Design Thinking for Data Science Problems | Sita Syal
About This Video
Sita Syal, Ph.D. Candidate of Mechanical Engineering at Stanford University hosts a workshop on ‘Design Thinking for Data Science Problems’.
In This Video
Ph.D. Candidate in Mechanical Engineering, Stanford University
Sita Syal is a PhD student in mechanical engineering and design at Stanford. Her research focuses on quantitatively modeling the uncertainty of humans in renewable energy systems. She is interested in how human uncertainty can be mathematically modeled and how that uncertainty influences engineering design outcomes of large solar and wind projects. Sita is a National Science Foundation Graduate Fellow. Sita grew up in Michigan and completed a B.S.E. in chemical engineering and an M.Eng in energy systems engineering, both from the University of Michigan, Ann Arbor. She was awarded a Morris K. Udall scholarship in 2012 for her work in sustainability and clean energy.