Jeff Ouyang

Engaging in end-to-end pilot projects to utilize electrical grid data, analytics, and machine learning to improve grid infrastructure resilience and operational efficiencies. Developed machine learning enhanced Estimated Time of Restoration model for outages and deployed service line issue detection algorithm as an email alert system.

Ensured successful deployment of high performance neural network-based Falcon fraud detection models for bank clients using Agile development. Led custom fraud detection model development, conducted performance monitoring, and created data ingestion and ETL programs.

Collaborated with analytic teams to research and develop new analytic capabilities for a credit reporting agency serving the under-banked financial sector. Developed auto-loan default risk grading systems using manually balanced custom decision trees.

Conducted model attribute innovation, data science research, and provided technical/analytic consultations to internal/external clients in the consumer credit product space. Led machine learning feature engineering research and designed analytical pipelines using SAS and Python.

Conducted research to enhance predictive performance of consumer credit risk models and improve data analysis processes. Implemented a Genetic Algorithm-based variable selection technique and automated credit attributes mapping using Python.

Provided high school to college-level tutoring in mathematics, statistics, and Matlab programming. Developed customized teaching plans based on individual client needs.

Assisted Millisecond software in the development and implementation of psychometric tests. Reverse-engineered cognitive and psychometric testing algorithms from research papers and implemented them using XML-based coding in Inquisit software.

Engaged in business analytic and social science training through course work, seminars, and independent research. Developed knowledge of applied econometrics and gained experience in statistical programming using R, Stata, and SAS.

Collaborated with R&D team to verify imaging performance of new sensor designs and analyze non-functioning sensors. Developed Matlab programs and automated sensor imaging performance test programs in C++.

Performed technical and logistical engineering functions to support sensor development and production. Conducted software and hardware integration of imaging performance measuring hardware and developed automated test programs.

Engaged in research to determine the feasibility and implementation strategy for on-camera photography quality feedback features. Conducted technical survey of image processing and recognition algorithms and proposed technical solutions.

Devised a software-based image de-blurring solution for an optical targeting system used in high power X-ray diffraction equipment. Researched and implemented C program for image de-blurring and tested de-noising and segmentation methodologies.

Master of Science in Quantitative and Computational Finance from Georgia Institute of Technology, completed from 2012 to 2013.

Master of Science in Accounting and Information Management from Northwestern University, completed from 2008 to 2011.

Master of Engineering in Electrical and Computer Engineering from Cornell University, completed from 2003 to 2005.

Bachelor of Science in Electrical and Computer Engineering from Cornell University, completed from 1999 to 2003.