Los Angeles Machine Learning

TEJAS JAIN

Los Angeles, California 213-***-**** ******@***.*** https://www.linkedin.com/in/jaintejas EDUCATION

University of Southern California Los Angeles, California Master of Science in Computer Science – CGPA: 3.83/4 May 2024 Coursework: Analysis of Algorithms, Database Systems, Deep Learning, Machine Learning, Applied Natural Language Processing University of Pune Pune, India

Bachelor of Engineering in Computer Engineering – CGPA: 9.58/10 Aug 2018-Jun 2022 TECHNICAL SKILLS

● Programming languages: Python, Java, C++, JavaScript Databases: Oracle, MySQL, and MongoDB

● Technologies: NodeJS, Django, Flask, React Native, Ajax, OpenCV, Gitlab, Pandas, NumPy, AWS, ETL, Git, R, Google Cloud, Spark, Jupyter, Scikit-Learn, Docker, Kubernetes, PyTorch, TensorFlow, Nltk,Azure,Hadoop, MapReduce,Power BI,Matplotlib RESEARCH EXPERIENCE

USC Information Science Institute – Visual Intelligence Multimedia Analytics Lab Los Angeles, California Machine Learning Engineer May 2023-Present

● Spearheaded research project funded by NSF, DARPA, focusing on temporal video segmentation for information extraction from lecture videos

● Engineered an innovative lecture segmentation algorithm utilizing the TW-FINCH approach with customized feature weighting, enhancing segmentation accuracy and efficiency in processing educational content EXPERIENCE

Ezml San Francisco, CA

Machine Learning Engineer Intern Nov 2023-Present

● Pioneered zero-shot learning implementation in custom computer vision, elevating model intelligence by 30%. Collaborated with a team of five to drive industry-leading advancements

● Improved object recognition accuracy by 40% across 10+ client applications using zero-shot learning models. Played a key role in a cross-functional team, facilitating the integration of cutting-edge technologies Sarvatra Centre of Research and Innovation (C. M. E, Pune) Pune, India Machine Learning Engineer Intern Oct 2021-Apr 2022

● Designed a chatbot using the fine-tuned LLM model on domain-specific use-case using proprietary Q&A pairs, achieving a remarkable 39% reduction in response time

● Enabled over 10,000 daily user interactions with the chatbot, providing accurate information and contributing to an 18% increase in operational efficiency

● Spearheaded the development of a cutting-edge surveillance application, integrating Faster R-CNN for precise object detection and FaceNet for robust facial recognition

Code Xperts Pune, India

Data Science Intern Aug 2020-Mar 2021

● Implemented a streamlined pipeline to scrape financial data from online sources for analyzing the ROI of start-ups, catalyzing financial analysis of 10,000 start-ups per week, and facilitating data-driven investment decisions

● Developed web crawlers and scrapers in Python to extract data from websites and employed predictive analysis and artificial intelligence to motorized data storage in managed system

● Created a hybrid classifier combining supervised LDA topic model and deep neural network, achieving an accuracy of 96.7% in predicting key attributes of scraped start-ups, boosting decision-making for investors Nsquare Xperts Pune, India

Software Engineer Intern Dec 2019-Jul 2020

● Built WeTrace, a secure mobile and web application prototype for logistics-based startups, resulting in a 40% improvement in shipment tracking efficiency and a 30% reduction in operational costs

● Devised a complex database and developed RESTful APIs using NodeJS and Swagger

● Optimized performance and mechanized data cleaning, resulting in a 50% reduction in database errors and revising overall data accuracy and reliability

PROJECTS

Smartxam

● Built a comprehensive test engine website with automated proctoring, deployed at more than 30 educational institutions

● Curated and refined a comprehensive data set, training advanced neural network models like YOLO for real-time object and auditory signal detection, achieving high precision in automated test proctoring environments FoodBot

● Engineered a cutting-edge contactless dine-out application for restaurants during the COVID-19 pandemic

● Integrated a DialogFlow-based NLU Engine to analyze and answer user queries and revolutionized dining experience by introducing Meera, a virtual butler, to enable guests to place orders effortlessly and securely Colorizer

● Designed an application to colorize old Bollywood tunes, video footage, and clips from the BBC's "India under the British Raj."

● Trained and fine-tuned the DeOldify model using a data set of 50,000+ photos, resulting in a 13% improvement in accuracy and enabling deployment via a Rest API for real-time practical applications

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