Hello, my name is Zaeem. I’m a Computer Science and Mathematics double major at the University of Massachusetts Amherst, with a focus on artificial intelligence and data science.
Currently, I am working with Professor Hamed Zamani at the Center for Intelligent Information Retrieval as a research fellow, focusing on developing methods and techniques for making large language models more useful for individuals through personalization. Over the summer, I worked on a research project that focused on optimizing convolutional neural networks for American Sign Language recognition and worked as a Data Science Intern at Neftwerk.
Additionally, I like watching football, cricket, tennis and Formula 1.
Experience
Software Development Extern
Snap Inc.
- Designed a soccer-themed AR lens incorporating Snap's Lens Studio and 3D modeling, certified by Snap Inc.’s Head of Entertainment.
- Launched a Snapchat lens inspired by Reebok and soccer, compatible with iOS and Android, gathering views from 100+ countries.
- Conducted data-driven market research in sports and technology using Tableau, and MySQL enhancing data visualization by 30%.
Data Science Intern
Neftwerk
- Designed and sorted data from CSVs to Attio dashboards to improve client information accuracy and operational efficiency by 60%.
- Leveraged Attio’s REST API to implement filtering and pagination, optimizing data retrieval by 30% and enhancing user experience.
- Engineered Python automation for Excel-to-CSV pipeline, leveraging Git version control to optimize Attio dashboard data processing.
AI Research Intern
Center for Intelligent Information Retrieval
- Building a benchmark for LLM personalization using crowdsourcing via MTurk and API-driven calls of models like GPT-4 and Llama.
ML Research Intern
University of Massachusetts Amherst
- Optimized a CNN for ASL recognition, achieving a 97% F1 score through data augmentation and additional convolutional layers.
- Utilized ResNet pre-trained models to enhance accuracy to 98% and reduce overfitting, improving generalization on unseen data.
- Enhanced model robustness in Keras with batch normalization, and the Image Data Generator for consistent validation performance.
Projects
Each Project has a link to my GitHub code. Feel free to look at the quick video demos or check out my code.
PerfectPitch
AI-powered platform designed to provide tailored feedback, script assistance, and a performance score for personalized interview preparation.
LeetBank
Web-based platform that is designed to help you store, annotate and manage your LeetCode questions efficiently.
Uber Data Pipeline
A scalable pipeline using Python, GCP, Mage.ai, and BigQuery to process NYC Uber trip data, automating ETL and delivering insights via Looker Studio.
PomoPay
A Pomodoro-based productivity app that sets weekly goals, links payments to accountability, and boosts focus with secure Stripe integration.
Sonar Data Classification
Developed a sonar signal classification model to distinguish between "Rock" and "Mine" signals using XGBoost.
Olympic Medal Predictor
Predictive analytics project designed to forecast Olympic medal counts using historical data and machine learning models.