Reiji Hatsugai

  • Research

Reiji Hatsugai

After graduating from the University of Tokyo in the Faculty of Engineering, Reiji proceeded to study at the Graduate School of Information Science and Engineering. As an undergraduate, he engaged in HPC research, while in graduate school he researched Deep Learning and contributed to scholarship on the subject through the presentation of several papers. Since joining DeepX, he has been engaged in multiple machine automation projects and has led the development of machina, a Deep Reinforcement Learning library that can be employed on a cross-sectional basis for the development of automation technology intended for various forms of machinery. He was appointed to the roles of Director and Chief Technology Officer in June of 2019.


Since the beginning of the Industrial Revolution, during the late 18th century, labor productivity around the world has continued to improve, resulting in a similarly rapid expansion in the total size and distribution of the human population as well. Based on the surplus garnered by the Industrial Revolution, infrastructure around the world has also developed, leading in turn to the present IT revolution. However, the reality is that the improvement in overall productivity that endured for so long has now stagnated. In addition, Japan and other developed nations are experiencing a wave of declining birth rates and rapid aging of the population, with the labor force diminishing as a result. If we define affluence in a rather simple manner, as the product of labor force and productivity, it seems that austerity is the only outcome when the labor force decreases and productivity is flat.

DeepX is an organization that seeks to tackle this issue head-on, emboldened by its central mission to “automate any machinery”. In the last 20 years, IT has evolved significantly, and the capabilities of software have improved dramatically. Looking at it on the macro level, I believe this is the result of reinvesting global surplus onto software. However, the industries that are set to experience the sharpest decline in the labor force are notably comprised by the likes of construction, agriculture, and food preparation, which have typically been difficult to imbue with the benefits of innovation in software. I believe that the coming together of rapidly evolving artificial intelligence technology and traditional hardware gives rise to a need for interface technology that will connect the complex real world with that of the software. We stand poised to significantly improve productivity and solve this problem by applying the great potential and capabilities of software to areas that have traditionally been difficult, until now, by means of artificial intelligence technology.

I welcome any opportunity to work in collaboration with others who share an appreciation of the issues outlined here, and the technical capability to seek out a remedy.



  • How can technology be leveraged to solve social problems?
  • Individual technological fields (Reinforcement Learning, Image recognition, Robotics)


  • I enjoy surfing and often go to the sea on weekends. Essentially, I think surfing embodies the idea of being "in the right place, at the right time". When you examine them closely enough, each wave is utterly unique – never to be repeated – and, as such, requires precision and timing in order to catch and ride it successfully. Mastering the ability to read and react to each wave demands repetition in practice and training. In this sense, it is analogous to fostering discipline in everyday life, to ensure that you are able to seize any opportunities presented in today's world, where circumstances are in the process of changing dramatically. Surfing reminds me that I am always a challenger and demands the kind of mindset a challenger must have in order to excel.

  • I work out on a regular basis. I believe that working out can act as the foundation of a resilient spirit, in addition to the obvious health benefits. The essence of this lies in the fact that your condition will improve only so long as you keep training, and deteriorate the moment you no longer apply yourself, providing an obvious physical reflection of what is lapse in determination. It teaches me how important it is to make an effort and how dangerous it can be to become complacent.

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