As a member of the JSC Safety and Mission Assurance Team, I develop and implement research objectives focused on the promotion of a healthy knowledge sharing environment for enhanced knowledge and quality management by:• Consulting clients on recommend programming software, machine learning algorithms, and cloud services for completing anticipated projects.• Finding solutions to a variety of data-informed challenges, i.e. optimizing the allocation of knowledge-driven and learning-driven resources required for program, project, and mission success;• Leveraging data science skills in the areas of big data analytics, exploratory data analysis, natural language processing, recommender systems, machine learning, deep learning, artificial intelligence, time series analysis, geolocation mapping, and software development.

Involved in three collaborative projects:Database pipeline implementation for client research projects and recommendation system(s) development----- Building a cloud computational pipeline to store and manage project data for candidate recommendation system(s) implementations using Amazon Web Services.Modulation recognition of digital radio frequency signals using artificial and convolutional neural networks----- Developed a modulation recognition neural network for digital radio frequency signals in the Python programming language with the aid of undergraduate researchers.Intrusion detection system development using support vector machines on network traffic data----- Designed an intrusion detection algorithm using principal component analysis, k-medoids clustering, and support vector machines in the R programming language employing undergraduate students of various academic backgrounds.Internal Research and Design: - Supervise and instruct undergraduate researchers of various academic backgrounds on fundamental data analysis methods and machine learning algorithms. - Daily machine learning, artificial intelligence, exploratory data analysis, neural network, natural language processing, and database research aimed towards application to real-world client solutions, i.e. recommendation systems, machine translation, classification, and object recognition. - Additional task include development of local executable and web applications using the Python programming language for anticipated projects.

• Guided up to 30 students through weekly session reviews of course materials and R programming methods as related to Introductory Statistics and Bioscience courses.

• Aided in the development and packaging of the Bayesian Optimum Interval (BOIN) package in R, testing and analyzing simulated data.

• Performed analysis on Multiple Risk Factor Intervention Trial (MRFIT) data set, identifying potential causes of certain illness and studying how certain prevention methods effected a given ailment. The investigation was carried out using R and SAS programming. During this time, a protocol for a small population study involving the effects of music on participants' cognitive skills was developed in a group setting.

• Coordinated lesson plans and exercises relevant to student course material. • Challenged students in their understanding of the material by developing and implementing group activities. • Distributed and graded in-class quizzes to assess mastery of the concepts.