Waleed Khamies is a machine learning scientist and on the PhD track at the University of Alberta, specializing in AI and healthcare. His research focuses on neural biomarkers in mental health conditions and developing secure AI models to support their care.
He holds a master's in Mathematical Sciences (specializing in Machine Learning) from the African Masters in Machine Intelligence (AMMI) and a bachelor's in Electrical and Electronics Engineering from the University of Khartoum.
Currently, Waleed works as an Applied Scientist at NTWIST, where he helps automate business processes in manufacturing using self-supervised learning and reinforcement learning. Previously, he contributed to deep learning research at MILA and interned at Brown University’s Robotics Lab, where his work was recognized at NeurIPS.
In his free time, Waleed enjoys reading, biking, tennis, and photography. He also shares insights through GradCorner AI, promoting AI advancements.
Solid experience with various generative models (Diffusion, GAN, VAE, Transformers, ..etc) for different types of data (text/image/video).
Solid experience with various machine learning and deep learning algorithms for different tasks.
Good experience with tensorflow extended (TFX) ecosystem for ML pipeline deployment.
Good experience with Google Cloud Platform.
Good experience with book and blog writings.
