Jignasu Pathak

Experience

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  Mifa Systems

  May 2019 - Jun 2019

  Project Intern

  We cleaned and organized huge data using various tools such as pandas, MYSQL, and excel to analyze feedback from the zig circuit. Strategized data acquisition software for remote fault detection operation in collaboration with software engineers. Designed the whole system to provide better visual components. Introduced safety switches and two feedback sensors to automate the process. Documented the entire project for future reference.

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  Virginia Tech - Pamplin College of Business

  Dec 2021 - Dec 2022

  Graduate Teaching Assistant

  • BIT: 4614 Information Security: I conducted lively and engaging discussions with 147 students,sharpening my communication skills and enabling me to convey complex technical concepts easily. I was also committed to staying up-to-date with the latest trends and technologies in the field, bringing valuable insights to the classroom and motivating students to explore the subject matter in greater depth.• BIT: 4424 Visualization Analytics: Explained advanced design principles and techniques for information visualization in tableau and D3.js in a class of 83 students. Show less

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  Amazon

  May 2022 - Aug 2022

  Software Development Engineer Intern

  • Built a React and AWS-based dashboard to quickly resolve deployment errors in IoT devices, resulting 30% decrease in response time.• Designed and implemented an end-to-end Continuous Integration/Continuous Deployment (CI/CD)pipeline for a full-stack website, using React for the front-end and AWS CloudFormation CDK to managethe back-end infrastructure.• Created REST APIs on AWS API Gateway and integrated it with AWS Lambda proxy to retrieveprocessed data from the AWS DynamoDB NoSQL database.• Utilized Git for version control and JIRA for project management within an Agile team of 10 engineers. Show less

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  Virginia Tech

  Jan 2023 - now

  Graduate Research Assistant - AI Assurance

  • AI Assurance: Designed, managed, and led a team to conduct a study comparing the effectiveness of various types of AI explanations on human-AI team outcomes, with a sample size of 30 human-AI teams.• Utilized statistical analysis and experimental design expertise to develop protocols, collect and analyze data, and synthesize information from reference papers.• Aimed to reduce over-trust and improve accuracy by developing effective explanations for human-AI teams.