Our Team

The DARC (Data, Analytics & Research Computing) team at the GSB Research Hub provides a wide array of research support services, including:
  • data management
  • code optimization
  • cloud computing
  • analytics support
  • data processing
  • ...and more!

Are you a GSB researcher with a specific request for support?  Fill out this form!

Email: gsb_darcresearch@stanford.edu





Amy Ng
awn@stanford.edu
Amy holds a Masters degree in Electrical Engineering and Computer Science from MIT.  Prior to joining the CIRCLE Research Support Team, Amy has served in a variety of roles at Google from its early days -- including quantitative marketing, user experience research, and social analytics.  She spends her time now looking at geospatial data using Quantum GIS, tinkering with API's, and figuring out zTree to conduct economic experiments. 

Alex Storer
Alex studied Computer Science and Cognitive Science, and has a PhD in Computational Neuroscience.  He works regularly in Python, R and Matlab, and has experience in a wide array of other languages, as well.  His strengths include signal processing, screen scraping, data munging and machine learning.
More: GitHubTwitter

       
Wonhee Lee
wolee@stanford.edu
Wonhee Lee has a Master's degree in Educational Psychology from the University of Colorado, Denver. She manages the private data collection and external resource management practices. Prior to joining the Research Support Service team, she led a social psychological research project in Stanford's Psychology Department. She is experienced in conducting program evaluation and experimental research. She enjoys cooking and sharing good food with friends and family.

       

Mason Jiang

mpjiang@stanford.edu
Mason studied X-ray and materials physics while earning his PhD in Physics from Stanford University. He has extensive experience designing and conducting experimental research projects and analyzing/interpreting results in both MATLAB and Python. On the side, he enjoys camping and hiking, especially in California.

https://sites.google.com/a/stanford.edu/rcpedia/the-team/wrmhs.png
W. Ross Morrow
wrossmorrow@stanford.edu
Ross is a mathematical modeler and analyst with over ten years of experience with optimization (linear and nonlinear programming), game theoretic modeling, statistical and machine learning techniques, and programming for high-performance computing. He has a PhD, MS, and BS in Mechanical Engineering and a MS in Applied Mathematics, all from the University of Michigan, Ann Arbor. Ross has also previously worked at Michigan, MIT, Harvard, Iowa State University, and Ford Motor Company's Palo Alto Research and Innovation Center. 
More: wrossmorrow.comweb.stanford.edu/~morrowwrGitHub, LinkedIn
   
   
 
Sal Mancuso
smancuso@stanford.edu
Sal received his degrees in Corporate Finance and Economics. Sal's various roles have afforded him the opportunity to work with researchers in multiple disciplines on tasks such as computing, data harvesting, data processing, data visualizations, application/script development and full-stack engineering. Tools Sal prefers to utilize for research analytics include Python, SQL, Tableau, D3 and Amazon Web Services (EC2, S3, etc.).  Previous to joining Stanford University, Sal worked for Tivo, Apple and Sun Microsystems. In his free time, Sal enjoys time with his wife and kids, hiking, motorcycle riding, biking, camping and tinkering all things Raspberry Pi or Arduino.
More: LinkedIn, Github, Twitter 
   
   
Brian Chivers
bchivers@stanford.edu
Brian received his master's degree in Data Science from the University of San Francisco.  Prior to joining the DARC team, Brian held roles as a technical analyst and developer in the Investments department at Nationwide Insurance.  Brian's interest and expertise lie in machine learning and processing of large data.  In his free time, Brian likes hiking, skiing, and exploring all that the Bay Area has to offer.
 
Ferdi Evalle
fevalle@stanford.edu
Ferdi has a long history working in the pharmaceutical industry in Roche and Genentech developing solutions for researchers from basic research to clinical trials to genetic experiments and everything else in between. Ferdi likes to be rounded in technology and has worked in the realms of database programming, statistical programming, full stack web development and Big Data. He likes learning and tinkering with different technologies. Current interests are Amazon Web Services, Unix Administration and Machine Learning. Ferdi enjoys time with his wife and daughter and the occasional video game.

 
Jason Ponce
jbponce@stanford.edu
Jason is an interaction researcher with extensive experience developing novel software and hardware platforms for both research and the arts. He has expertise in realtime data analysis, signal processing, computer vision, and machine learning. With DARC Jason works on Big Data engineering, research computing technologies, and cloud infrastructure. In a parallel life Jason is an experienced alpinist, and an award-winning composer and multimedia artist.