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Shankar Sankararaman

Data Science and Machine Learning

Shankar Sankararaman is a highly skilled professional with over a decade of experience in the field of data science and machine learning. His expertise includes predictive analytics, statistical modeling, probabilistic techniques, Bayesian methods, and risk and reliability analysis.

Shankar has a special focus on autonomous systems like UAVs and drones, where he applies machine learning for perception, prediction, and decision-making. He is a prolific researcher in stochastic methods, failure prediction, reliability estimation, uncertainty quantification, and Bayesian networks.

With a strong background in engineering applications across aerospace, mechanical, civil, and electrical domains, Shankar holds a Ph.D. in Structural Engineering from Vanderbilt University. He has also studied Data Mining at Stanford University and Civil Engineering at the Indian Institute of Technology, Madras.

Throughout his career, Shankar has held various roles including Staff Data Scientist at Intuit, Senior Manager & Lead Data Scientist at PwC, Data Scientist at One Concern, and Research Engineer at NASA Ames Research Center. He has also been involved in academic roles as a Post-Doctoral Research Scholar, Research Assistant, and Teaching Assistant at Vanderbilt University.

Passionate about education, Shankar mentors students at high-school and middle-school levels, tutors students occasionally, and judges STEM-based competitions. He has published over 100 technical research papers in esteemed journals and conference proceedings.

His expertise covers data-mining techniques, regression methods, clustering methods, decision-trees, random forests, and boosting/bagging methods. Shankar Sankararaman's dedication to advancing STEM education and his extensive research contributions make him a valuable asset in the field of data science and beyond.

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Location

San Francisco Bay Area