Sep 2022 – May 2023 · 8 mos · Dublin, County Dublin, Ireland · Hybrid

• Developed BIDS compatible Continous Event Neural Data structure for storing and sharing neuroimaging data in the field of Natural Sensory Perception as part of the Cognition and Natural Sensory Processing Initiative (CNSP) which combines the benefits of both the Brain Imaging Data Structure (BIDS) and the Continuous Event Neural Data (CND) structure. Also created the bids_cnd library, which offers researchers a suite of tools to convert existing CND datasets to the BIDS-CND format and load the BIDS-CND dataset into their preferred analysis environments (MATLAB or Python).

Jun 2022 – Aug 2022 · 2 mos · Dublin, County Dublin, Ireland · Hybrid

• Completed a 3-month Software Engineering Internship at Microsoft, working on expanding the types of available monitors for the Microsoft in-house Diagnostic and Health tool service in OMEX (Office Modernisation Experience) for APIs and services in action. My project included the development of Zero Traffic and Traffic Pattern Recognition monitors. As a software engineering intern, I had the opportunity to work on a real-world project and gain valuable experience in the industry.

Jan 2022 – May 2022 · 4 mos · Dublin, County Dublin, Ireland · Remote

• As Team Lead and Co. Back-End Lead, I led a team of 7 students to deliver a system that supported lecture dictation and natural language querying of a knowledge corpus. We utilized IBM Watson Discovery and IBM speech-to-text to develop the system. This project was nominated for Outstanding Software Engineering Project of the year 2022 at Trinity College Dublin. I was responsible for the technical direction of the project, as well as mentoring and motivating the team to achieve the project goals. My role included coordinating with the other leads and stakeholders to ensure the smooth delivery of the project.

Jan 2021 – May 2021 · 4 mos · Dublin, County Dublin, Ireland · On-site

• As a Developer for the research project "Do AI models learn better if they see more classes?", I worked in a team of 6 students under the guidance of Dr. Mohommed Al-Rawi. Our goal was to test the hypothesis that "AI models learn better if they see more classes". To do this, we tested generally available CNN models on CIFAR datasets and found that the hypothesis was true. My role as a developer involved implementing and testing the models, analyzing the results, and contributing to the team's research efforts

Jan 2019 – Jan 2019 · 0 mo · Geneva, Switzerland

• As a delegate of Austria at the Fermun committee on AI and ethics, I had the opportunity to participate in important discussions on the responsible use of AI. As part of the first Indian delegation to represent a country at an international level at this event, I was honored to contribute to the conversation on how to ensure that AI is used ethically, particularly in relation to the military. I worked to pass resolutions that promoted transparency, accountability, and the protection of human rights in the development and deployment of AI technology. It was a valuable experience to be a part of shaping the future of AI in a responsible manner.