Celebrating Abdalaziz Awad’s PhD Defense

The Computational Lithography and Optics Group warmly congratulates Abdalaziz Awad on successfully defending his PhD thesis titled “Machine Learning Applications for the Acceleration of Computational Lithography" on July 16, 2026.

In his doctoral research, Abdalaziz addressed the growing computational demands of advanced computational lithography, where rigorous simulation and optimization are essential for modern EUV patterning. His work focused on how machine learning can accelerate lithography workflows while maintaining the accuracy required for process variation, mask 3D effects, and large-scale chip applications.

A central contribution of his thesis was the development of machine learning models for fast and accurate EUV image prediction, including a mask-topography-aware U-Net that achieved strong generalization and a speed-up of around 200× compared to rigorous simulations. He also investigated practical strategies for reducing training data requirements, including transfer learning, domain knowledge-based data selection, and the combination of simulated and experimental SEM data.

Beyond imaging, Abdalaziz applied machine learning to broader lithography challenges, including photomask fabrication modeling and inverse lithography technology (ILT). His work demonstrated that hybrid machine learning approaches can significantly improve computational efficiency while preserving high pattern fidelity, helping to make large-scale lithography simulation and optimization more practical.

This work was carried out in collaboration with partners including Google, LEB, and Photronics, highlighting the strong industrial relevance of his research. We are also delighted to see Abdalaziz continue this path in industry, where he is now working at Siemens EDA.

We sincerely congratulate Abdalaziz on this outstanding achievement and thank him for his dedication, innovation, and valuable contributions to our research. We wish him every success in the exciting journey ahead!