Center for Machine Learning and Health

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 2023-2024 CMLH Translational Fellows

Photo of CMLH Fellow Yuxin Guo

Yuxin Guo is a Ph.D. student in the Neural Computation program, advised by Professor Pulkit Grover. Yuxin is broadly interested in brain computer interfaces and neural stimulation, which have potential applications in modulating the brain’s reward circuit and treating neurological diseases. In particular, her current research involves using optimization and data-driven algorithms to design neural stimulation parameters to target deep brain regions minimally invasively. Prior to her Ph.D. studies, Yuxin completed her bachelor’s degree in electrical and computer engineering at CMU, with an additional major in biomedical engineering. 

Fellowship Research: "DeepFocus: A Novel Minimally Invasive Stimulation Platform To Safely Control Neural Activity at Deep-Brain Targets in the Reward Circuit"

Photo of CMLH Fellow Zhixiong Li.

Zhixiong (Jack) Li is a Ph.D. student in the Mechanical Engineering Department, advised by Professor Eni Halilaj. Jack’s research focuses on investigating precision rehabilitation to prevent post-traumatic osteoarthritis through wearable technologies and computer vision. Currently, he collaborates with clinicians at the University of Pittsburgh Medical Center to predict long-term changes in knee cartilage health from physical therapy performance. Prior to joining CMU, Jack completed his bachelor’s degree in biomedical engineering at the University of California San Diego, and master’s degree in biomedical engineering at Duke University.

Fellowship Research: "Automated Triaging of Total Joint Replacement Patients Through Deep Learning"

Photo of CMLH Fellow Yingtao Luo.

Yingtao Luo is a Ph.D. student in information systems, advised primarily by Professor Rema Padman in Heinz College. Yingtao's research aims to create accurate and explainable machine learning platforms that collaborate with clinicians and facilitate medical decision-making to optimize patient outcomes. His current research focuses on building contextualized simulations to inform sequential decision-making agents. He is also working on clinical foundation models to accelerate the predictive modeling in the health domain. He received his bachelor’s degree in applied physics at Huazhong University of Science and Technology, and his master’s degree in computer science and systems at the University of Washington.

Fellowship Research: "Sequential Decision-Making Agent for Heart Transplantation"

Photo of CMLH Fellow Akhil Padmanabha

Akhil Padmanabha is a Ph.D. student in the Robotics Institute, co-advised by Professor Zackory Erickson and Carmel Majidi, the Clarence H. Adamsen Professor of Mechanical Engineering. Akhil’s research focuses on developing sensors and algorithms to improve healthcare outcomes and assistive interfaces to enable individuals with loss of hand function to control robots and perform physical activities of daily living again. He completed his bachelor’s degree in mechanical engineering at the University of California, Berkeley.

Fellowship Research: "Tracking Scratching in Patients with Chronic Itch Using Wearable Devices"

Photo of CMLH Fellow Prasoon Patidar.

Prasoon Patidar is a Ph.D. student in the Software and Societal Systems Department (S3D), advised by Professor Yuvraj Agarwal. His research focuses on leveraging large-scale foundational models, user-focused sensing systems and machine learning to enhance ubiquitous sensing for user health and wellness. Prasoon's current work involves developing an AI-system that uses low-cost sensors and human-AI interaction techniques to support dementia patients during their daily routines. Before joining CMU, he worked as a data scientist in industry. He completed his bachelor's degree in computer science and engineering at the Indian Institute of Technology (IIT) Delhi.

Fellowship Research: "Assisting Dementia Patients With Multi-Step Activities Using Privacy-Sensitive Ambient Sensors"

Photo of CMLH Fellow Kimi Wenzel

Kimi Wenzel is a Ph.D. student in the Human-Computer Interaction Institute (HCII) advised by Professors Geoff Kaufman and Laura Dabbish. Her research focuses on measuring and mitigating the mental health harms of emerging AI technologies. This year, she is assessing a conversational design intervention for voice-based healthcare tools. Kimi received her bachelor's degree from Barnard College at Columbia University.

Fellowship Research: "Enhancing Marginalized Practitioners and Patients' User Experience With Healthcare Technologies: A Voice-Based Design Intervention"