Session Details
[18a-PA2-1~16]FS.1 Focused Session "AI Electronics"
Wed. Mar 18, 2026 9:30 AM - 11:00 AM JST
Wed. Mar 18, 2026 12:30 AM - 2:00 AM UTC
Wed. Mar 18, 2026 12:30 AM - 2:00 AM UTC
PA2 (Arena (1F))
[18a-PA2-1]Object Detection Model Using Hybrid Quantum Classical Machine Learning
〇Ang Li1, Fei Bao1, Rei Sato2, Genki Okano2 (1.MACNICA, Inc., 2.Classiq Technologies G.K.)
[18a-PA2-2]Quantum Reservoir using NISQ Devices for Time-Series Information Processing
〇Mio Kawanabe1, Saud Cindrak2, Takumi Kanezashi1, Daisuke Tsukayama1, Jun-ichi Shirakashi1, Tetsuo Shibuya3, Hiroshi Imai3 (1.Tokyo Univ. Agr. & Tech, 2.TU Ilmenau, 3.Univ. Tokyo)
[18a-PA2-3]Wide-Range Tuning of Relaxation Time Constant in ITO/4H-SiC Schottky Junction Reservoirs Using Persistent Photoconductivity
〇(B)Kento Teshima1, Yumeng Zheng1, Kentaro Kinoshita1 (1.Tokyo Univ. of Sci.)
[18a-PA2-4]Proposal of a 1T1R Cell Model and Dynamic Gate-Control Circuit for Accelerating AI Training
〇Sho Hamano1, Yusuke Mizobata1, Kensei Kugio1, Rozu Henmi1, Kaito Tabata1, Munehiro Tada1 (1.Keio Univ.)
[18a-PA2-5]Simulation of Online Learning in Magneto-Optical Diffraction Neural Networks
〇(M2)Tomonao Matsuya1, Fatima Zahra Chafi1, Hotaka Sakaguchi1, Takayuki Ishibashi1 (1.Nagaoka Univ. Tech.)
[18a-PA2-6]Increasing the number of time-series optical characters that can be recognized
using a solid electrolyte physical reservoir
〇(B)Kenshin Takeo1, Tsuyoshi Hasegawa (1.Waseda Univ.)
[18a-PA2-7]Recognition of All 26 Letters of the Alphabet in Optical Pattern Classification Using a Physical
Reservoir
〇(B)Koki Masuda1, Tsuyoshi Hasegawa1 (1.Waseda Univ.)
[18a-PA2-8]Development of learning circuits for building a real-time rock-paper-scissors system
〇(B)Sota Sato1, Tsubasa Nishikawa1, Takao Fukuda1, Tsuyoshi Hasegawa1 (1.Waseda Univ)
[18a-PA2-9]Basic characteristics of a physical reservoir made of a liquid crystal
〇(B)Kanon Nakazawa1, Yuya Ishizaki2, Shusaku Nagano2, Tsuyoshi Hasegawa1 (1.Waseda Univ., 2.Rikkyo Univ.)
[18a-PA2-10]Recognition of optical signals by a photoconductive-molecule/Ag2S reservoir
〇(M1)Takao Fukuda1, Tsuyoshi Hasegawa1 (1.Waseda Univ.)
[18a-PA2-11]Photo-response of a BiVO4-particles’ physical reservoir
〇(M1)TSUBASA NISHIKAWA1, TSUYOSHI HASEGAWA1 (1.Waseda Univ.)
[18a-PA2-12]A proposal of a simple reservoir computing circuits utilizing oxide networks
〇(B)Chima Gerald Anumaka1, Sinya Aikawa1 (1.Kogakuin Univ.)
[18a-PA2-13]Neuromorphic Properties in Ag2S Based Random Atomic Switch Networks
〇Jyouji Iimori1, Naoki Shimazaki2, Kouta Miura1, Satoshi Hamano1, Keiichi Yanagisawa3, Usami Yuki4, Hirofumi Tanaka4, Takahiro Morimoto5, Ryouta Negishi1,2,3 (1.Toyo Univ., 2.Grad of Toyo Univ., 3.BNC, 4.Kyutech, 5.AIST)
[18a-PA2-14]Real-Time Hardware System Using Ag2Se Atomic Switching Network Reservoir Computing Device
〇(D)Ahmet KARACALI1, Takumi Kotooka1, Yuki Usami1,2, Hirofumi Tanaka1,2 (1.LSSE, Kyutech, 2.Nemorph Center, Kyutech)
[18a-PA2-15]Binary reservoir computing consisting of clusters for scalable in-memory applications
〇Oliver Aaron Velasco1, Rei Kusunose1, Alexandre Schmid2, Ayane Matsuzaki1, Seiji Adachi1, Kota Ando1, Tetsuya Asai1, Takao Marukame1 (1.Hokkaido Univ., 2.EPFL)
[18a-PA2-16]Sumanene-inspired Binary Reservoir Computing as a joint function of Neuromorphic Computing
〇Rei Kusunose1, Oliver Velasco-Cardenas1, Ayane Matsuzaki1, Seiji Adachi1, Kota Ando1, Tetsuya Asai1, Yuichiro Mitani2, Takao Marukame1 (1.Hokkaido Univ., 2.Tokyo City Univ.)