- Published on November 25, 2021
- In AI Features
Maintaining A Daily Log Help In Structuring Research Work: Sahana Prabhu, Robert Bosch
Explainability is emerging for many domains such as medical imaging, assisted driving, and manufacturing defect detection.
- By Dr. Nivash Jeevanandam
A data scientist transitioned from an electronic communication engineer, Sahana Prabhu's research interests include diabetic retinopathy image analysis, meibomian image segmentation, emotion recognition via deep learning approaches, and retail analytics via RFID and stereo cameras. Analytics India Magazine caught up with Sahana, who is currently serving as a research scientist and technical architect at Bosch Engineering and Business Solutions, to understand her insights on deep learning, machine learning, etc.
AIM: As a research scientist, what factors do you believe contribute to your research success? Please throw some light on it for us.
Sahana Prabhu: Proper dataset collection that is representative of the problem to be solved is vital. Once the problem statement is formulated,
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Dr. Nivash Jeevanandam
Nivash holds a doctorate in information technology and has been a research associate at a university and a development engineer in the IT industry. Data science and machine learning excite him.
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