- Location
- Ottawa, Ontario, Canada
- Resume
- b_resume_2 (2).pdf
- Portals
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Toronto, Ontario, Canada
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Toronto, Ontario, Canada
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- Categories
- Artificial intelligence Databases Machine learning Project management Security (cybersecurity and IT security)
Skills
Socials
Latest feedback
Achievements



Recent projects

Cybersecurity Data Collection Research Assistant
The main objective of the project, focusing on cybersecurity data collection and labeling for vulnerability management, is to enhance the understanding and management of cybersecurity vulnerabilities. This project aims to engage students in the crucial task of gathering, analyzing, and labeling data related to cybersecurity threats and vulnerabilities. Problem to Solve: Students will be tasked with addressing the challenge of identifying and categorizing various types of cybersecurity vulnerabilities. This involves the collection of vast amounts of data from different sources, such as security logs, network traffic, and public vulnerability databases. The key challenge lies in accurately analyzing and interpreting this data to identify potential vulnerabilities. Expected Outcome: By the end of the project, students are expected to achieve the following outcomes: 1. Comprehensive Data Collection: Students should be able to gather relevant cybersecurity data from multiple sources systematically. This includes understanding where to find data and how to extract it efficiently. 2. Effective Data Labeling and Categorization: Students should develop skills to accurately label and categorize the collected data based on the type and severity of the vulnerabilities. This involves understanding different types of cybersecurity threats and their characteristics. 3. Vulnerability Analysis Skills: Students should be able to analyze the labeled data to identify patterns or trends that could indicate potential security vulnerabilities or breaches. 4. Reporting and Documentation: Students should be able to document their findings in a clear and concise manner, providing insights and recommendations for vulnerability management and mitigation strategies. 5. Awareness of Ethical and Legal Considerations: Students should understand and adhere to ethical and legal standards in data handling, particularly regarding sensitive or personal information. 6. Collaborative Skills: Given the complexity of cybersecurity, students should also learn to collaborate effectively, sharing insights and combining expertise to tackle multifaceted problems. The success of this project lies in its ability to equip students with practical skills in handling real-world cybersecurity challenges, enhancing their ability to identify, analyze, and manage cybersecurity vulnerabilities in various environments.

Client Intake & Assessment Feature Development for The Clean Divorce
The main goal for the project is to develop a Client Intake & Assessment Feature for The Clean Divorce platform. This feature should streamline the process of gathering necessary information from clients and assessing their needs during the divorce process. The feature should be user-friendly, comprehensive, and aligned with the company's mission to empower and support families during critical times. This will involve several different steps for the team, including: - Initial meetings to understand the specific requirements and goals for the Client Intake & Assessment Feature. - Designing the user interface and user experience for the feature, ensuring it is intuitive and supportive for clients going through the divorce process. - Developing the backend system to securely store and manage client information, as well as automate the assessment process based on predefined criteria. - Testing the feature with real users and making improvements based on feedback. - Integrating the feature into The Clean Divorce platform and providing necessary training for staff to use it effectively.
Work experience
Cybersecurity Research Assistant
PatchIT
Toronto, Ontario, Canada
March 2025 - May 2025
Extracted and parsed large-scale cybersecurity data from security logs, network traffic, and public vulnerability
databases using data extraction tools. Applied advanced data labeling techniques to classify vulnerabilities by type and severity, enhancing threat detection accuracy. Conducted in-depth vulnerability analysis, identifying patterns and anomalies using data aggregation and analytical
frameworks. Produced detailed technical reports with data-driven insights, mitigation strategies, and vulnerability assessments. Delivered a final presentation showcasing analytical methodologies, findings, and vulnerability management
solutions
Anti-Malware Software Developer
Wilfrid Laurier University
Waterloo, Ontario, Canada
October 2024 - March 2025
Collaborating with a Computer Security professor to develop an innovative anti-malware solution using C/C++ and Python, leveraging cryptography and cybersecurity knowledge to design advanced detection and prevention algorithms while researching modern threats to enhance software performance.
Web Developer
Sessila Academy
Ottawa, Ontario, Canada
May 2024 - August 2024
Designed and developed a secure, full-stack website using HTML, CSS, and JavaScript, incorporating robust client-side validation, accessibility standards, and responsive design for seamless cross-browser functionality. Additionally, coordinated daily operations, addressed inquiries, and maintained clear communication with parents and youth to ensure a smooth program experience.
Education
Bachelor of Science (B.S.), Computer Science
Wilfrid Laurier University
September 2022 - July 2026
Personal projects
AI Chess Engine
November 2024 - February 2025
https://github.com/brianpacouloute?tab=overview&from=2025-03-01&to=2025-03-17Designed and developed an interactive chess platform with adaptive AI opponents using Python, featuring ANSI-colored CLI visualization, move validation algorithms, and tiered AI logic with heuristic decision-making for varying difficulty levels. Applied object-oriented programming and game theory concepts to create robust move generation and check detection systems.
COVID-19 Impact Visualization: Trends & Insights
August 2022 - September 2022
Developed an interactive data visualization project analyzing the impacts of COVID-19 using Python, Pandas, and Matplotlib. Processed large datasets to illustrate trends in infection rates, vaccination progress, and economic effects, presenting insights through dynamic charts and heatmaps to enhance data-driven decision-making.