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Four Days
in Michigan

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buy the acclaimed novel by Philip Zazove
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(all sale proceeds go to LTZF)

Scholarship Recipients

Daniel Daniel graduated from UC Berkeley with a B.S. in Electrical Engineering and Computer Science, with emphasis in the latter major this past May. He will start working in October 2016 at a Boston startup called Celect, led by two computer science professors at MIT. The company uses machine learning to help retailers increase their profits. It is his first job out of college and he is looking forward to working at the startup.

Daniel grew up in small town California. He's been incredibly successful in both in high school and college, winning multiple awards from Berkeley and in various robotics competitions in high school. Dan had a 4.43 GPA in high school, and scored a 5 on three AP exams. He has done well in college too, with a 3.6 GPA despite taking rigorous engineering courses. Daniel's passion is robotics, and he has served as the president of the UC Berkeley robotics club.

Dan has been involved in other activities besides robotics. He was in the math club, which has informed his robotics work, as well as winning the San Francisco Library Living Green statewide essay contest in high school. His letters of recommendation contain wonderful comments such as "Daniel is an extraordinary young man...he will make a engineering a solution to...problems."

Daniel is starting his fourth and final year at University of California, Berkeley. He is majoring in computer technology and plans to find a job in that area, hopefully one that will allow him to write programs "that help people." During the summer of 2015 he did a fellowship at the University of Michigan where he wrote programs to help hearing loss researchers analyze signals from the auditory nerve. In past summers, he interned at Lawrence Berkeley Laboratory (LBL) and worked on lithium-ion battery research and more recently on database design, with the aim of designing and populating a database flexible enough to store different types of building energy usage data in a consistent format that allows one to easily analyze the data.