Applying new data analysis or ML methods to analyze multi-modal time series data
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1 min read
Work:
- Using parallelization and GPU/CPU to improve data analysis pipelines
- Denoising neural data and extracting important features
- Dealing with small datasets
- Classifying behavior in images
Application in industry:
- Healthcare: Analyzing condition of motion and sensory processing of each patient
- Robotics: Develop robots with motion inspired by real humans
- Assistive Devices: tackling only motion dimension of a human and built assistive devices based on that
- Automated data labelling to train models for smart wearables
- Various Data analysis cases where limited time series data is a problem
