2023/12: Takuhiro Nishida, Yuki Yabumoto(井尻研M1), The 20th ACM SIGGRAPH European Conference on Visual Media Production (CVMP), best short paper award. “Refocus-NeRF: Focus-Distance-Aware Neural Radiance Fields Trained with Focus Bracket Photography”
2023/11, Kei Suzuki (SugayaLab D1), Best Paper Award, Swin Transformer Based Depression Detection Model Learning Only Single Channel EEG SignalAsia Pacific Conference on Robot IoT System Development and Platform (APRIS2023)
2023/01: Masaki Wago (B4, Shinkuma Lab.), BEST DEMO AWARD RUNNER UP, "Prototype of edge sensing and computing system with multi-LIDAR network for autonomous micro-mobility," IEEE CCNC 2023
2022/12: Leisi Chen(Sugimoto Lab M2) SCIS&ISIS 2022, Best Student Presentation Award, "Quantifying and debiasing gender bias in Japanese gender-specific words with word embedding"
2022/01. Kentarou Kanai et al. (Sugaya Lab. B4) APRIS2021, Best Short Paper Award, "Assessing Damage in Disasters Using Drones with BiometricInformation Obtained from Wearable Devices", link
2021/12. Kensho Nishizawa (Nakajima Lab M1) CORETA 2021, Advances on Core Technologies and Applications. "A Method for Analyzing Improper Driving Using Passenger’s Danger Perceptions" link
2021/09. Yoshinori Ono (Usami Lab M2 (Graduated))IEEE CEDA All Japan Joint Chapter Academic Research Award, "Energy Efficient Approximate Storing of Image Data for Non-volatile Memory" link
2021/09. 中川友梨(菅谷研M1),第23回日本感性工学会大会,優秀発表賞「オンライン授業におけるコミュニケーションの差異が学習状態に与える効果の生体情報による客観的評価」 link
2021/09. 大網啓裕,橋本優希, 大塚嵩柾,井上健一,井口拓海,金井健太郎(菅谷研B4), enPiTサマースクール2021, 飛行技術の総合評価 1位/ 災害コンセプト 1位/プレゼンテーションの総合評価1位 link
2021/08. 小野 義基 (卒業生, 発表時 宇佐美研M2), 情報処理学会 2021年度コンピュータサイエンス領域奨励賞「Approximate Computingを用いた不揮発性メモリへの画像データ書き込みにおけるエネルギー削減手法」 link
2021/07. Yuri Nakagawa (Sugaya Lab M1), AHFE 2021, BEST STUDENT PAPER AWARDS"Evaluation of distance learning effects on concentration and relaxed states by EEG and HRV"
2021/07. Narumon Jadram (Sugaya Lab M1), AHFE 2021, BEST STUDENT PAPER AWARDS"Preliminary experiment for driver’s comfortable state using EEG and HRV during semi-autonomous driving"