Research Scientist applying the latest Neural Network research to OphthalmologyBuilding Advanced Neural Networks to diagnose diseases, enroll patients in drug trials and enhance treatments for the eye.Past Projects and Presentations include:One of the first deployed Geographic Atrophy Segmentation AlgorithmsDiabetic Retinopathy ClassificationOCT 3D SegmentationIndependent Classification of 7 field Color Fundus PhotographsEnhancement of high resolution pictures to measure blood vessel diametersMeasurement of Geographic Atrophy via weak and strong labels

Course Lead and Instructor for Master's Level Natural Language Processing and Data Science Methods courses. Taught between 2-4 Sections per semester, developed and updated course content to be relevant for recent industry best practices.Updating official course content for 2020 course re-write, working with external vendor to build and record new asynchronous material for students.Final year project advisor for small groups (similar to thesis) in varied topics with results published in SMU Data Science Journal.

NLP Data Scientist and Data Engineer for Executive IT• Built Natural Language Processing model in tensorflow for use in a chatbot that served as a first line of contact for IT Support. Chatbot was gauged on metrics to ‘deflect’ or answer questions that would normally consume help desk manpower.• Built multiple dashboards for IT Inventory Management, IT Support Desk, and IT Executives to monitor critical items within the business space. Combined data into a consumable format, built out the front end of the dashboards to customer specifications, including drill-downs and filters. Recommend and chaired a weekly session to mentor junior developers and spread knowledge of our software (Tableau).• Led the team that is responsible for the data pipelines and monitoring for the next generation of our virtual assistant—moving from a chatbot to an integrated software assistant. Setup the data format, collection, and final storage for all data so that information could be relayed to dashboards automatically (Previously data was locked away and required extensive work to retrieve, even for basic analysis).• Established best practices for software development and guided team through multiple post-mortems to root out in efficient practices and establish a healthy culture of communication and standards. Worked with multiple first and second year employees to incorporate their unique knowledge and develop their skills to industry best practices.

Developed Natural Language Processing models using deep learning neural nets coded in python to enhance the consumer experience within Toyota Automobiles. Developed models within a continuous development, continuous integration environment using agile and scrum, while integrating state of the art machine learning algorithms into deployable software.Worked to deploy advanced Tensorflow models into production to facilitate voice commands (Similar to Amazon/Google personal assistants). Worked not only with machine liearning but also communications protocols such as gRPC as well as container environments such as kubernetes and docker.4 Patent Applications filed for work with machine learning and the automobile industry.

Starting July 2017 received temporary assignment as a Data Scientist to grow and develop opportunities within State Farm for its Data Science community. Outside of work had developed a Data Science skillset which facilitated selection for this opportunity. Completed continuing education courses in Machine Learning and Programming and competed in Data Science contents on Kaggle.com. Worked in python with an emphasis on Neural Nets/Deep Learning and Boosted Learning Algorithms (XGBoost). Familiar with a majority of basic machine learning tools including gradient descent, random forests, neural nets, cross-validation and support vector machines (SVM) .March 2015 to July 2017Individual contributor on projects to remediate internal audit findings. Projects included setting up data governance processes for Data Quality, Identifying Sensitive Data, and Database Access on both traditional relational database systems (RDBMS) and Hadoop (Cloudera Distribution). Extensive experience working on developing governance for Hadoop including work on Cloudera Navigator, Sentry, Hive, and Impala. Trained as Cloudera Administrator to understand Data Governance in Hadoop.Developed Software to download Audit Logs and Parse from JSON to CSV. Setup initial monitoring threshholds for user activity in Hadoop concerning users who access sensitive data, data retention protocols, and general user access..2015 Q4 Special Achievement Award

Led and expanded a team Data Quality Experts (5 direct reports, 1 onsite contractor, 2 offshore contractors) charged with ensuring data quality for the enterprise data warehouse at GM Financial--the captive lender for GM.Performed software test and evaluation for Data Quality software and provided recommendations to senior leadership.Successful audit review with 0 findings of all policies and procudures for Data Quality.

Data quality analyst for Teradata, Oracle, and Microsoft SQL servers for Capital One Auto Finance. Prioritized software defects as the internal Voice of Customer (VOC), Subject Matter expert for database content in Auto Finance. Work on multiple cross matrix projects such as data sharing between legal entities, evaluation of new software tools and submissions for oversight to the Federal Reserve.Performed used acceptance testing for roll out of division data warehouse. Optimized and streamlined the process approval for database changes across multiple platforms and rolled out those changes as value-added methods to other teams. Developed a systematic approach to classify and prioritize defects that was then adopted across multiple teams.Facilitated a transition of contracts from one vendor company to another vendor which was recognized internally with a monetary award for teamwork; all while maintaining 100% workload during transition.Was recognized as one of the top Subject Matter Experts (SMEs) for Data Warehouse, SQL, and Auto finance

•Research Engineer for III-V semiconductor processes. Major projects included researching and improving on-chip capacitor lifetime, extended the 3 layer interconnect process to 5 layer interconnects, and the introduction of GaN semiconductors to manufacturing processes.•Introduced new methodology (paired t-test) to group data and coded program to take data and analyze trends throughout the processing procedure. Became to R&D group expert for data analysis, statistics, and computers as well as a company-wide resource on statistical methods and interpretation. •Maintained Oracle database of R&D data and developed Unix Shell Scripts/C Programs for Extract Transform and Load (ETL) of raw data. Developed ETL in Labview for a direct Instrument-to-Database data connection, including developing ODBC code (from scratch, did not use NI's proprietary code modules due to license restrictions) to connect to Oracle via Labview.

•Metal Deposition Process Engineer for Tantalum (Ta), Copper (Cu), Titanium (Ti), Titanium Nitride (TiN), Cobalt (Co), Nickel (Ni) and Nickel Platinum (NiPt). Worked on both 300 mm and 200 mm AMAT Endura 5500 deposition systems that included Self-Ionized Plasma (SIP), Ionized Metal Plasma (IMP), Chemical Vapor Deposition (CVD), and standard Physical Vapor Deposition (PVD) chambers for advanced CMOS processing at 45 nm, 65 nm, 90 nm, and 130 nm nodes.

Spent 50% of time as Plasma Etch Process Engineer for Tungsten and Silicon Carbide reactive ion etch (RIE) process. Remaining 50% of duties were as an integration engineer for magnetic thin film read/write heads.Member of the integration team the produced the first line of a new technology (Current Perpendicular to Plan Giant Magnetoresistance) read heads for enterprise and consumer hard drives. Brought into manufacturing an Inductively Coupled Plasma RIE etch tool. Setup the manufacturing process. Wrote all specifications and setup all control charts. Personally trained sustaining personnel including engineers, technicians, and operators. Worked with R&D on tool purchase specifications and tool selection criteria.

•Development engineer (process and equipment) for metal deposition in the chip connect area for 90 nm and 65 nm CMOS technologies employing the “flip chip” or solder bump connections.•Led a team of 4 engineers and 8 shift technicians. Participated directly in technician performance reviews and career development. Chaired the chip connect area PVD process improvement team that included engineers from 3 sites (Oregon, New Mexico, Ireland) and equipment supplier. Led a small team looking into replacing electro-static chucks with more reliable and cost effective solution.

Researched Thin Magnetic Films for PhD thesis. Research was done on giant magnetoresistance (GMR) films with microfabricated superconducting contacts.Research included extremely sensitive voltage measurements near absolute zero (liquid helium temperatures). Measurements were performed with a SQUID feedback loop for pico-volt sensitivity. Researched and developed method to fabricate thin magnetic film stacks (Exchange Bias Spin Valves) with dimensions from 100 microns to the sub-micron (nanometer) critical dimension. Developed optical and e-beam lithography techniques to produce samples, including a combined alignment technique for microfabricated contacts and devices of different size. Published the first results of micron-sized area current measurements in a macroscopic film for GMR films (See Publications).Additional duties included PVD system maintenance, SQUID magnetometer maintenance, building measurement equipment for voltage measurements at 4.2 K, programming (via Labview) of a measurement system to automate the collection of magnetic resistance data, UHV system repair, Ion milling expert, and, LaTeX paper submission expert.