YouTube Shorts Consumption

Interpreter Mode (IM): A google assistant feature where users can converse with another individual from a different language via live translations. https://blog.google/products/assistant/interpreter-mode-brings-real-time-translation-your-phone/

• Designed and developed landscape mode for Interpreter Mode, which included decisions on trade‐offs, design decisions for different surfaces, and flag guarding.

• Led the launch and organized bug bashes for landscape mode.

• Collaborated with team members to design possible feature ideas for Interpreter Mode using LLMs.

Dual Screen Interpreter Mode: A revamped Interpreter mode experience on the Pixel Fold, which takes advantage of the concurrent triple screen setup to provide streamlined live translations between individuals. https://blog.google/products/pixel/feature-drop-fall-2023/

• Designed, developed and successfully launched the Dual Screen Interpreter Mode for the Pixel Fold.

• Led the design and launch of the inner screen for Dual Screen Interpreter Mode.

• Collaborated with cross-functional teams across different time-zones.

• Helped brainstorm and consult on the marketing demo. https://www.youtube.com/watch?v=veN7yMLhYVs&ab_channel=MadebyGoogle

• Awarded a patent.

Interpreter Mode Platform Migration: A major platform update for Interpreter Mode to improve quality.

• Led the design and development of a complex internal service end-to-end in order to decouple the handling of assistant query intents from language resolution.

• Helped teammates ramp up on the new service through design docs and meetings.

• Collaborated with different teams to sync development and launch timelines.

• Investigated and analyzed large scale data to find the root causes of approximately 18% missing migration traffic.

• Full-stack development experience using ReactJS, TypeScript, C#, Python, PostgreSQL, and BigQuery.

• Worked on feature end-to-end to reduce code technical debt and optimize HOS rulesets for the Drive app.

• Improved various features for the Drive app to streamline the experience for thousands of clients and efficiently meet ELD compliance.

• Identified high-priority issues for important clients and resolved them quickly with minimal supervision.

• Mentored new software developers.

• Authored two empirical software engineering research journals on large software distribution platforms.

• Developed and maintained large scale crawlers written in Python and PostgreSQL for mining software data.

• Sampled, cleaned and analyzed software data using statistical, machine learning and data mining techniques.

• Queried and visualized patterns of active modding communities with Python, R, and SQL.

• Built predictive models (e.g., logistic regression and random forest) with Python and R.

• Developed complex and robust modeling pipelines using various modeling strategies (e.g., feature selection) and statistical methods (e.g., ANOVA, cross-validation, and bootstrap sampling) to interpret models.

• Implemented natural language processing (NLP) pipelines using stemming, lemmatization, word-embeddings, sentiment analysis, and latent Dirichlet allocation (LDA).

• Built deep learning models (e.g., gated recurrent neural network) on Python using Keras and TensorFlow.

• Mentored 15 students in a 3rd-year Algorithms course (CMPE 365).