Our Advisers
Our advisers are highly experienced scientists, research experts, tech practitioners and educators who volunteer in their personal capacity to consult with our team on curriculum, program, and learning outcomes.
Ahmad Rushdi
Senior Manager of Research Communities, Stanford Institute for Human-Centered Artificial Intelligence (HAI)
Curriculum Adviser, AI for Good Institute
Ahmad A. Rushdi is a Sr. Research Manager at the Stanford Institute for Human-Centered AI (HAI). He works with the diverse machine learning, deep learning, and artificial intelligence communities across Stanford and the corporate world, in order to envision, build, and maintain new bridges around cutting-edge research that would create useful and trusted systems for a variety of AI applications.
Dr. Rushdi's research interests include statistical signal processing and uncertainty quantification methods applied to machine learning models trained on time-series and real/synthetic image datasets. His publications span system design, communications, genomics, meshing, and national security applications.
Prior to joining Stanford, Ahmad was a research scientist at the Center for Computing Research of Sandia National Laboratories, an R&D manager of data science at Northrop Grumman Corporation, a research fellow at the Department of Electrical and Computer Engineering of UC Davis and the Computational Visualization Center under Oden Institute for Computational Engineering and Sciences at UT Austin, and an R&D engineer at Cisco Systems.
Ahmad holds a PhD in Electrical and Computer Engineering from the University of California, Davis, and MSc/BSc degrees in Electrical Engineering from Cairo University.
Younes Bensouda Mourri
Founder & CEO, Livetech.AI
Lecturer, Machine Learning at Stanford University
Curriculum Adviser, AI for Good Institute
Younes Bensouda Mourri is the founder of LiveTech.AI, an AI learning platform that transforms academic institutions by providing them with AI tools. He got his B.S. in Math & Computer Science and M.S. in Statistics all from Stanford University. He started a PhD at MIT in Social Robotics and is currently on leave to work on LiveTech.AI. He co-created 5 Deep Learning, 4 Natural Language Processing, and 1 Machine Learning course that have reached over 1.3 million learners online. 23% of the online learners got a job in AI after completing the courses. He is currently an Adjunct lecturer of computer science at Stanford since the age of 22 where he teaches Machine Learning with Andrew Ng. Younes previously worked in Coursera and Deeplearning.AI where he not only developed and taught courses but also built smart AI auto-graders capable of grading millions of submissions in real time. Outside of Stanford, he taught/teaches generative AI courses in companies like ASML, CISCO, Boston Consulting Group (BCG), etc. Recently his interests are in developing AI educational tools and more specifically NLP for personalized feedback and chain of thought reasoning.
Younes was born and raised in Morocco and advocates for Artficial Intelligence powered education. He helps people learn new skills to prepare them for jobs in a fast changing world. His work focuses on Artificial Intelligence. Younes prefers working with products from the start. He is interested in data acquisition strategies to build solid AI models during the early prototyping phases of product. Finally, while at Stanford, he built an interest in education technology and is particularly interested in using technology and AI for better social learning.
Alaa Talaat Youssef
AI Postdoctoral Scholar, Stanford University, School of Medicine
Curriculum Adviser, AI for Good Institute
Dr. Alaa Youssef is a postdoctoral fellow at the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), in the Department of Radiology. She received her Doctor of Philosophy (PhD) degree in Population Health and Medical Education from the Institute of Medical Science, University of Toronto in 2021, Canada. Her research interests lies at the intersection of artificial intelligence (AI) implementation and clinical evaluation. She works with multi-disciplinary research teams to assess, design, develop, and implement person-centered AI solutions that address a clinical need. Her research addresses the ethical, organizational, and workflow barriers that impede clinical adoption of AI in healthcare. Dr. Youssef spearheads the curriculum design, development, and evaluation of several AI educational programs, focusing on creating a diverse and inclusive training environment. Through this work, she aims to build capacity for AI research and ensure the safe and responsible development and deployment of AI in healthcare.