Data Scientist and Quantitative Analyst @ Quality of ads, ads products, and presentation formats - Design of random-user experiments - Definition and characterization of metrics to evaluate experiments - Large-scale data analysis for statistical inference and hypothesis testing - Statistical modeling and estimation of experimental effects with regression techniques - Reports and presentations to engineering, product, and management groups Detection and removal of abuse/fraud in ads interactions - Large-scale data forensics to reliably identify anomalous groups, in an ads eco-system characterized by extreme diversity and complexity - Metrics to infer validity of traffic from advertisers’ accrued value - Methods and measures to estimate degree of anomaly of signal distributions, under conditions of heterogeneity and sparsity - Implementation of the above in active, operational systems From 2007 to Present (8 years)

PhD, Physics @ University of Illinois at Urbana-Champaign From 2001 to 2007 MS, Physics @ Virginia Polytechnic Institute and State University From 1999 to 2001 MS, Industrial & Systems Engineering @ Virginia Polytechnic Institute and State University From 1995 to 1997 V Akkineni is skilled in: C++, Algorithms, Distributed Systems, Machine Learning, Software Engineering, Java, Data Mining, Scala, R, Matlab, Mathematica, Statistics, Applied Mathematics, Numerical Analysis