I am currently serving as the Team Lead for the advanced R&D unit at AWL, Inc. My primary responsibility is to enhance, improve, and automate the AI pipeline and model life cycle, aiming to improve the accuracy and performance of detection models and other vision models.

During my personal time, I engage in projects related to modular neural networks. This includes activities such as training an ensemble of expert neural networks and exploring innovative ideas for smarter design, such as data partitioning and clever subset class partitioning in ensemble machine learning models. I aspire to implement a large ensemble of learning models where only a portion of them will be activated during inference, resembling a Mixture Of Experts approach.

Before my current role, I pursued a Ph.D. degree at the University of Aizu in Japan, under the supervision of Prof. Qiangfu Zhao (https://u-aizu.ac.jp/~qf-zhao/) with a focus on knowledge distillation for model compression and the architecture modularization of deep neural networks, specifically employing a mixture of INDEPENDENT experts for resource-efficient training and inference.