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000-517-173

Venkata Gorantla

Scholar Department: Computer Science - College of Computing Certificate Views : 698 Followers : 1

Chapter: ABCD-Index Machine Learning and Artificial Intelligence Chapter
Region: Missouri, UNITED STATES MINOR OUTLYING ISLANDS
Designation: Member
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Name: Venkata Gorantla
Designation: Scholar
Department: Computer Science - College of Computing
Research Area: AI/ML, Health Informatics, Cyber Security, Cloud Computing, Data Engineering, Data Analysis
Organization: Georgia Institute of Technology
Contact: Contact Reviewer
Qualification: Masters
About: Ashok is a distinguished expert in the fields of low-code/no-code platforms, artificial intelligence and machine learning (AI/ML), and business analytics. His career is marked by a strong record of leading technical and business transformations, excelling in solution architecture, and steering Centers of Excellence for notable organizations. Currently serving as Associate Director at Verizon, Ashok is at the forefront of developing and applying innovative AI/ML algorithms, predictive and adaptive analytics. Ashok's background includes pivotal roles in the healthcare industry, where he has been instrumental in designing and executing major projects focused on customer service, Medicare management, and care management systems. With a Master of Science in Computer Science from Georgia Tech, his academic prowess complements his vast professional achievements. As a researcher, Ashok's interests span a diverse range of applications of AI/ML, covering healthcare, cybersecurity, cloud computing, and telecommunications, showcasing his versatile and profound expertise in these areas.
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Journal

Author: G. Ramesh, Venkata Ashok K Gorantla, Venkataramaiah Gude
Title: A hybrid methodology with learning based approach for protecting systems from DDoS attacks
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ISSN:
Volume:
Issue:
2023
2169-0065
26,2023
5
Indexing: SCOPUS, ESCI, SCI-E, ABCD-Index, 
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Author: Venkata Ashok K Gorantla; Shiva Kumar Sriramulugari; Amit Hasmukhbhai Mewada; J. Logeshwaran
Title: An intelligent optimization framework to predict the vulnerable range of tumor cells using Internet of things
Publication Year:
ISSN:
Volume:
Issue:
2023
979-8-3503-8197-9

Indexing: SCI-E, ABCD-Index, 
Visit Paper: Click here
More Details Click here