We are proud to announce that Momona Yamagami was selected as the winner of the first annual CNT (Center for Neurotechnology) Fernando Family Fund Best Student Paper award for her paper titled, “Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance”. The best paper award was selected based on its significance and potential impact, its technical content, the originality of the proposed research, and the clarity of the solutions presented. Congratulations to Momona!
Awards
Michael Rosenberg awarded the Gatzert Child Welfare Fellowship
Elijah Kuska named TL1 scholar, 2020 Cohort
We are very proud to announce that Elijah Kuska is part of a cohort of new trainees in the Institute of Translational Health Sciences (ITHS) TL1 Translational Research Training Program. This is a one-year mentored research training program in translational science in a cross-disciplinary community with training, career development, and team science skills.
Project Title: “Analyzing the complex interaction between impaired neuromuscular and musculoskeletal system to determine if gait abnormalities of children with cerebral palsy are advantageous”. Congratulations Elijah!
Alyssa Spomer 2020 ‘Husky 100’ Awardee
Congratulations to Alyssa Spomer for being awarded the Husky 100. This award recognizes 100 students who are making the most of their time at UW through coursework, research, volunteer and leadership efforts, internships, and jobs: they have created their own Husky Experience.
Please help us in congratulating and welcoming Alyssa into the 2020 Husky 100 class!
Congratulations – Damon Ding is awarded UWIN’s Innovation Undergraduate Fellowship in Neuroengineering.
Our undergraduate student, Damon Qilang Ding, has been awarded the Innovation Undergraduate Fellowship the UW’s Institute for Neuroengineering. The UWIN Fellowship provides funding for Damon to conduct research in his upcoming quarters and is a highly prestigious and selective competition. Congratulations, Damon!
Damon’s research is to lead a fabrication, assembly, and tuning of a dynamic walking bipedal robot, which will serve as a testbed for validating the Ability & Innovation lab’s simulation framework evaluating whether discrepancy modeling with data-driven approaches enables more accurate dynamic solutions of bipedal movement with both unaltered and altered control.