Benjamin Diaz Email and Phone Number

• Configured script utilizing the Selenium package in Python to scrape the web for Institutional Research, Effectiveness, Assessment, and Program Review documents and policies from our peer and aspirant institutions. This approach created great efficiency for the office's periodic benchmarking activities and resource-sharing with Program Chairs• Wrote machine learning code for predicting student retention (including but not limited to Gradient Boosting, Support Vector Machines, Regression Analysis, Random Forests, Principal Component Analysis along with checks for Multicollinearity, Overfitting/Underfitting, using accuracy/recall, F-scores, AUC/ROC analysis, and validation performed via 2-10-fold Cross Validation• Ran exhaustive statistical analysis such as binary logistic regression, chi-square, ANOVA, finding probability values and effect size (Cohen’s d, eta2), presenting descriptive/ summary statistics, building correlation matrices, conducting sentiment analysis, and binary logistic regression within the context of academic program assessment.• Participated in the development of an ETL process: data mapping, SQL querying for development of a Snowflake Schema for our newly developing Data Mart. • Created Tableau stories / visualizations from IPEDS (Integrated Postsecondary Education Data System) and NSSE (National Survey of Student Engagement)• Ran descriptive statistics and visualizations in R (word clouds, sentiment analysis)• Supervised the reorganization of program review data for department chairs and college deans, and trained faculty in the use of interactive data visualizations and integration of indirect assessment evidence into self-studies.• Generated Cognos 11 reports via accessing our ODS• Wrote an internal document for using Excel in the context of program review (developing graphs, using formulae, filtering and analyzing data)• Consulted with faculty and staff on research design, R and SPSS functions on an ad-hoc basis

• Worked on developing a method of automating drone paths using robot localization, dronekit-python: a software development kit specifically for drones on MAVLink• Configured script utilizing the Selenium package in Python to scrape the web for images to train custom data for object detector• AWS for cloud computing on EC2 instances, storing scripts in S3 buckets, configuring along the ECR, and deployment with EKS• Developed a web-based object detector in Flask (Python) with an HTML front-end • Containerized code in Docker and deployment in Kubernetes locally with Minikube

• Configured object detection files using faster-RCNN (Region Convolutional Neural Network) in Python• Detected text using (Connectionist Text Proposal Network) CTPN from Tensorflow model zoo• Parsed through financial data, cleaned data with pandas, and built 2D hierarchical clusters along attributes of the data using scikit-learn• Used VMware (Ubuntu) extensively for coding and machine learning purposes• Briefly used Django in Python to configure a minimally viable product for a bartering app• Configured Kubeflow UI within GCP and queried data via BigQuery

Worked extensively on a project which solved coupled differential equations which model neutron stars. The project centered around solving for the boundaries of the stars, which are needed in the physics of oscillations--which are necessary for finding gravitational waves.

Coordinated labs of 24, providing support to students in basic circuitry, python programming, and experimentation. Provided assessments of lab reports, and holding weekly office hours.

Working with students to meet their educational needs in calculus, essay writing, communication skills, creative writing, geometry, physics, history, and general science.

I worked as an undergraduate learning assistant for the department of Physics, where I helped a graduate student in a lab to provide insight for labs and sample problems, as well as worked in a tutoring centre for an hour a week providing homework and exam help to students in need.