostic tool for Covid infections based on generative adversarial and convolutional neural networks. The benefit will be a high accuracy of lung infection identification with 99% accuracy. This could lead to a support tool that helps in rapid diagnosis, and an accessible Covid identification method using CXR images.

Rapid diagnosis of Covid-19 infections by a progressively growing GAN and CNN optimisation

Computer Methods and Programs in Biomedicine

In the present study, a method based on artificial intelligence is proposed, leading to a rapid diagnostic tool for Covid infections based on Generative Adversarial Network (GAN) and Convolutional Neural Networks (CNN). The benefit will be a high accuracy of detection with up to 99% hit rate, a rapid diagnosis, and an accessible Covid identification method by chest X-ray images.

Development of CNNs for recognition of tenogenic differentiation based on cellular morphology

Computer Methods and Programs in Biomedicine

Our study reveals that the CNN models show good performance by identifying stem cell differentiation. Importantly this technique provides a faster and real-time tool in comparison to traditional methods enabling the adjustment of culture conditions during cultivation to improve the yield of therapeutic stem cells.

Artificial neural networks in structural dynamics

Computer Methods in Applied Mechanics and Engineering

The aim of the present study is to develop a series of artificial neural networks (ANN) and to determine, by comparison to experiments, which type of neural network is able to predict the measured structural deformations most accurately. For this approach, three different ANNs are proposed. By means of comparative calculations between neural network-enhanced numerical predictions and measurements, the applicability of each type of network is studied.