Vishnu S. Pendyala

Vishnu S. Pendyala

Vishnu S. Pendyala, PhD is a faculty member in Applied Data Science and an Academic Senator at San Jose State University; chair of the IEEE Computer Society Santa Clara Valley chapter; and IEEE Computer Society Distinguished Contributor. During his recent 3-year term as an Association for Computing Machinery (ACM) Distinguished Speaker and before as an industry expert and researcher, he was invited to speak at 60+ engagements including conferences, faculty development programs, and other forums some of which are available on YouTube and IEEE.tv. He is a senior member of the IEEE and has over two decades of experience in the software industry in the Silicon Valley. His book, “Veracity of Big Data,” and some of his other edited books on machine learning and software development are available in major libraries in USA including those of the US Congress, MIT, Stanford University, and internationally. Dr. Pendyala taught a one-week course sponsored by the Government of India’s Ministry of Human Resource Development (MHRD), under the GIAN program in 2017, to Computer Science faculty from across the country and delivered the keynote in a similar program sponsored by All India Council for Technical Education (AICTE), Government of India in 2022. Dr. Pendyala recently served on a National Science Foundation (NSF) proposal review panel. He received the Ramanujan memorial gold medal and a shield for his college at the State Math Olympiad in Andhra Pradesh, India. He also played an active role in the Computer Society of India and was the Program Secretary for its annual national convention. He has served as an Area Governor with Toastmasters International and has received the Distinguished Toastmaster, Area Governor of the Year, and Silver Scribe awards.

Publications

Misinformation Containment Using NLP and Machine Learning: Why the Problem Is Still Unsolved
Vishnu S. Pendyala. © 2023. 16 pages.
Despite the increased attention and substantial research into it claiming outstanding successes, the problem of misinformation containment has only been growing in the recent...
Reconnoitering Generative Deep Learning Through Image Generation From Text
Vishnu S. Pendyala, VigneshKumar Thangarajan. © 2023. 19 pages.
A picture is worth a thousand words goes the well-known adage. Generating images from text understandably has many uses. In this chapter, the authors explore a state-of-the-art...
Machine Learning for Societal Improvement, Modernization, and Progress
Vishnu S. Pendyala. © 2022. 290 pages.
Learning has been fundamental to the growth and evolution of humanity and civilization. The same concepts of learning, applied to the tasks that machines can perform, are having...
Machine Learning for Ecological Sustainability: An Overview of Carbon Footprint Mitigation Strategies
Vishnu S. Pendyala, Saritha Podali. © 2022. 26 pages.
Among the most pressing issues in the world today is the impact of globalization and energy consumption on the environment. Despite the growing regulatory framework to prevent...
Prediction of Formation Conditions of Gas Hydrates Using Machine Learning and Genetic Programming
Anupama Kumari, Mukund Madhaw, Vishnu S. Pendyala. © 2022. 25 pages.
The formation of gas hydrates in the pipelines of oil, gas, chemical, and other industries has been a significant problem for many years because the formation of gas hydrates may...
Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities
Vishnu Pendyala. © 2020. 223 pages.
The development of software has expanded substantially in recent years. As these technologies continue to advance, well-known organizations have begun implementing these programs...
Evolution of Integration, Build, Test, and Release Engineering Into DevOps and to DevSecOps
Vishnu Pendyala. © 2020. 20 pages.
Software engineering operations in large organizations are primarily comprised of integrating code from multiple branches, building, testing the build, and releasing it. Agile...
Continuous Deployment Transitions at Scale
Laurie Williams, Kent Beck, Jeffrey Creasey, Andrew Glover, James Holman, Jez Humble, David McLaughlin, John Thomas Micco, Brendan Murphy, Jason A. Cox, Vishnu Pendyala, Steven Place, Zachary T. Pritchard, Chuck Rossi, Tony Savor, Michael Stumm, Chris Parnin. © 2020. 14 pages.
Predictable, rapid, and data-driven feature rollout; lightning-fast; and automated fix deployment are some of the benefits most large software organizations worldwide are...