Ravi S Cheruvu
About Ravi S Cheruvu
Ravi S Cheruvu is a Principal Research Investigator with extensive experience in artificial intelligence and natural language processing. He currently works at BIRD Analytics and Sensfix, contributing to advancements in defect detection, chatbot development, and predictive algorithms.
Work at Sensfix
Ravi S Cheruvu serves as the Principal Research Investigator at Sensfix since 2020. In this role, he focuses on developing innovative solutions that leverage artificial intelligence and machine learning. His work includes creating natural language-based information extraction tools tailored for the healthcare industry. This position allows him to apply his extensive expertise in computer science and natural language processing to address complex challenges in the field.
Current Role at BIRD Analytics
Since 2017, Ravi S Cheruvu has held the position of Chief Research Scientist at BIRD Analytics in Greater Bengaluru Area. In this capacity, he leads research initiatives that integrate advanced technologies into practical applications. His contributions include assisting banks and recruiting companies in the development of domain-specific interactive chatbots, utilizing natural language processing techniques to enhance user interaction and efficiency.
Education and Expertise
Ravi S Cheruvu has a strong educational background in computer science and engineering. He earned his Bachelor of Technology (BTech) in Electrical, Electronics, and Communications Engineering from IIT Madras from 1971 to 1976. He then pursued a Master of Technology (MTech) in Computer Science from 1976 to 1978. Later, he completed his Ph.D. in Natural Language Processing, AI, and Computer Science at the University of Hyderabad from 1986 to 1993. This extensive education underpins his expertise in various domains, including AI and computer vision.
Research Contributions
Ravi S Cheruvu has made significant contributions to various industries through his research. He has helped manufacturing companies implement early defect detection systems in production and assembly processes using computer vision technology. Additionally, he developed predictive algorithms for early detection of crack formation in shafts in steam turbines. His work also includes creating advanced AI-based vehicle routing algorithms for logistics companies, showcasing his versatility in applying technology to solve real-world problems.