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Yeshwanth Vasa | Information Technology | Excellence in Innovation

Postdoctoral Research Associate at CIPET:SARP-LARPMb, India.

Yeshwanth Vasa is an accomplished AI/ML Consultant at Miracles Tek LLC, bringing a wealth of experience in project management methodologies, particularly in Waterfall and Agile frameworks. He possesses excellent communication and interpersonal skills, enabling him to effectively collaborate with stakeholders to analyze functional requirements. Yeshwanth has a proven track record in developing comprehensive test plans and documentation for both manual and automated testing processes, showcasing his dedication to quality and innovation in software development.

 

Profile:

Education

Yeshwanth Vasa completed his Bachelor’s degree in Electronics and Communication Engineering from Jawaharlal Nehru Technological University in Hyderabad, Telangana, India. His academic journey spanned from September 2009 to July 2013, during which he developed a strong foundation in core engineering principles and technical skills. The curriculum emphasized a comprehensive understanding of electronic systems, communication protocols, and signal processing, equipping him with the knowledge necessary for his future career in technology. Through various projects and practical assignments, Yeshwanth honed his problem-solving abilities and gained hands-on experience in applying theoretical concepts to real-world challenges. His educational background not only prepared him for the complexities of the technology sector but also fueled his interest in artificial intelligence and machine learning, driving him to explore innovative solutions in software development and automation. This solid educational foundation continues to support his professional growth in the rapidly evolving tech landscape.

 

Professional Experiences 

Yeshwanth Vasa has been making significant contributions as a Software Engineer at Miracles Tek LLC since November 2016. In this role, he is responsible for designing automation frameworks for end-to-end Angular-based web applications, leveraging Selenium WebDriver via Protractor. His expertise extends to running regression and smoke testing suites, utilizing tools like Jenkins for nightly builds, and performing RESTful API testing to validate financial transactions. Yeshwanth also excels in functionality-based UI testing and data validation, using DynamoDB and AWS CloudWatch for comprehensive analysis. Beyond his technical responsibilities, he plays a crucial role in mentoring employees on various technical platforms and conducting performance appraisals to ensure career development. His leadership capabilities are further highlighted by his management of a team of IT professionals and analysts, guiding them through the design, development, and implementation of innovative solutions, making him a valuable asset in the software development arena.

Research Interests

Yeshwanth Vasa’s research interests lie at the intersection of artificial intelligence and machine learning, particularly in enhancing software development processes through innovative testing methodologies. He is deeply engaged in exploring how AI can optimize software testing and quality assurance, aiming to streamline the lifecycle of project management from requirements analysis to deployment. His focus includes developing automation frameworks that improve the efficiency and effectiveness of testing for web applications, leveraging tools such as Selenium and Protractor. Additionally, Yeshwanth is interested in the application of machine learning algorithms to analyze data for defect tracking and reporting, enabling more accurate predictions of potential issues within software. He is also keen on understanding the implications of data management and business intelligence in AI-driven solutions. By combining his technical expertise with a strong research foundation, Yeshwanth aims to contribute to advancements in AI/ML that enhance software performance and reliability.

 

Research skills 

Yeshwanth Vasa possesses a robust set of research skills that are essential for driving innovation in the fields of artificial intelligence and machine learning. His expertise in automation testing frameworks is evident in his design and implementation of end-to-end solutions using Selenium WebDriver and Protractor for Angular-based web applications. Yeshwanth has a strong foundation in API validation, performing comprehensive tests to ensure data integrity and functionality. He is proficient in data analysis and management, utilizing AWS CloudWatch and DynamoDB to monitor and evaluate system performance. His knowledge extends to version control systems like GIT, as well as project management tools such as JIRA and Confluence, which facilitate effective collaboration and documentation throughout the development process. Yeshwanth’s meticulous approach to developing test plans and scenarios, combined with his ability to analyze defect severity, showcases his analytical capabilities and commitment to delivering high-quality software solutions.

 

Award And Recognition 

While specific awards and recognitions were not mentioned in the provided information, Yeshwanth’s consistent contributions to the field of AI/ML and his role in enhancing software testing practices position him as a notable figure in his domain. His research publications and successful project implementations are a testament to his dedication and impact in the industry, which may lead to future accolades and recognition in the field.

 

Conclusion

In conclusion, Yeshwanth Vasa’s combination of research experience, technical expertise, and leadership skills make him a strong candidate for the Research for Excellence in Innovation Award. His ongoing contributions to the AI/ML field and his role in advancing automation and software testing practices underscore his commitment to innovation and excellence in his domain.

 

Publication Top Notes
  • yak, D., Choudhary, R.B.
  • Year: 2023
    Citations:
  • Title: Optimizing Photometric Light Curve Analysis: Evaluating Scipy’s Minimize Function for Eclipse Mapping of Cataclysmic Variables
    Authors: A Kumar, MMT Ayyalasomayajula, D Panwar, Y Vasa
    Year: 2024
    Cited by: 15
    Citation: arXiv preprint arXiv:2406.00071 🌌📈
  • Title: AUTOMATED MACHINE LEARNING FRAMEWORK USING LARGE LANGUAGE MODELS FOR FINANCIAL SECURITY IN CLOUD OBSERVABILITY
    Authors: Y Vasa, SR Mallreddy, JV Suman
    Year: 2022
    Cited by: 6
    Citation: IJRAR-International Journal of Research and Analytical Reviews (IJRAR) 🌐🔒
  • Title: Proactive Cyber Threat Hunting With AI: Predictive And Preventive Strategies
    Authors: Y Vasa, P Singirikonda
    Year: 2022
    Cited by: 1
    Citation: International Journal of Computer Science and Mechatronics 8 (3), 30-36 🔍🤖
  • Title: Predictive Maintenance In Cloud Computing And Devops: ML Models For Anticipating And Preventing System Failures
    Authors: SR Mallreddy, Y Vasa
    Year: 2023
    Cited by: –
    Citation: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal 10 (1), 213-219 ⚙️🔧
  • Title: Natural Language Querying In SIEM Systems: Bridging The Gap Between Security Analysts And Complex Data
    Authors: SR Mallreddy, Y Vasa
    Year: 2023
    Cited by: –
    Citation: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal 10 (1), 205-212 🗣️💻
  • Title: AUTOMATED MACHINE LEARNING FRAMEWORK USING LARGE LANGUAGE MODELS FOR FINANCIAL SECURITY IN CLOUD OBSERVABILITY
    Authors: JVS Yeshwanth Vasa, Sukender Reddy Mallreddy
    Year: 2022
    Cited by: –
    Citation: International Journal of Research and Analytical Reviews (IJRAR) 🌐🔒
  • Title: Biotechnological Approaches To Software Health: Applying Bioinformatics And Machine Learning To Predict And Mitigate System Failures
    Authors: Y Vasa, SR Mallreddy
    Year: 2022
    Cited by: –
    Citation: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal 13645-13652 🧬💻
  • Title: Develop Explainable AI (XAI) Solutions For Data Engineers
    Authors: Y Vasa
    Year: 2021
    Cited by: –
    Citation: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal 425-432 📊✨
  • Title: REVOLUTIONIZING DEVOPS WITH QUANTUM COMPUTING: ACCELERATING CI/CD PIPELINES THROUGH ADVANCED COMPUTATIONAL TECHNIQUES
    Authors: PM Katikireddi, Y Vasa, P Singirikonda
    Year: 2021
    Cited by: –
    Citation: Innovative Research Thoughts 7 (2), 97-103 🚀⚛️
  • Title: Develop Solutions To Detect And Mitigate Data Quality Issues In ML Models
    Authors: P Singirikonda, S Jaini, Y Vasa
    Year: 2021
    Cited by: –
    Citation: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal 16968-16973 📉🔍
  • Title: Design Scalable Data Pipelines For AI Applications
    Authors: Y Vasa, S Jaini, P Singirikonda
    Year: 2021
    Cited by: –
    Citation: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal 215-221 🔄🛠️
  • Title: Deep Learning Models For Fraud Detection In Modernized Banking Systems: Cloud Computing Paradigm
    Authors: Y Vasa, SKM Cheemakurthi, NB Kilaru
    Year: –
    Cited by: –
    Citation: Articles 1–12 💳🔍
Yeshwanth Vasa | Information Technology | Excellence in Innovation

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