Synopsis:
The talk will explore Eigen Decomposition, PCA, Kernel PCA, Eigen Faces, t-SNE, UMAP, Manifold Learning, a taxonomy of dimensionality reduction techniques, and discuss how the speaker used them for some of his research experiments.
Speaker Profile:
Vishnu S. Pendyala, PhD is a faculty member in Applied Data Science and an Academic Senator at San Jose State University; current 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 two other edited books on machine learning and software development are available in major libraries in USA including the US Congress 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 in 1995. 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.
IEEE Computer Society, Silicon Valley Chapter
