Agus Sudjianto

Agus Sudjianto is a highly skilled inventor and patent holder based in Matthews, NC in the US. With a total of 18 patents to his name, Agus has made significant contributions to the world of natural language processing (NLP) and financial crime detection. His latest patents focus on NLP model robustness determination and network based features for financial crime detection. In the first patent, Agus has developed systems and methods to determine robustness information for an NLP model. This involves generating modified test data based on instances of test data and analyzing the output of the NLP model to determine instances of output changing modified test data. This information is then used to determine the robustness of the NLP model. In his second patent, Agus has developed an innovative approach to detect financial crime and fraud using machine learning models. The approach involves using both network and non-network features to train the predictive machine learning model. The network features are generated by applying financial entity risk vectors to a network model with representations of various types of networks. The graphical network features generated from these networks are then fed to the predictive model to generate a likelihood and/or prediction with respect to a financial crime. Agus has worked for some of the top financial institutions, including Wells Fargo Bank and Bank of America. Alongside his coworkers Jie Chen and Harsh Singhal, Agus has made significant contributions to these companies in the areas of risk management, data analytics, and machine learning. Overall, Agus Sudjianto is a highly skilled inventor and patent holder who has made significant contributions to the fields of NLP and financial crime detection. His innovative approaches and models have the potential to revolutionize the way we approach these areas and ensure greater accuracy and efficiency.