George H. John (PhD)
                           Redwood City, CA
                    george_john@stanfordalumni.org
                            (650) 315-4943

Employment:
E.piphany, San Mateo, CA
9/97 -- 5/02
Sales Manager, Strategic Accounts; Principal Sales Consultant; Product
Manager; Engineering Director.

Joined E.piphany as employee #13 and helped the company grow annual
sales from $0 to $127M in three years.  Sales wins included many
firsts for the company: Wells Fargo (first bank), Amazon.com (first
dot-com), AOLTimeWarner (largest database), and Applied Materials
(largest deal size).  

As Engineering Director, led the team that developed E.piphany's
revolutionary analysis functionality, creating the first commercial
software package to truly integrate data mining algorithms and
relational databases, with a web-based user interface that marketers
could understand, ultimately placing E.piphany as one of two leaders
on Gartner's "Analytics" magic quadrant market analysis.  

As Product Manager, analyzed usage and ROI and helped launch the E.4
product suite.  Led on-campus recruiting at Stanford, recruited award-
winning PhD graduate, top MBA student, and top undergradute engineers.
At the time of the IPO, had recruited one out of every five 
employees.

IBM Almaden Research Center, San Jose, CA
6/95 -- 9/97
Senior Sales Specialist/Senior Data Mining Analyst.  Responsible for
customer data-mining engagements in banking, instructing classes on
data mining, making presentations to prospective customers, and
technical marketing.  Recruited a team of eight PhD's to fill out the
team.

Lockheed AI Center, Palo Alto, CA
6/94 -- 6/95
Research Scientist, Data Comprehension Group.  Developed a neural
network package in C for use in a data-mining system.  Analyzed large
databases of stock market data and retail consumer purchasing data.

Previous employment includes two summers at the NASA Ames AI Lab
working on neural networks and agents, and two summers with small
startup companies in Dallas, TX, working on network optimization,
financial modeling, and marketing database development.


Education:
PhD with Distinction in Teaching, Stanford University
9/92 -- 4/97 
Coursework and research focuses on data mining.  Thesis committee:
Usama Fayyad, Jerry Friedman, Pat Langley, Nils Nilsson (Principal
Advisor).

BS & MS, Stanford University
9/88 -- 6/91 (BS), 4/95 (MS)
MS GPA: 4.0  Major: Computer Science, AI Specialization.  BS GPA: 3.7 
Major: Computer Science.  GRE: 740V  800Q  800A.  SAT:  780V  780M.  



Select Publications: (many more available from WWW page given above)

George H. John.  Enhancements to the Data Mining Process.  PhD Thesis,
Computer Science Department, Stanford University.  March, 1997.

George H. John and Pat Langley. Estimating Continuous Distributions in
Bayesian Classifiers.  In _Eleventh Annual Conference on Uncertainty in
Artificial Intelligence_, 1995. Morgan Kaufmann Publishers.

George H. John and Peter Miller.  Building Long/Short Portfolios using
Rule Induction.  In _Computational Intelligence in Financial
Engineering_, 1996.  Manhattan, NY.  IEEE Press.


Advisory Boards:

i-Loft,Inc. (2000-present)
Work with CEO on corporate development, sales, and product direction. 

Enviz, Inc. (2001-present)
Work with CEO on corporate development, engineering staff on product
direction.

Intelligent Results, Inc. (2002-present)


Professional Activities:

Press: Interviewed by CNET ("Data Mining: Digging user info for gold,"
2001) and Washington Post ("Data Mining Developments Gain Attention",
1997).

National Science Foundation: panelist, reviewed grant proposals, 
influenced the investment of tens of millions in data mining research.

Panel Discussions: Organized "Data Mining Startups" (2001) and "Behind
the Scenes Data Mining" at upKnowledge Discovery and Data Mining,
DBExpo 1997, Data Warehousing Institute 1997.

Invited Talks: "How to Succeed in Data Mining without Really Trying"
and "Data Mining vs Statistics," Data Warehousing Institute, August
1997.  "Towards Quantitative and Computational Business Processes with
Data Mining," NYU Stern School of Business, March 1997.  "Data Mining
in the Real World," Carnegie Mellon University, May 1998, 
University of Toronto, June 1997, and Stanford University, March 1997.

Journal Reviewing: Data Mining and Knowledge Discovery, Machine Learning, 
Decision Support Systems, Journal of Artificial Intelligence Research,
IEEE Transactions on Pattern Analysis and Machine Intelligence.

Conferences: Knowledge Discovery and Data Mining Program Committee
(1998-2001), Organizing Committee (2001), Machine Learning (1998).

Teaching: (All courses were taught at Stanford) Instructor for
"Introduction to Artificial Intelligence," Teaching assistant for
"Machine Learning," Instructor for "Data Structures and Algorithms,"
TA for "Compilers," Instructor and TA for various programming courses.

Honors & Societies:
National Science Foundation Graduate Research Fellow, Tau Beta Pi,
National Merit Scholar, Most Likely to Succeed Award (5th Grade), ACM
member.