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Sricharan Poundarikapuram

age ~47

from Scottsdale, AZ

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Also known as:
  • Srichara Poundarikapuram
  • Sricharan Poundari
  • Poundarikapuram Sricharan
Phone and address:
2996 N 83Rd Pl, Scottsdale, AZ 85251
Related to:
Connected to:

Sricharan Poundarikapuram Phones & Addresses

  • 2996 N 83Rd Pl, Scottsdale, AZ 85251
  • Herndon, VA
  • Fairfax, VA
  • 1402 Regent St, Madison, WI 53711

Work

  • Company:
    Sap
    Mar 2019
  • Position:
    Director, data science

Education

  • Degree:
    Master of Science, Doctorates, Masters, Doctor of Philosophy
  • School / High School:
    University of Wisconsin - Madison
    1998 to 2006

Skills

Operations Research • R • Optimization • Algorithms • Simulations • Cplex • Linear Programming • Mathematical Modeling • Data Mining • Mathematical Programming • Matlab • Machine Learning • Sas • Business Intelligence • Statistics • Data Analysis • Combinatorial Optimization • Strategy • Integer Programming • Stochastic Optimization • Ampl • Research • Stochastic Programming • Nonlinear Optimization

Industries

Computer Software

Resumes

Sricharan Poundarikapuram Photo 1

Director, Data Science

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Location:
Phoenix, AZ
Industry:
Computer Software
Work:
Sap
Director, Data Science
Decisive Analytics Corporation Mar 2006 - Oct 2007
Senior Operations Research Analyst
University of Wisconsin-Madison Aug 1999 - Feb 2006
Research Scholar
Education:
University of Wisconsin - Madison 1998 - 2006
Master of Science, Doctorates, Masters, Doctor of Philosophy Indian Institute of Technology, Madras 1994 - 1998
Bachelors, Bachelor of Technology, Mechanical Engineering
Skills:
Operations Research
R
Optimization
Algorithms
Simulations
Cplex
Linear Programming
Mathematical Modeling
Data Mining
Mathematical Programming
Matlab
Machine Learning
Sas
Business Intelligence
Statistics
Data Analysis
Combinatorial Optimization
Strategy
Integer Programming
Stochastic Optimization
Ampl
Research
Stochastic Programming
Nonlinear Optimization

Us Patents

  • System And Method For Management Of Financial Products Portfolio Using Centralized Price And Performance Optimization Tool

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  • US Patent:
    20110071857, Mar 24, 2011
  • Filed:
    Sep 23, 2009
  • Appl. No.:
    12/565527
  • Inventors:
    Denis Malov - Scottsdale AZ, US
    Sricharan Poundarikapuram - Scottsdale AZ, US
  • Assignee:
    SAP AG - Walldorf
  • International Classification:
    G06Q 40/00
  • US Classification:
    705 4, 705 36 R
  • Abstract:
    A computer-implemented method controls commercial transactions involving a portfolio of financial products by conducting business operations related to commercial transactions between a bank and consumer involving purchase and utilization of the financial products, collecting transactional data related to the financial products, and providing a centralized modeling and optimization tool to predict customer response to changes in an attribute of a financial product under evaluation based on the transactional data and to optimize the variable of the financial product under evaluation. The modeling and optimization tool is configurable to evaluate the financial products in the portfolio under KPIs and business rules selected according to the financial product under evaluation. The optimized variable is transmitted to the bank. The movement and utilization of the financial products between the customer and bank is controlled in accordance with the predicted customer response to changes in the optimized variable of the financial product.

  • Managing Operations Of A System

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  • US Patent:
    20120254092, Oct 4, 2012
  • Filed:
    Mar 28, 2011
  • Appl. No.:
    13/073536
  • Inventors:
    Denis Malov - Scottsdale AZ, US
    Sricharan Poundarikapuram - Scottsdale AZ, US
  • Assignee:
    SAP AG - Walldorf
  • International Classification:
    G06N 5/02
  • US Classification:
    706 52
  • Abstract:
    A computer-implemented method for managing operations of a system includes deriving a nonlinear modeling function from a nonlinear response function, defining an allowed range for output values of the nonlinear modeling function, determining a range of a first set of input values of the nonlinear modeling function based on the allowed range of the output values, deriving a nonlinear probability function from the nonlinear response function, receiving the first set of input values, calculating the output values by processing each input value in the first set of input values through the nonlinear modeling function, determining, using the probability function, a relative probability of performing a first future system operation for each input value of the first set of input values and displaying, for each input value in the first set of input values, the corresponding output value and the corresponding probability.
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