Nijanth G

● Visiting Client places for Data Collection,Technical Support and Handling Client Issues.
● Annotating the collected data for training AI Model.
● Troubleshooting applications in Client places. Data collection as per requirement.
● Revising training data. Data segregation, Data preprocessing. Training the AI Model in GPU and
GCP(Segmentation). Inferencing the model and recording the Result. Testing the Model.
● Creating Generic Datasets.
● Handled clients for AI Automation Model with Schneider Electric, Tata Advanced Systems, Maini
Precision Products, TE - Connectivity.
● Working on a Product - Testing User Experience, Training Models.

Visiting client places for data collection, technical support, and handling client issues.
Annotating the collected data for training AI model.
Troubleshooting applications in client places.
Data collection as per requirement.
Revising training data.
Data segregation.
Data preprocessing.
Training the AI model in GPU and GCP (Segmentation).
Inferencing the model and recording the result.
Testing the model.
Creating generic datasets.
Handled clients for AI Automation Model with Schneider Electric, Tata Advanced Systems, Maini Precision Products, TE-Connectivity.
Working on a product - testing user experience, training models.

Responsible for filing additional claims that are in a pending status until all the required information is received.
Organized and reviewed medical claims for completeness and accuracy.
Took appropriate action to ensure procedures are followed.
Assisted Medical Claims Examiners in reviewing approved claims for payment, ensuring information is accurate.
Filled out discrepancy sheets for Adjudicators to correct any misspelled information approved claims.
Made appropriate system entries and verified accuracy.
Ensured utilization of most up to date processes and procedures to update claims.
Identified process improvements.
Offered solutions to claim problems.
Communicated recommendations to management.

Project Tannhaus – AI Machine Learning project that needs to annotate an image containing natural scenarios.
Project Drogon – detecting objects lively from a satellite view.
Project Reznikov – detecting objects inside a car with the driver while driving, including the driver's activities.
Project Notre Dame 2D-OD – object detection process mainly used for automated driverless cars.
Detection of traffic lights, traffic signs, nearby vehicles, pedestrians, and some more attributes.
Project Skyhawk – segmentation process same as the previous project and some modified attributes used for automated driverless cars.
Used tool – Playment GT studio.