Responsibilities include:

• Analyzed crime patterns using complex network metrics and developed a Graph Neural Network (GNN)-based technique for crime prediction utilizing the city’s street network structure
• Designed and implemented visual analytics tools to assist machine learning practitioners in selecting and applying feature attribution methods

Responsibilities include:

• Investigated patterns of disagreement among feature attribution methods in Explainable AI (XAI), providing insights into how disagreement relates to explanation quality and machine learning model accuracy
• Created a Python library to assist machine learning practitioners in systematically assessing, comparing, and selecting the most appropriate feature attribution method for their needs; published findings
• Conducted an analysis of large language models (LLMs), focusing on their reasoning processes, output generation, and issues related to hallucination

Responsibilities include:

• Led educational sessions highlighting the transformative impact of 5G technology on AI systems %development and deployment
• Authored technical documentation demonstrating the/ applications of AI and 5G solutions in the industry

Responsibilities include:

• Designed and implemented an Intelligent Tutoring System (ITS) for introductory programming courses, featuring automated formative feedback to support student learning and enhance problem-solving skills; published findings

Responsibilities include:

• Designed and deployed Intelligent Tutoring Systems for Propositional Logic and Mathematics, integrated into university courses Fundamentals of Mathematics and Logic Applied to Computing
• Contributed to a project integrating data from multiple sources using a semantic approach to construct and maintain user profiles for enhancing a recommender system
• Gained hands-on experience in recommendation systems, Case-Based Reasoning (CBR), Machine Learning, and programming with Scala, Python, ShellScript, and Java