Difference between revisions of "Fellow:Howard Brown"
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| − | [[File:HowardBrown.jpg|thumb|none | + | [[File:HowardBrown.jpg|thumb|none]]Howard Brown is an undergraduate student at Hampton University majoring in Computer Science with a minor in Mathematics. His research experience includes optical refrigeration of rare-earth doped solids, solid state laser development and spectroscopy, materials science, high performance computing and artificial intelligence. He spent a decade as a senior editor at a media outlet establishing and maintaining relationships with companies such as Microsoft, Sony, Nintendo and managed a team of writers across multiple entertainment industries. He has experience working at an NGO as well as mentoring high school students in nanoscience. Upon graduation he plans to pursue a PhD in computer science while creating a discipline-agnostic general form model for solving nonlinear problems across massive data sets. |
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[[Hampton University|Hampton University]] | [[Hampton University|Hampton University]] | ||
| − | [ | + | [[Hampton_University_Strategic_Plan|Hampton University Strategic Plan]] |
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| − | + | [[Category:Student Changemakers|Student_Changemakers]] | |
| − | [[Category:Student_Changemakers]] | ||
Revision as of 19:36, 8 April 2014
Howard Brown is an undergraduate student at Hampton University majoring in Computer Science with a minor in Mathematics. His research experience includes optical refrigeration of rare-earth doped solids, solid state laser development and spectroscopy, materials science, high performance computing and artificial intelligence. He spent a decade as a senior editor at a media outlet establishing and maintaining relationships with companies such as Microsoft, Sony, Nintendo and managed a team of writers across multiple entertainment industries. He has experience working at an NGO as well as mentoring high school students in nanoscience. Upon graduation he plans to pursue a PhD in computer science while creating a discipline-agnostic general form model for solving nonlinear problems across massive data sets.
