Charles Edison Tripp (Preferred)
Charles Tripp
Charles E Tripp
Charles Edison Tripp
Researcher, National Renewable Energy Laboratory
Joined
June 2022
Names
,
,
Emails
****@nrel.gov (Confirmed)
Personal Links
Career & Education History
Researcher
National Renewable Energy Laboratory (nrel.gov)
2019 – Present
CTO
Terrain Data, Inc (terraindata.com)
2013 – 2018
Software Engineer
Zazzle, Inc (zazzle.com)
2011 – 2013
PhD student
Stanford University (stanford.edu)
2008 – 2013
Chief Algorithms Engineer
Foodily, Inc (foodily.com)
2009 – 2011
Software Engineer
Predictify, Inc. (predictify.com)
2008 – 2009
MS student
Stanford University (stanford.edu)
2006 – 2008
Software Engineering Co-Op
International Business Machines (ibm.com)
2007 – 2007
VLSI Engineering Intern
Hewlett-Packard (hp.com)
2006 – 2006
Undergrad student
Rice University (rice.edu)
2002 – 2006
RF Engineering Intern
T-Mobile USA (t-mobile.com)
2005 – 2005
Advisors, Relations & Conflicts
Coauthor
Sarah Aguasvivas
2019 – Present
Coauthor
Christopher Farmer
2019 – Present
Coauthor
David Brandes
2019 – Present
Coauthor
Tricia Miller
2019 – Present
Coauthor
Adam Duerr
2019 – Present
Coauthor
Melissa Braham
2019 – Present
Coauthor
Shree Sowndarya
2019 – Present
Coauthor
Robert Paton
2019 – Present
Coauthor
Erotokritos Skordilis
2019 – Present
Coauthor
Todd Katzner
2019 – Present
Coauthor
Jeffrey Law
2019 – Present
Coauthor
Dmitry Duplyakin
2019 – Present
Coauthor
David Biagioni
2019 – Present
Coauthor
Darice Guittet
2019 – Present
Coauthor
Jennifer King
2019 – Present
Coauthor
Aaron Barker
2019 – Present
Coauthor
Lindy Williams
2019 – Present
Coauthor
Stanley Young
2019 – Present
Coauthor
Eric Bensen
2019 – Present
Coauthor
Yi Hou
2019 – Present
Coauthor
Mike Optis
2019 – Present
Coauthor
Matthew Moniot
2019 – Present
Coauthor
Xin Jin
2019 – Present
Coauthor
Xiangyu Zhang
2019 – Present
Coauthor
Benjamin Grossman-Ponemon
2014 – 2018
PhD Advisor
Ross Shachter
2008 – 2013
Expertise
Probabilistic Graphical Models
Present
Reinforcement Learning
Present
Decision Theory
Present
Decision Analysis
Present
Deep Learning
Present
Information Retrieval
Present
Bayesian Systems
Present
Derivative-Free Stochastic Optimization
Present
Reference Counting
Present