Julio C. Villalta III

- Architected Web Monitoring workflow, with focus on performance, scalability and high availability
- Evaluated numerous tools and integrated in the monitoring workflow
- Developed patterns for provisioning infrastructure and application delivery using Terraform, Kubernetes , ArgoCD, GCP, and various third party solutions deployed into k8s

Enhancement of QA process of content published in proprietary content authoring tool. As part of the engagement, Julio made created enhancements to UI, added custom workflows, designed APIs, and provided a framework for unit testing to improvement development process. Technology stack included .NET Framework Standard, Vanilla JS, Kendo UI, SQL Server

Julio led platform security architecture at DAIS, providing various components to implement multitenancy and enforce authorization decisions. Solutions were capable of controlling access at the endpoint, method and row level, using a combination of vanilla Java, Spring Security, and Spring Data. Julio has experience integrating with services like AWS Cognito, Axiomatics Policy Server, WSO2 and Firebase.

Participated in the development of a Docker workshop.

Technology stacks included: Java, Gradle, Spring Data, Docker, Angular 2

• Develop Docker image to create a containerized Angular 2 development and testing environment.
• Develop Angular 2 application to serve as a client for a containerized RESTful API

Contributed to the development of a multi-faceted learning system; Contributions were in multiple applications, using a wide array of frameworks.

Technology stacks included: Java 8, Groovy, Gradle, Spring Data, Hibernate, JPA, PostgreSQL, Redis, AWS S3, Netflix Feign, Angular (1), Grunt, Node Express, Backbone, Jade, jQuery, Selenium, Spock, Docker

• Designed and developed content tool suite to extract, validate, and transform application content from various sources, including… Show more

Contributed to the development of a multi-faceted learning system; Contributions were in multiple applications, using a wide array of frameworks.

Technology stacks included: Java 8, Groovy, Gradle, Spring Data, Hibernate, JPA, PostgreSQL, Redis, AWS S3, Netflix Feign, Angular (1), Grunt, Node Express, Backbone, Jade, jQuery, Selenium, Spock, Docker

• Designed and developed content tool suite to extract, validate, and transform application content from various sources, including JSON, XML, and proprietary RESTful APIs. Identified edge cases for validation and lead integration test development. Additionally, developed a content deployment service and a user interface to invoke the tools and report job statuses and errors.
• Collaborated on a proprietary authoring application for interactive content, as well as and end-to-end testing suite for the application.
• Contributed to the development, maintenance, and deployment of various microservices, along with database design.
Show less

Human islet transplantation is a novel treatment modality for type I diabetes mellitus, designed to reduce patients’ dependence on external insulin administration. Because pancreatic islets contain insulin-secreting beta cells, these islets are extracted from a donor pancreas and injected into a patient to restore production of insulin. In order for islet transplants to be successful, the technique requires assessment of the critical amount of islet mass in a sample, which is measured in units… Show more

Human islet transplantation is a novel treatment modality for type I diabetes mellitus, designed to reduce patients’ dependence on external insulin administration. Because pancreatic islets contain insulin-secreting beta cells, these islets are extracted from a donor pancreas and injected into a patient to restore production of insulin. In order for islet transplants to be successful, the technique requires assessment of the critical amount of islet mass in a sample, which is measured in units of islet equivalents. However, the current method of assessing the islet equivalents in a sample is to manually count islets and their sizes under a microscope, with subjective results that are not consistent between researchers.

As a solution, our team proposed a smartphone-based method for assessing the total islet equivalents of a sample, by estimating the number and sizes of islets flowing through a microfluidic device. To this end, we have created a product with two components.

The first is a physical frame designed as a platform for brightfield microscopy to interface with a smartphone in order to capture a magnified video of islets flowing through a microfluidic channel. The second is a software tool written using the OpenCV library to track islet motion in the recorded video, estimate the number and diameters of islets, and ultimately calculate the number of islet equivalents in the sample. Together, these hardware and software components may be able to provide a tool to automate and facilitate the assessment of samples for human islet transplantation. Show less