Purva Patel

Follow-Up Caller

2023 - Present

Ontario Tech University, Oshawa, ON

• Communicated with incoming students to address their queries regarding university admission, courses offered, and campus life.
• Provided detailed information and guidance to help students make informed decisions about their academic future.
• Automated various tasks using scripts and tools to enhance productivity and streamline the follow-up process.
• Ensured timely and effective communication by managing schedules and maintaining organized records of student interactions.

Tutor/Teacher Assistant

2023 - Present

Sylvan Learning Center, Pickering, ON

• Taught Courses including Mathematics, Physics, and Python programming to a diverse group of students.
• Developed personalized lesson plans to meet the unique learning needs and goals of each student.
• Simplified complex technical concepts, making them accessible and easier for students to understand.
• Provided one-on-one and group tutoring sessions to enhance student comprehension and performance.
• Collaborated with other educators to create and implement effective teaching strategies and materials.

Peer Tutor

2024 - 2025

Ontario Tech University, Oshawa, ON

• Provided one-on-one tutoring in Machine Learning to a university student, covering foundational concepts and practical applications.
• Introduced essential Python libraries for Machine Learning, including NumPy, Pandas, Matplotlib, and Scikit-learn.
• Guided the student through data preprocessing techniques, exploratory data analysis (EDA), and data visualization to derive insights.
• Taught various supervised and unsupervised Machine Learning models, including Linear Regression, Logistic Regression, KNN, SVM, Random Forest, Naive Bayes, and Deep Neural Networks (DNN).
• Ensured a strong understanding of model evaluation, hyperparameter tuning, and practical problem-solving using real-world datasets.

Deputy Executive at Netsoc

2023 - 2024

Ontario Tech University, Oshawa, ON

• Successfully organized TacOps, a capture-the-flag event at Ontario Tech University, in collaboration with the team.
• Monitored and maintained systems during the event to ensure smooth operation and security.
• Designed and set up networking and security challenges for event participants as a part of the technology team.
• Collaborated with peers to develop and implement effective strategies for club activities and events.

Cryptographic Encryption & Decryption Tool

Winter 2023

• Collaborated with a group to implement cryptographic encryption and decryption on plain text using various ciphers, including substitution cipher, RSA, Playfair cipher, Caesar cipher, and product cipher.
• Utilized Python and Object-Oriented Programming to develop and structure the project effectively.
• Designed and coded modules for each cipher, ensuring accurate encryption and decryption processes.
• Conducted thorough testing and debugging to validate the functionality and security of each implemented cipher.
• Presented the project, demonstrating the practical application of cryptographic techniques in securing data.

Predictive Stock Price Modeling

Winter 2024

• Focused on predicting stock prices for five major tech companies: Google, Nvidia, Microsoft, Cisco, and Apple.
• Conducted data preprocessing, feature engineering, and model evaluation to ensure robust and reliable predictions.
• Developed an ML predicting model utilizing Linear Regression, Random Forest, and Deep Neural Network (DNN).
• Achieved an impressive accuracy of 98.42% using the Deep Neural Network (DNN) approach.

Pentesting Project

Summer 2024

• Conducted a comprehensive penetration test on a network via TryHackMe, employing techniques such as enumeration, pivoting, command and control, and data exfiltration.
• Executed network enumeration to identify and map out connected devices, services, and potential vulnerabilities.
• Utilized pivoting techniques to move laterally across the network, gaining access to isolated systems and critical resources.
• Implemented command and control strategies to maintain access and control over compromised systems.
• Compiled a thorough report detailing key findings, tactics, techniques, and procedures (TTPs) used, providing actionable insights and recommendations for network security improvements.

IoT-Based Smoke Detection Using Machine Learning

Fall 2024

• Developed and analyzed machine learning models for classifying smoke events using IoT sensor data.
• Performed comprehensive data preprocessing steps, including capping outliers at the 99th percentile and applying log transformations to reduce skewness for features such as TVOC[ppb], eCO2[ppm], PM1.0, and PM2.5.
• Engineered new features, such as Temperature-Humidity Ratio and Difference, to enhance model interpretability and performance.
• Evaluated multiple models, including Logistic Regression, Random Forest, SVC, KNN, Decision Tree, Gradient Boosting, and Naive Bayes, with Ensemble based models achieving the highest accuracy of 100%.
• Conducted a comparative analysis of models, highlighting ensemble methods for their reliability, while showcasing IoT sensor data's potential in predictive safety systems.