Applied ML Scientist

Who is Waleed Khamies?

Waleed Khamies is an applied machine learning scientist and researcher currently based in Edmonton, Canada. He is on a PhD track at the University of Alberta, where he is exploring the intersection of AI and neuroscience, with a particular focus on how AI can help uncover visuo-linguistic patterns in individuals with mental health disorders.
Waleed holds a master's degree in Mathematical Sciences with a specialization in Machine Learning from the African Masters in Machine Intelligence (AMMI) program and a bachelor's degree in Electrical and Electronics Engineering from the University of Khartoum (UofK). His robust academic background is complemented by significant practical experience in the field of machine learning and artificial intelligence.
His professional journey includes roles such as Applied Scientist at NTWIST, where he helps enterprises leverage machine learning to automate business processes in the manufacturing industry. He focuses on both process manufacturing and discrete manufacturing, utilizing self-supervised learning and reinforcement learning (RL). Previously, he developed a weld-defect analytics platform using computer vision and an abstractive audio-document summarization system utilizing BERT models. His work involved significant contributions to optimizing model performance and deploying models in production environments. Waleed also worked as an ML Research Engineer at the Quebec Artificial Intelligence Institute (MILA), where he developed deep learning algorithms for noisy label applications and contributed to research published in prestigious conferences like ICML and ICLR. Additionally, he has interned at the Robotics Lab at Brown University, where he focused on reinforcement learning and interpretability, with his work being recognized at NeurIPS.
Outside of his professional and academic pursuits, Waleed enjoys reading, biking, playing tennis, and engaging in photography. He also shares his knowledge and insights through ZitoonAI publication, contributing to the dissemination of AI advancements and applications.