
Kai Malcolm successfully defended his MS thesis, “A Federated Learning Framework for Personalized and Privacy-Preserving Biosignal Interfaces”. Congratulations!
Kai Malcolm successfully defended his MS thesis, “A Federated Learning Framework for Personalized and Privacy-Preserving Biosignal Interfaces”. Congratulations!
Graduate student Mikayla Deehring gave a poster presentation on “Predicting Adherence to At-Home Rehabilitation Using Biosignals”. Great job Mikayla!
The Yamagami lab participated in the first Health Equity Workshop hosted by the Digital Health Initiative at Rice University. Momona Yamagami presented on “Accessible and Inclusive Digital Health Technologies for Ubiquitous Rehabilitation“. We also had poster presentations from Kai Malcolm and Mikayla Deehring:
Our lab has received funding on “Enabling Access to Prehab for Kidney Transplant Candidates who are Frail” through seed funding from the 2023 Digital Health Workshop hosted by the PATHS-UP ERC. We are looking forward to working with Drs. Atiya Dhala (Houston Methodist), Farzan Sasangohar (Texas A&M University), and Elizabeth Lorenz (Baylor College of Medicine) to develop a mobile health platform to support at-home prehabilitation for individuals with end-stage kidney disease. See other winners and more information on Rice News.
The Yamagami lab participated in the October 2023 AI in Healthcare Conference [https://events.rice.edu/event/347482-2023-ai-in-health-conference] as well as the September 2023 Texas Colloquium on Distributed Learning [https://sites.google.com/view/tldr2023], both hosted by the Ken Kennedy Institute at Rice University. Kai Malcolm presented his recent work as a poster at both venues: Protecting Sensitive Biosignal Data in Model Training: Federated Learning for Healthcare Applications. Great job Kai!
Kai was selected to join the Bioelectronics NSF Research Traineeship program, which focuses on training PhD students to collaborate across different disciplines. Kai will be collaborating with other students to design new brain/body-machine interfaces to augment human capabilities for people with and without disabilities.
Lauren was selected for the Dean’s Prize bonus award from Rice ECE and GPS. This award will help Lauren transition to her graduate studies and support her research on developing data-driven models to improve health and accessibility. She will be starting as a PhD student at Rice University in Fall 2023. Congratulations Lauren!
We are excited to continue developing personalized human-machine interfaces that adapt to the abilities of individual users and support their health and accessibility goals.