I am currently the director of AI engineering and technical lead for robotics and AI in manufacturing at Toyota. Most recent prior work has been in the building of a technology that enables a new type of perception for robotics through chemical sensing (olfaction). I became frustrated with the current state of olfaction sensors as none of them are optimized for real-time robotics. So, I built and patented my own, optimizing the entire hardware and software engineering stack in the process. Follow Scentience to learn more.
My doctoral work focused on enabling robots to navigate by scent through computational chemistry, reinforcement learning, and continual deep learning. This also included substantial hardware development to optimize chemical sensors for real-time decision making in robotics. Many of my AI models and datasets have been published on Hugging Face. I hope to standardize olfaction for AI and machines. Scentience was founded to continue the work I started in my PhD.
My Master's research on reinforcement learning and swarm intelligence was supervised by Dr. John Sheppard at Johns Hopkins University. I was then a graduate researcher for olfaction sensor development under Dr. Shalini Prasad at the University of Texas at Dallas. I was supervised by Dr. Ovidiu Daescu for my Doctoral thesis in continual learning and multimodal sensing machine for robotics. An introduction for the curious can be found here and here.
A significant amount of my spare time is spent building algorithmic trading software for my prop fund; in another life, I was a quant.

This positional survey, at the time of publication, seemed to be the only one intersecting machine olfaction with modern artificial intelligence and robotics. We hope this gives the community a state of the union on where the sense of smell for robotics currently stands and where the open questions lie. ArXiv link here.
Part 1
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