Afiya Ayman

I am a Machine Learning Scientist on the Deep Learning & AI team at Shell, where I work on applied ML and generative AI systems for scientific and engineering applications. My work focuses on developing agentic AI workflows and translating research prototypes into scalable, production-ready solutions in collaboration with domain scientists.

I have completed my PhD in Informatics at The Pennsylvania State University (graduating Summer 2025), advised by Dr. Aron Laszka in the Applied Artificial Intelligence Lab. My research specializes in Automated Multi-Task Machine Learning (AutoMTL), data science, and AI for social good, focusing on scalable deep learning and statistical models that optimize training efficiency and maximize real-world impact.

Over the past seven years, I have contributed to NSF- and DOE-funded projects, applying machine learning to improve public transit operations, enhance energy efficiency, and advance security analytics. My PhD thesis investigates factors influencing MTL performance and introduces cost-effective affinity prediction strategies to optimize task grouping across domains including computer vision, tabular data, time series, and transportation.

I hold an MS in Computer Science from the University of Houston and a BSc in Computer Science and Engineering from Chittagong University of Engineering and Technology, Bangladesh.

Interests

• Automated Machine Learning (AutoML)
• Multi-Task Learning (MTL)
• AI for Social Good
• Data Science