Abdul Kazeem Shamba
About
I am a doctoral researcher with the Norwegian Research Center for AI Innovation (NorwAI). My motivation for joining the NorwAI research center stems from my affinity towards conducting research in machine learning and developing innovative technologies. My experience as a teaching assistant in computer vision at Carnegie Mellon University has crystallized a strong interest in teaching, research, and innovation. As such, I look forward to contributing to the existing body of knowledge through rigorous scientific research and AI-driven industrial innovation to consolidate and strengthen the Scandinavian applied AI communities.
I am an avid supporter of the notion that we don't need larger models but better learning algorithms. My objective is to understand how humans learn (meta-learning), and I hope that by some serendipity, I can help create a technology that works. To that end, I have spent a huge part of my research deciphering what robots see when they look at the world (computer vision) and how best to represent the world or data to a computer (contrastive representation learning).
Research
Norwegian Research Center for AI Innovation (NorwAI)
Norwegian Open AI Lab (NAIL)
Publications
2025
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Shamba, Abdul Kazeem;
Bach, Kerstin;
Taylor, Gavin.
(2025)
Contrast All The Time: Learning Time Series Representation from Temporal Consistency.
Academic chapter/article/Conference paper
Part of book/report
-
Shamba, Abdul Kazeem;
Bach, Kerstin;
Taylor, Gavin.
(2025)
Contrast All The Time: Learning Time Series Representation from Temporal Consistency.
Academic chapter/article/Conference paper