Center for Machine Learning and Health

2022 Translational Fellowships in Digital Health

The Translational Fellowships in Digital Health were introduced in fall 2022. The projects are led by CMU faculty, research faculty or a system scientist with a Ph.D. student working as a team. The initial phase-one research for the project must have already been completed in order to qualify for this fellowship.

Meet the 2022 CMLH Translational Fellows

Student Riku Arakawa wearing a gray shirt

Riku Arakawa is a Ph.D. students in the Human-Computer Interaction Institute (HCII) advised by Professor Mayank Goel. Riku aims to develop high-impact intelligent systems with multimodal sensing/ML techniques and human-AI interaction perspectives. He hopes to help clinicians monitor children’s hyperactivity by leveraging techniques from wearable sensing. He completed his bachelor’s and master’s degrees in engineering at the University of Tokyo.

Fellowship Research: "Objective Measurement and Interpretable Interface for Hyperactivity Using Mobile Sensing"

Student Gautam Gare standing in a wooded area

Gautam Gare is a Ph.D. student in the Robotics Institute (RI) advised by Professor Deva Ramanen  and Assistant Systems Scientist John Galeotti. Gautam's research aims to advance the field of diagnostic healthcare by creating accurate and interpretable machine learning models that can facilitate better decision-making. His current research focuses on using causal techniques to improve the interpretability and reliability of artificial neural networks. He completed his bachelor’s degree in electronics and communication engineering at BMS College of Engineering, India, and his master’s degree in electrical and computer engineering at CMU.

Fellowship Research: "Synthetic Data Generation by Sampling from Learnt Causal Graph"

Student Michael Vinciguerra wearing glasses and a black shirt

Michael Vinciguerra is a Ph.D. student in the Mechanical Engineering Department, co-advised by Carmel Majidi, the Clarence H. Adamsen Professor of Mechanical Engineering, and Lining Yao, the Cooper-Siegel Assistant Professor in the HCII and the College of Engineering.  Michael's research focuses applying and integrating novel material architectures toward soft robotics, sensors and wearable devices. He is particularly focused on integrating liquid crystal elastomer (LCE), a shape reconfigurable material similar to artificial muscle, and liquid metal architectures (eutectic gallium indium, EGaIn) to stimulate shape change in LCEs. Michael leverages direct ink write (DIW) 3D printing to design customizable LCEs with stretchable, integrated circuitry.

Fellowship Research: "Self-Revealing LCE Bandage"

Fellow- Humphrey Yang

Humphrey Yang is an HCII Ph.D. Student advised by Assistant Professor Lining Yao. Humphrey's research focuses on using smart materials to make sensing and actuatable devices, applying these materials to different application contexts, and adapting machine learning to model smart materials and develop interactive design tools. Prior to joining the HCII, Humphrey earned his bachelor’s degree in architecture from the National Cheng Kung University, Taiwan, and an M.Sc. degree in computational design from the School of Architecture at CMU.

Fellowship Research: "Developing Stiffness Tunable Compliant Exoskeleton With Digital Twin"

Student Nur Yildirim sitting with cup of coffee

Nur Yildirim is an HCII Ph.D. student advised by John Zimmerman, the Tang Family Professor of Artificial Intelligence and Human-Computer Interaction. Nur's research focuses on supporting cross-functional AI teams in envisioning AI products and services. Her recent work in healthcare explores how AI capabilities can improve critical care practice in the intensive care unit. Prior to joining Carnegie Mellon, she worked as a design consultant in industry. She received her master’s and bachelor’s degrees in industrial design from METU in Turkey.

Fellowship Research: "Designing and Evaluating Human-AI Interactions for Increasing Adherence to Standard of Care in the Intensive Care Unit"