Machine Learning Computer Science

Jeet Patel

Ó +1-201-***-**** R ************@*****.***

Education

Courant Institute of Mathematical Sciences, New York University New York, NY Master of Science in Computer Science Expected: May 2026 Coursework: Programming Languages, Operating Systems, Machine Learning Indian Institute of Technology Guwahati Guwahati, India BTech in Electronics & Communication Engg.; GPA: 9.24/10 (Rank: 2/90) July 2018 – June 2022 Minor in Computer Science and Engineering

Coursework: Computer Networks, Data Structures and Algorithms, Computer Vision, NLP Technical Skills

• Frontend & Web: JavaScript/TypeScript, ReactJS, Redux, HTML, CSS, Django, Flask, Webpack

• Backend & Databases: Python, Java, NodeJS, REST APIs, Microservices, Redis, Amazon DynamoDB, SQL

• Misc.: C/C++, Docker, Kubernetes, Spark, AWS Lambda, Pandas, Linux, Jenkins, Git, New Relic, Splunk Experience

Software Development Engineer II June 2022 – August 2024 Adobe Inc. (Search & Discover Experiences) Noida, India

• Owned development of search UI components (dropdown & results page) for Adobe web platforms with 10M+ MAU

• Reduced frontend Webpack build size by 50% by optimizing tree shaking, lazy loading, and asset minification

• Refactored async code to remove unnecessary blocking API calls, reducing page load time by 70%

• Developed microservices and deployed RESTful APIs for topical ordering & app recommendation on backend server

• Spearheaded project for connecting online storage providers and built UI for browsing files within them

• Implemented Redis caching for top 1,000 queries, reducing average query response time by 80% and lowering DB load

• Built an LLM-based Retrieval-Augmented Generation (RAG) pipeline for a conversational assistant on Creative Cloud

• Set up New Relic monitoring & Splunk alerts, improving issue detection and enabling quick resolution

• Tech Stack: JavaScript/TypeScript, Python, C++, Java, Docker, Kubernetes, ReactJS, NodeJS, DynamoDB, SQL Research Intern May 2021 – July 2021

Adobe Research Bangalore, India

• Built CollabColor - an intelligent support system to assist creatives in collaboration

• Trained a transformer (GPT) model using offline reinforcement learning (RL) and sequence modeling

• Designed a user interface (UI) to demonstrate the working of the model

• Validated our method through extensive evaluations using automated metrics and human studies

• Published at ACM CHI 2022 conference (Late-Breaking Work) Publications

• Suryateja BV, Jeet Patel, Atharva Naik, Yash Parag Butala, Sristy Sharma, Niyati Chhaya Towards Enabling Synchronous Digital Creative Collaboration: Codifying Conflicts in Co-Coloring. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems. Link Projects

NoteKeeper Mobile App

• Built a mobile application for note-keeping in which notes can be created, updated, or deleted and can be stored according to priority. Technologies/Frameworks used - Dart, Flutter, Android Studio Multilingual Question Answering Course Project

• Explored various multilingual models for Extractive Question Answering in Hindi and Tamil

• Fine-tuned these models on multilingual QA datasets and experimented with hyperparameters, post-processing techniques, and ensembling methods to enhance performance on test data

• The task was part of chaii - a Kaggle research code competition, hosted by Google Research India

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