This inventor holds 3 USPTO granted patents and 14 published patent applications. Top assignees: Nec Corporation, The University of Tokyo. Active years: 2022-2026.
Company Filing History:


Years Active: 2022-2026
Title: Yusuke Sakemi: Innovator in Spiking Neural Networks
Introduction
Yusuke Sakemi is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of neural networks, particularly in the area of spiking neural networks. With a total of 3 patents to his name, Sakemi's work is at the forefront of computational neuroscience.
Latest Patents
Sakemi's latest patents include a "Method and device for controlling firing timing in spiking neural networks." This invention features a computation apparatus that incorporates a spiking neuron model. The model varies an index value of a signal output based on the input condition of a signal during an input time interval. It subsequently outputs a signal during an output time interval that begins after the input time interval ends. Another notable patent is the "Neural network device, firing timing calculation method, and recording medium." This device narrows down the candidate time segments from when a spike is received to when the next spike is received. It represents the membrane potential of the spiking neuron as a monotonic function of time, with the firing condition being determined by comparing the membrane potential to a threshold.
Career Highlights
Throughout his career, Yusuke Sakemi has worked with notable organizations such as NEC Corporation and The University of Tokyo. His experience in these institutions has allowed him to develop and refine his innovative ideas in neural network technology.
Collaborations
Sakemi has collaborated with esteemed colleagues, including Takashi Kohno and Kazuyuki Aihara. These partnerships have contributed to the advancement of his research and inventions.
Conclusion
Yusuke Sakemi is a key figure in the development of spiking neural networks, with a focus on innovative methods for controlling firing timing. His contributions to the field are significant and continue to influence advancements in computational neuroscience.