Deepak Dasaratha Rao Editor at IgMin Research
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Biography
Deepak Dasaratha Rao is a technologist with 25 years experience in software R&D and worked for large product companies. He has experience in software R&D and developed for Embedded Systems, Smartphone platforms, Data Wireless Communication, Cloud, AI, IoT, Connected Vehicle Telematics, Automotive, Consumer Electronics, Connected Healthcare, Bio-medical, Wearable products.
He has developed on several first-of-its kind innovatie software products, devised strategy and reached differentiated products as a solution architect, product manager, technology leader and innovator. Experienced in designing embedded system-based software architecture, technically leading full stack development for software platforms, system software, middleware, solutions, services and applications.
Deepak Rao has worked software products for Connected Car, Smartphones, Connected Devices Platform, Wearables, Smart Home Setup Box, Robotics. He has published several international papers in the journals and conferences. He has contributed as a journal reviewer for many research publications in area of wireless communication and computer science. He is a Fellow of RSA (UK), Fellow of The Institution of Engineers (India), Fellow of The Institution of Electronics and Telecommunication Engineers (IETE) India.
Research Interest
IoT, Computer Science, Networking, Wireless Communication, AI
Editor
Work Details
Consultant
Infosys Ltd.
software R&D
United States
Contribution by Topic Area
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Research Articles
- Deep Learning-based Multi-class Three-dimensional (3-D) Object Classification using Phase-only Digital Holographic Information
- Application of Virtual Reality (VR) in Facility Management Competency-based Training (CBT) in the Era of Industrie 5.0
- Methodology of the Professional-Business Game for the Development of a Cadet Leader in Professional Training Courses (L-1B) of the Tactical Level of Military Education
- Examining the Causal Connection between Lipid-lowering Medications and Malignant Meningiomas through Drug-target Mendelian Randomization Analysis
- Federated Learning- Hope and Scope
- A Machine Learning-based Method for COVID-19 and Pneumonia Detection
