Azam Amir

Results-oriented civil engineer with a strong background in data science and AI. Skilled in applying advanced analytical methodologies and machine learning algorithms to optimize civil engineering problems, especially the maintenance management processes, and enhance decision-making. Committed to driving innovation at the intersection of civil engineering and AI.

• Designed, supervised, and implemented infrastructure construction projects in Pakistan.
• Successfully completed and supervised 240 km of road network under JICA (Japan) assisted project.
• Conducted progress report meetings with JICA and effectively managed project communications.
• Collaborated with multidisciplinary teams to ensure project timelines and deliverables were met.
• Developed and implemented quality control measures to ensure adherence to engineering standards and specifications.

• Ph.D. student focusing on integrating AI and machine learning algorithms for infrastructure maintenance management.
• Conducting in-depth research on the application of AI and machine learning techniques to optimize infrastructure maintenance practices.
• Designing and implementing data-driven models for condition assessment, asset prioritization, and risk analysis in infrastructure maintenance.
• Collaborating with industry partners to gather relevant data and validate the effectiveness of AI-based maintenance approaches.
• Analyzing large datasets to identify patterns, anomalies, and potential failure modes, enabling proactive maintenance interventions.
• Publishing research findings in reputable journals and presenting at conferences to contribute to the academic discourse on AI in infrastructure management.
• Utilizing programming languages (such as Python, or R) and AI frameworks (such as sci kit-learn) to develop and evaluate AI-based models.
• Applying statistical analysis and data visualization techniques to interpret research results and communicate insights effectively.