About me

I’m an AI/ML enthusiast who thrives on solving complex problems through innovative technology. My journey started with a passion for machine learning and deep learning, and since then, I’ve had the opportunity to work on a wide range of projects, from sensitive data discovery to computer vision applications in financial security. I love diving into data, building models, and optimizing solutions that create real-world impact.

I’m excited to continue pushing the boundaries of AI/ML and applying these technologies in impactful ways - whether in financial systems, healthcare, or other industries that can benefit from data-driven innovation.

I’m intrigued by ML and AI models and their applications in Quantitative Analysis, I also have an interest in Cryptography and Cybersecurity and its uses in Blockchain Security. I want to gain knowledge about these areas and more fields in Computer Science and Mathematics. My goal is to create something helpful for everyone that can improve and make everyone’s life easier.

Education

I’m a third year undergraduate student studying Mathematics & Computer Science at UC San Diego. I have also completed a Machine Learning Foundations Certificate from Cornell University.

Experience

1. American Express ML Intern

• Developed a sensitive data discovery model that detected and redacted PII, PCI, and contextual data from large financial text datasets, achieving an accuracy of 93% for identifying sensitive information
• Leveraged Named Entity Recognition (NER) techniques, successfully identifying sensitive data with a precision of 90% and recall of 88%, ensuring compliance with privacy regulations
• Integrated Regex for enhanced contextual discovery and redaction, improving detection of complex entities by 15%
• Enhanced the dataset’s consistency by overwriting it with proper classifications, using regex for accurate redaction validation, and improving detection of incorrectly classified data by 25% with custom regex solutions

2. Image InfoSystems Computer Vision Intern

• Developed and trained high-performance computer vision models for OCR, mathematical symbol, and Russian character datasets, achieving over 95% accuracy and reducing loss to under 5%
• Converted trained TensorFlow models to PyTorch using a custom ONNX conversion function, ensuring 100% retention of model accuracy and preventing data loss across frameworks
• Worked on a Bank Security Enhancement Project by working on computer vision solutions for cheque verification, increasing verification accuracy by 20%
• Completed Stanford deep learning courses available on YouTube, expanding knowledge of neural networks, CNNs, and deep learning architectures

3. Break Through Tech Machine Learning @ UCLA AI/ML Fellow

• Selected from 3000+ applicants, learnt data handling and preprocessing techniques, using Pandas for efficient data manipulation, NumPy for numerical operations, and Seaborn and Matplotlib for data visualization
• Developed proficiency in training machine learning models using scikit-learn. Achieved an average model accuracy of 92% across various datasets, with hyperparameter tuning increasing model performance by 15% on average
• Implemented a diverse range of models such as decision trees, k-nearest neighbors, ensemble methods, deep learning, and neural networks, gaining experience in model selection and reducing loss by 20% through effective model selection
• Created and evaluated various machine learning models weekly to ensure high performance on unseen data, consistently achieving over 85% accuracy in validation tests and reducing overfitting by implementing regularization techniquesn data

4. UJIMA S&P Lab (Professor Imani Munyaka) Research Assistant

• Developed a web-app for an Implicit Association Test (IAT) to measure an individual’s level of bias toward autism
• Created a prototype on OpenSesame and used Flask to recreate the IAT as a web-app written in Python
• Worked on the backend integration of the web-app to store and get reasonable insights from the survey
• Used the insights to contribute to Professor Munyaka’s anti-autistic hate speech detection project

5. ITA Workshop App Developer

• Developed a mobile application using Flutter and Dart for an annual workshop on information technology
• Worked closely with Professor Alon Orlitsky as part of a two-person team, engaging in frequent communication
• Redesigned and tested the splash screen and other in-app features using emulators for both Android and iOS
• Worked on the deployment of the mobile application on the App Store and Play Store after development

6. Mathematics Undergraduate Instructional Assistant

• Assisted Professors Hammock, Sarkar, Mackall, and Bach in maintaining an efficient learning environment for students
• Promptly and accurately graded weekly homework assignments which included MATLAB based assignments
• Provided constructive feedback to help students understand their mistakes, contributing to their academic growth
• Improved my mathematical skills and programming skills by identifying mistakes and thinking critically

7. Data Analyst Intern - Cimcon Software

• Analyzed sales data using Power BI to extract valuable insights and trends
• Developed interactive and visually appealing dashboards to present key performance indicators and sales metrics
• Automated recurring reports, saving time and increasing efficiency in data reporting
• Attained real world working experience by working under experienced professionals

8. Investment Advising Intern - Forthius Capital

• Worked with Kshitij Lodha, an experienced investment advisor and learnt about various ways of investing
• Researched and suggested possible investment opportunities based on profitability and client’s goals
• Learnt about risks in the stock market and how to assess them
• Shadowed Ksithij Lodha and improved professional communication skills and critical thinking

Awards

• Revelle College Provost Honors: Received Provost Honors based on the quarterly GPA
• Top 1/5th Of Revelle Student Body: Received the award for being in the top 200 students in Revelle College at UCSD