David Pugh
- Instructional Assistant Professor, Computer Science
Prof. David Pugh aims to prepare students to become proficient AI practitioners who can contribute to the advancement of AI technology and its responsible use in society. He has a significant experience developing applications using machine learning, deep learning, and generative AI, particularly Large Language Models (LLMs).
Biography
David Pugh completed his postdoctoral work at the University of Oxford in 2016, following an M.Sc. in 2009 and a Ph.D. in Economics in 2014 from the University of Edinburgh. He previously earned a B.S. in Mathematics from the College of William and Mary in 2005.
Professor Pugh leads the theme Accelerating GenAI Adoption in the KAUST Center of Excellence for Generative AI (GenAI). His work focuses on developing GenAI platforms to support innovations and applications, building capacity through training and residency programs, and promoting outreach activities to foster broader GenAI adoption, particularly among non-experts.
Research Interests
David has significant experience developing applications using machine learning, deep learning, and generative AI, particularly Large Language Models (LLMs).
His experienced research software engineer and data scientist who loves to teach. he just finished developing training materials to help data scientists get started managing their virtual environments with Conda and Docker. Currently developing data engineering solutions to accelerate distributed training of deep neural networks on HPC resources. He have a deep knowledge of the core data science Python stack: NumPy, SciPy, Pandas, Matplotlib, NetworkX, Jupyter, Scikit-Learn, PyTorch, TensorFlow.
His teaching interests span the across the entire AI pipeline, from data collection and pre-processing to model training, evaluation, and deployment. He is passionate about teaching students how to build, fine-tune and deploy AI models effectively and responsibly and emphasizes the importance of understanding the ethical and societal implications of AI technology.