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Welcome!

I'm Jatin Kulkarni, a Computer Science graduate from the University of Texas at Austin, where I specialized in Machine Learning and Artificial Intelligence. I'm currently advancing my journey at Cornell Tech in New York City, pursuing a Master of Engineering in Computer Science. Here, you can explore my projects, read about my experiences, and discover what fuels my passion for technology.

About Me

Hello! I'm Jatin, and I've always been captivated by the potential of technology to tackle complex problems and create meaningful impact. My academic journey began at the University of Texas at Austin, where I immersed myself in Machine Learning and AI, driven by a curiosity about how algorithms can learn from and adapt to the world around us.

In addition to my major, I pursued minors in Business Entrepreneurship and Design Strategies, which provided me with a unique combination of technical expertise and creative problem-solving skills. My education extended beyond just understanding technology—it was about learning how to innovate responsibly and ethically in a rapidly evolving field.

My passion for AI deepened through hands-on projects and internships where I applied my knowledge to real-world challenges. Whether enhancing software quality with advanced machine learning models at Aristocrat Gaming or implementing cloud security protocols at Kellogg Brown and Root, each experience has been a stepping stone towards a more profound understanding of AI's potential and its broader implications.

I'm now excited to continue my educational journey at Cornell Tech, where I aim to not only refine my technical skills but also explore how emerging technologies can be leveraged to drive positive change. On this personal website, I share insights from my journey, showcase the projects that have shaped my path, and offer my thoughts on the future of technology.

Experience

Aristocrat Labs

AI Research & Development Intern

January 2024 – July 2024


  • Spearheaded the development of advanced machine learning models for test case generation and analysis to optimize unit testing processes and identify patterns in flaky tests.
  • Led a comprehensive research initiative on defect prediction and root cause analysis using data analysis techniques to enhance software quality proactively.
  • Integrated Retrieval-Augmented Generation (RAG) techniques to build sophisticated internal tooling for quality assurance, improving the relevance and accuracy of automated test cases.

Technology Rotational Intern

May 2023 – August 2023


  • Configured Cloud Security Protocols in Azure Active Directory and AWS Identity and Access Manager for new projects and team members.
  • Implemented Azure AI Search (Azure Cognitive Search) to enhance the company's document management system by automating document indexing and retrieval.
  • Performed data analysis on over 600,000 tickets to locate trends and improve the efficiency of the Information Technology department.

Kellogg Brown and Root

Responsible Artificial Intelligence Institute

Software Engineering Intern

January 2022 – December 2022


  • Assisted in the design and planning of the third version of the RAI Collab, updating the technical stack to increase web traffic capacity by 100% and save 20 hours per week on maintenance.
  • Expedited the timeline of the RAI Collab Portal by re-engineering the front-end UX/UI development and creating several tools used in the portal.
  • Developed the AI Regulatory Tracker Web Application using React and Google Firebase, tracking over 170 AI-related regulations globally.

Undergraduate Researcher

August 2021 – December 2021


  • Conducted a detailed study on human-robot interactions, focusing on the perceived safety of subjects when walking past a Boston Dynamics robot, Spot, in different conditions.
  • Utilized ROS programming and RVIZ to create SLAM maps of test environments, enhancing the accuracy of robot navigation and subject monitoring during experiments.
  • Implemented Azure Kinect and TF Echo in the programming of Spot to detect and track human positions in real-time, ensuring safe interactions at speeds up to 5 mph.
  • Analyzed qualitative data from surveys to assess variations in human comfort levels with and without visible robot constraints, contributing to research on improving robot design for public safety.

Undergraduate Research: Autonomous Robotics

Projects

Blog Posts

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Contact Information

Email: contact@jatinkulkarni.com

Location: New York City, NY 10044

Phone: (832) 623-2238

LinkedIn: Jatin Kulkarni

GitHub: jatinkulkarni