I am currently a senior at the University of Alberta pursuing Honors Applied Mathematics and Computer Science. I am currently working with Professor Animashree Anandkumar (Nvidia) at Caltech in the Theoretical Computing Science (TCS) Group as a Research Intern as well as Professor Martha White and Adam White (DeepMind) at the Reinforcement Learning and Artificial Intelligence (RLAI) Lab and the Alberta Machine Intelligence Institute (Amii). I am also currently a CSRMP Research Scholar at Google and was a Data Science Intern at Microsoft in their Azure Compute Team and collaborated with Microsoft Research.
My research interests include theoretical aspects of Machine Learning and Reinforcement Learning specifcally in Computational Learning Theory, Complexity Theory and Foundations of Deep Learning. I would like to better contribute to understanding the generalization properties of Neural Networks, Representation Learning, Robustness and also dive into Meta Learning. Learning algorithms are frequently created to produce (and optimize) bounds on the relevant values. These bounds offer assurances and provide insight into black-box machine learning systems. I find this exciting as it gives me a deeper understanding of the algorithm, and it's fun to prove these bounds and correctness.
Another area of study I hope to get into is Explainable Artificial Intelligence and during my time at the Explainable AI (xAI) Lab I have seen the necessity that humans must understand how to build domain models which support explanation of an AI system's behaviour. I have also had the chance to do research in Numerical Algorithms afflaited with the Pacific Institute of Mathematical Sciences (PIMS) and the Applied Mathematics Institute (AMI) where I better contributed to understanding and developing algorithms for Quasi - Linear PDE's, climate forecasting (I was part of the AI Computational Team at the Wishart Lab) and Healthcare (I was part of the Canadian VIGOUR center). I am interested in contributing to interdisciplinary projects that involve AI 4 Science to help impact the community positively.
Lastly, for graduate school, I am mostly interested in pursuing Theoretical Machine Learning especially the Foundations of Deep Learning, Reinforcement Learning and Computational Learning Theory. I also am interested in giving back to the community by teaching and mentoring students and sharing my love for Mathematics and Computer Science and co-leading the ML Theory Reading Group at Cohere for AI.
Feel free to contact me at rjoseph1 (at) ualberta (dot) ca if any of these interests align with your research or if you have any questions. I am always open to new opportunities and collaborations.