Waleed Khamies

Area of Study / Keywords

Machine Learning Healthcare

About

I am a machine learning scientist at NTWIST and on the PhD track at the University of Alberta, exploring the intersection of AI and healthcare. 

Currently, I work as an Applied Scientist at NTWIST, where I help enterprises leverage machine learning to automate business processes in the manufacturing industry, focusing on both process manufacturing and discrete manufacturing. My work primarily involves utilizing self-supervised learning and reinforcement learning (RL).

Concurrently, I am on PhD track at University of Alberta, exploring the intersection of AI and healthcare. I am particularly interested in exploring the informational capacity of neural biomarkers in individuals with mental health conditions and assessing the feasibility of developing secure AI models to support their care.

I hold a master’s in Mathematical Sciences with a specialization in Machine Learning from AMMI and a bachelor’s in Electrical and Electronics Engineering from the University of Khartoum. Previously, I contributed to deep learning research at MILA and interned at Brown University’s Robotics Lab, with work recognized at top-tier workshops at NeurIPS and ICML.

Research

1. Khamies; The Creative Engine: Explore Generative Modeling From VAE to Diffusion Models; 2023; Book, ISBN 978-1-7390105-4-6; Online Draft
2. Khamies; How to Solve Algorithm Problems: Make Coding Interview Preparation Less Painful; 2023; GuideBook, ISBN 978-1-7390105-0-8; Available Online
3. Mai, Khamies, Paull ; Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression using Privileged Information; 2021; ICML Workshop on Uncertainty & Robustness in Deep Learning.
4. Khamies, Konidaris; Interpretable Reinforcement Learning Using Latent Reward Functions; 2019; NeurIPS Workshop: BAI.
5. Khamies, Mohammedalamen, Rosman; Transfer learning For Prosthetic Using Imitation Learning; 2018; BAI workshop, NeurIPS Workshop: BAI.

Teaching

Teaching Assistant Roles

• CMPUT 274 - Introduction to Tangible Computing I (Fall 2024).

1. Join GradCorner AI Publication

If you are interested in learning more about advanced AI and machine learning algorithms, join GradCorner AI publication. GradCorner AI is a space where you can learn about specialized ML techniques and things people in the industry and academia won’t tell you :), so please come and join us

-------->>  Join the Publication From Here!

2. My book "How to Solve Algorithm Problems" is out, get your copy now!

• Amazon: https://amzn.to/432vzO7
• Leanpub: https://leanpub.com/how-to-solve-algorithm-problems-book
• Khamies’ Store: https://shop.waleed.khamies.ca/b/hsap

3. The Creative Engine

• Join "The Creative Engine" Book waitlist here: https://gradcorner.ca/books/the-creative-engine
• Get notified when it is published here: https://leanpub.com/the-creative-engine-generative-modeling-book