Java Developer & React Developer

The candidate is a Software Engineer with experience in developing intelligent features for Google Workspace Editors. They have a strong educational background with a dual degree in Computer Science and Engineering. The candidate has also worked on research projects related to natural language processing and has publications and patents in the field. They are skilled in frontend tools and technologies and have experience guiding junior engineers on programming tasks.

Dec 2022 - Present As a Software Engineer, I am currently working on Keep, a notetaking editor in Google Workspace. My responsibilities include developing intelligent features for Google Workspace Editors using my expertise in client-side software and natural language processing infrastructure. I also work on technical designs for end-to-end problems, collaborate with other teams, and guide junior engineers.

Aug 2020 - Nov 2022 In my role as a Software Engineer, I developed intelligent features for Google Workspace Editors, such as spellcheck in encrypted documents and writing style suggestions. I used cutting-edge frontend tools and internal technologies to enhance user-facing features. I also formulated technical designs, resolved technical debt, and guided junior engineers on programming tasks.

May 2019 - July 2019 During my internship, I worked on developing a user interface for the Google text auto-correction feature. I focused on the client-side software infrastructure and implemented control options for users to undo or provide feedback on corrections.

May 2018 - July 2018 As a Research Intern, I developed a mobile application for Text to Scene Conversion in Augmented Reality. This involved using novel research techniques for predicting three-dimensional object sizes and positions from textual features.

Sep 2019 - May 2020 For my Master's Thesis, I worked on paraphrase generation using a bilingual model and continuous embeddings. I developed a novel technique using the von Mises-Fisher Loss on a transformer network to produce superior paraphrases compared to existing models.

May 2017 - July 2017 As a Research Intern, I developed a cognitive text parser for processing textual data into cognitive structural representations. This work aimed to extract cognitive features for downstream NLP tasks and demonstrated correlations with semantic and syntactic text features.