Vishwaas Narasinh is a seasoned researcher specializing in Artificial Intelligence, particularly in Industrial AI applications. With a Bachelor’s degree in Electronics and Communication Engineering from PESIT and a Post Graduation Diploma in Artificial Intelligence and Machine Learning from the Great Lakes Institute of Management, he has accrued over 8.5 years of experience in the field. Currently employed at Hitachi India Pvt. Ltd., Narasinh has made significant contributions to enhancing sales forecasts for construction equipment and analyzing wind turbine vibration data, leading to additional projects, publications, and patents. His expertise extends to Conversational AI, where he led projects in weather data conversion and model optimization at LG Soft India Pvt. Ltd. He has also contributed to predictive modeling for Lithium-Ion batteries and workflow recommendation systems at Robert Bosch Bangalore.
- Google Scholar Citation Profile: Link
Education:
- Bachelor of Engineering in Electronics and Communication Engineering from PESIT
- Post Graduation Diploma in Artificial Intelligence and Machine Learning from the Great Lakes Institute of Management
Research Focus:
Narasinh’s research primarily focuses on Industrial AI applications, including construction equipment sales forecasting, wind turbine vibration analysis, and machine fault diagnostics in manufacturing plants. He also explores areas such as Music Information Retrieval and Audio Signal Processing.
Professional Journey:
- Researcher at Hitachi India Pvt. Ltd., specializing in Industrial AI
- Senior Research Engineer at LG Soft India Pvt. Ltd., leading Conversational AI projects
- Associate Software Engineer at Robert Bosch Bangalore, focusing on predictive modeling and workflow recommendation systems
Honors & Awards:
- Best Paper Award at the 4th Hitachi AI Conference
- Co-author of patents related to troubleshooting in factory environments and real-time pitch optimization for power output maximization
Publications Top Noted & Contributions:
Narasinh has authored or co-authored several publications and contributions, including papers presented at conferences and under peer review. Notable works include raga detection, readability analysis of Kannada language, wind turbine fault analysis, and machine fault diagnostics in manufacturing plants.
Readability Analysis of Kannada Language
- Author: V Narasinh
- Conference/Journal: 2019 1st International Conference on Advances in Information Technology
- Cited By: 1
- Year: 2019
Sequential Pitch Distributions for Raga Detection
- Author: V Narasinh
- Source: arXiv preprint arXiv:2308.16421
- Cited By: N/A (not specified)
- Year: 2023
Sequential Pitch Distributions for Raga Detection
- Author: SRG Vishwaas Narasinh
- Source: AI Music Creativity 1, 16
- Cited By: N/A (not specified)
- Year: 2023
A Deep Learning Approach for Tonic Detection For Indian Art Music
- Author: SRG Vishwaas Narasinh
- Conference/Journal: International Conference on New Music Concepts 10 (1)
- Cited By: 9
Research Timeline:
- 2019: Presented “Readability Analysis of Kannada Language” at the 1st International Conference on Advances in Information Technology
- 2023: Presented papers on “Sequential Pitch Distributions for Raga Detection” and “A Deep Learning Approach for Tonic Detection for Indian Art Music”
- 2024: Co-authored a paper on “Investigating power loss in a wind turbine using real-time vibration signature” published in Engineering Failure Analysis
- Ongoing: Contributing to ongoing research projects and patent applications in Industrial AI and related fields
