TAKK Solutions

science based solutions...

Transition to Turbulence Prediction

Predicting the onset of something as chaotic and unpredictable as Turbulence is a challenge worth exploring. This project dives into the sea of predicting different transition to turbulence scenarios.

Application of Multiscale Non-Linear Transition model to fluid flow problems was implemented to acheive a higher order transition model.

Use of different supervised and unsupervised machine learning algorithms to predict the onset of boundary of Turbulent zones is a novel approach to predicting Transition.

Lung Cancer Detection

Early lung cancer detection algorithm can help save thousands of lives. The application of machine learning algorithms to detect lung cancer was the goal of this project.

This project was initiated as an entry in the Data Science Bowl 2017. The goal was to predict the presence of malignant lung cancer growth from CT Scan images of patients, an year prior to their diagnosis.


Using GPU computing to save on power per unit teraflop. Building GPU workstations and hands on experience with CUDA and OpenCL applications/libraries.

Using optimized hardware for different problems. GPU power being used for Convolution Neural Networks. Using optimal CPU and GPU workload for solving non-linear partial differential equations.

Using salavged equiment to prevent it from going to landfills with optimal loads to improve efficiency. Making the world a better place while solving complex problems and using the right tools for the job.

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For more details of our projects please email us at info@takksol.com