VISHNU VARDHAN REDDY CHADA

A challenging and innovative career in a forward-thinking company where I can share and improve my expertise and advance professionally by giving it my best. I am highly knowledgeable in Java/J2EE technologies and thrive in all phases of the software development lifecycle, including design, analysis, coding, testing, and deployment. I bring extensive expertise in a diverse array of web technologies, including HTML5, CSS3, and JavaScript, typescript, along with proficiency in frameworks such as AngularJS, NodeJS, ReactJS, Vue.js, and .Net. My knowledge extends to the Spring Framework and Java 8 features, complemented by familiarity with various open-source frameworks and testing tools, including JUnit, Mockito, TestNG, and Cucumber. I excel in designing and implementing MongoDB clusters, managing NoSQL and SQL databases, and deploying fault-tolerant systems on leading cloud platforms like AWS and Azure. My skills include the establishment of robust CI/CD pipelines using Jenkins, GitHub Actions, and Azure DevOps, as well as adeptness in containerizing applications with Docker. With strong project management capabilities utilizing tools like Jira and Agile methodologies, I am dedicated to delivering high-quality software solutions. Proficient in RESTful API design, microservices architecture, and frontend frameworks like Bootstrap, I consistently implement security best practices in software development. Additionally, my expertise extends to version control systems, encompassing GitHub Actions and SVN, reflecting my ability to contribute effectively to software development projects through collaborative and version-controlled workflows.

Logical data analyst skilled in requirement analysis, software development and database management. Self-directed and proactive professional with several years of vast experience collecting, cleaning and interpreting data sets. Natural problem-solver possessing strong cross-functional understanding of information technology and business processes.

Self-motivated Data Analyst offering several years of leadership experience across various industries. Methodical with significant experience in data mining and statistical analysis. Excellent problem-solver with history automating processes and driving operational enhancements.

Goal-oriented professional successfully assists companies by developing and implementing updates to operational standards, team organization and employee engagement strategies. Proactive and personable leader with top-notch skills in streamlining information, prioritizing tasks and approaching issues with analytical mindset. Bringing years of experience and demonstrated track record of success.

Business professional offering experience delivering cost-effective, high-performance technology solutions to meet shifting organizational demands. Astute technology-business professional translates operational needs into technical solutions. Equipped with analytics and reporting expertise to provide insights using data-driven philosophy.

Seasoned SQL Developer with experience in designing, coding, and testing database systems. Skills include advanced knowledge of SQL, data management, and ability to troubleshoot complex software issues. Proven success in enhancing system performance in previous roles. Committed to maintaining up-to-date industry knowledge and IT skills.

• S. Athmaja, M. Hanumanthappa and V. Kavitha, A survey of machine learning algorithms for big data analytics, 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, India, 01/01/17, 1-4, 10.1109/ICIIECS.2017.8276028
• S. Mittal and O. P. Sangwan, Big Data Analytics using Machine Learning Techniques, 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 01/01/19, 203-207, 10.1109/CONFLUENCE.2019.8776614
• P. Thamjaroenporn and T. Achalakul, Big Data Analytics Framework for Digital Government, 2020 1st International Conference on Big Data Analytics and Practices (IBDAP), Bangkok, Thailand, 01/01/20, 1-6, 10.1109/IBDAP50342.2020.9245461
• P. Vashisht and V. Gupta, Big data analytics techniques: A survey, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Greater Noida, India, 01/01/15, 264-269, 10.1109/ICGCIoT.2015.7380470
• L. Zhou, S. Pan, J. Wang, & A. Vasilakos, Machine learning on big data: Opportunities and challenges, Neurocomputing, 237, 350-361, 01/01/17, 10.1016/j.neucom.2017.01.026
• J. Liu and T. Wang, Scalable Machine Learning for Big Data Processing, Journal of Data Management, 8, 3, 09/01/20, https://www.researchgate.net/publication/308123199_Scalable_machine-learning_algorithms_for_big_data_analytics_a_comprehensive_review_Scalable_machine-learning_algorithms_for_big_data_analytics
• E. T. Bradlow, M. Gangwar, P. Kopalle, & S. Voleti, The role of big data and predictive analytics in retailing, Journal of Retailing, 93, 1, 79-95, 01/01/17, 10.1016/j.jretai.2016.12.004
• M. Alloghani, D. Al-Jumeily, A. Hussain, A. J. Aljaaf, J. Mustafina and E. Petrov, Application of Machine Learning on Student Data for the Appraisal of Academic Performance, 2018 11th International Conference on Developments in eSystems Engineering (DeSE), Cambridge, UK, 01/01/18, 157-162, 10.1109/DeSE.2018.00038
• H. B. Patel and S. Gandhi, A Review on Big Data Analytics in Healthcare Using Machine Learning Approaches, 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, 01/01/18, 84-90, 10.1109/ICOEI.2018.8553788
• J. Bzai, F. Alam, A. Dhafer, M. Bojović, S. M. Altowaijri, I. K. Niazi, & R. Mehmood, Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective, Electronics, 11, 17, 2676, 01/01/22, 10.3390/electronics11172676
• Dávid Markovics, Martin János Mayer, Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction, Renewable and Sustainable Energy Reviews, 161, 01/01/22, 112364, 10.1016/j.rser.2022.112364
• P. S. Kumar and S. Pranavi, Performance analysis of machine learning algorithms on diabetes dataset using big data analytics, 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), Dubai, United Arab Emirates, 01/01/17, 508-513, 10.1109/ICTUS.2017.8286062
• R. F. Gibadullin, G. A. Baimukhametova and M. Y. Perukhin, Service-Oriented Distributed Energy Data Management Using Big Data Technologies, 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Sochi, Russia, 01/01/19, 1-7, 10.1109/ICIEAM.2019.8743064
• Jian Li, Big Data Analytics Using Machine Learning Techniques for Prediction on Datasets, Computational Methods, 1, 1, 32 – 41, 01/01/24, 10.58614/cm114
• R. Singh and G. Kaur, Machine Learning in Big Data for Cybersecurity Applications, Journal of Cyber Intelligence, 13, 7, 01/01/20, https://www.researchgate.net/publication/366071082_Real-Time_Big_Data_Processing_and_Analytics_Concepts_Technologies_and_Domains
• P. Kumar and A. Verma, Leveraging Machine Learning for Big Data Supply Chain Analytics, Journal of Supply Chain Analytics, 10, 9, 01/01/21, https://www.researchgate.net/publication/378108443_Leveraging_Big_Data_Analytics_to_Enhance_Machine_Learning_Algorithms
• Y. Zhao and L. Wei, Real-Time Traffic Monitoring Using Big Data and Machine Learning, Journal of Transport Analytics, 5, 2, 02/01/22, https://www.researchgate.net/publication/364672198_Real-time_traffic_congestion_prediction_using_big_data_and_machine_learning_techniques
• R. Bose and S. Kumar, Predictive Maintenance Using Machine Learning on Big Data, Journal of Industrial Analytics, 4, 12, 12/01/21, https://www.researchgate.net/publication/360724726_Predictive_Maintenance_using_Machine_Learning