Mahboubeh Bahari Nematabad

Intro

Hello! I'm Mahboubeh Bahari Neematabad, a Master’s student in Computer Science at the University of Victoria. I am passionate about data analysis, machine learning, and privacy-preserving technologies. My journey in computer science has allowed me to develop a strong foundation in programming, statistical analysis, and the ethical implications of data handling. With a background in software engineering and experience in developing privacy-enhancing algorithms, I aim to create impactful solutions that protect user data while enabling valuable insights. In addition to academic excellence, I have practical experience in data science, backend development, and research, which I am excited to bring to real-world applications.

Thesis Description

Title: Exploring the Impact of Different Neighbouring Definitions on Differential Privacy in Bus Trajectory Data Analysis

As urban transportation systems grow increasingly dependent on trajectory data for planning and optimization, safeguarding individual privacy within such datasets has become a pressing challenge. My thesis addresses this issue by investigating Differential Privacy (DP) techniques tailored to trajectory data. Specifically, my research focuses on: Neighbouring Definitions: Examining various privacy levels, such as user-level, event-level, and ℓ-trajectory privacy, to determine their effectiveness in protecting sensitive trajectory information. Data Representation: Utilizing structured approaches like prefix trees and implementing Laplace noise to obfuscate sensitive data while preserving utility. Privacy-Utility Tradeoff: Balancing privacy protection with data utility to enable meaningful analysis for urban transit systems. By implementing privacy-preserving mechanisms, my work aims to provide a framework for anonymizing trajectory datasets, ensuring they are secure and valuable for applications like route optimization, urban planning, and research in public transportation. My thesis not only contributes to the theoretical foundations of Differential Privacy but also offers practical methodologies for addressing real-world privacy challenges in mobility data.

CV

Welcome to my professional profile. Below, you will find an overview of my key skills, achievements, and a link to my detailed CV.

• Technical Skills: Proficient in Python, SQL, and machine learning frameworks (e.g., scikit-learn, PySpark).
• Research Expertise: Specialized in Differential Privacy, focusing on anonymizing trajectory datasets.
• Academic Achievements: Multiple awards, including the Graduate Research Funding Award and Top Academic Performance Award at the University of Victoria.
• Professional Experience: Experience as a mentor, business plan writer, and software developer with expertise in real-time tracking systems.

For a detailed overview of my academic and professional journey, you can download my CV here:

Download My CV

Contact

Feel free to reach out for questions, collaborations, or simply to connect!

📧 Email: mismbahari@Uvic.com

💼 LinkedIn: linkedin.com/in/m-bahari

💻 GitHub: github.com/M-Bahari

• GitHub
• LinkedIn

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