Center for Machine Learning and Health

2023 Fellowships in Digital Health Innovation

Meet the 2023 CMLH Fellows in Digital Health Innovation

Photo of PhD student Peiran Jiang

Peiran Jiang is a Ph.D. student in the Computational Biology Department, advised by Professor Jose Lugo-Martinez. Prior to joining CMU, Peiran earned his bachelor's degree in bioinformatics from Huazhong University of Science and Technology. His research mainly focuses on the development of novel computational methods and pipelines for accelerating knowledge discovery in biomedicine. 

Fellowship Research: "Inferring the Phenotypic Impact of Variants of Liquid–Liquid Phase Separation Proteins"

Photo of PhD student Yubo Li

Yubo Li is a Ph.D. student in information systems, advised by Rema Padman. His research centers around the development of explainable AI systems, with a focus on more effective, efficient and transparent healthcare decision-making. He seeks to build robust AI systems that revolutionize the way we approach healthcare challenges and empower medical professionals to make informed choices that improve patient outcomes. Yubo received a bachelor’s degree in applied mathematics from the University of California San Diego and a master’s degree in information systems from CMU.

Fellowship Research: "Empowering Decision-Making in Healthcare With Explainable AI for Major Chronic Diseases"

Photo of PhD student Hatice Gökçen Güner

Hatice Gökçen Güner is a Ph.D. candidate majoring in computational mechanics advised by Human-Computer Interaction Institute faculty member Alexandra Ion and Kaushik Dayal, a professor in the Civil and Environmental Engineering Department. Her research focuses on soft material analysis and inverse design methods. Previously, Hatice completed her bachelor’s degree in civil engineering at Izmir Institute of Technology in Turkey. 

Fellowship Research: "Machine Learning Driven Metamaterial Design for Customizable Prosthetic Sockets With Real-Time High-Fidelity Sensors"

Photo of PhD student Mostofa Rafid Uddin
Mostofa Rafid Uddin is a Ph.D. student in the Computational Biology Department, advised by Min Xu. His research aims to develop automated annotation-efficient computer vision methods for in situ biological shape analysis from bioimages, particularly cryo-electron tomography images. Currently he focuses on large-scale comparative analysis of organelle and macromolecular shape attributions across multiple cell populations. Prior to joining CMU, Mostofa earned his bachelor’s degree in computer science and engineering from Bangladesh University of Engineering and Technology. Mostofa has published his research works in top-tier venues like CVPR, Bioinformatics, Nature Cancer, etc.

Fellowship Research: "Leveraging Cryo-ET Imaging Technology to Improve Patient Care for Neurodegenerative Diseases by Identifying Subcellular Biomarkers"

Photo of PhD student Nahom Mossazghi
Nahom Mossazghi is a Ph.D. student in the Biomedical Engineering Department,  advised by Assistant Professor Sossena Wood. His research aims to use deep learning to develop a novel approach to predict the severity of sickle cell disease (SCD) from resting state functional magnetic resonance imaging (fMRI) data. SCD is a genetic disorder caused by a mutation in the hemoglobin gene that affects millions of people worldwide. He is originally from Eritrea and completed his bachelor’s degree in neuroscience at the University of Minnesota Twin–Cities and his master's at CMU.

Fellowship Research: "Deep Learning-Based Resting State fMRI Analysis for Predicting Severity of Sickle Cell Disease"

Photo of PhD student Sampada Acharya

Sampada Acharya is a Ph.D. student in the Mechanical Engineering Department, advised by Associate Professor B. Reeja-Jayan. She earned her bachelor’s degree from Mumbai University in India and her master’s degree in mechanical engineering from CMU prior to starting her doctoral program. Her research focuses on design, fabrication and characterization of functionalized, nature-inspired materials that will optimize pathogen (e.g., bacteria, virus, fungi) collection from target surfaces in an infectious environment. These materials will be integrated into a robot for autonomous surface navigation and sampling to minimize human interaction with contaminated surfaces.

Fellowship Research: "Fabrication of Nature-Inspired Structures for Clinical Environment Monitoring"

Photo of PhD student Bardienus Duisterhof
Bardienus Duisterhof is a Ph.D. student in the Robotics Institute, advised by Jeffrey Ichnowski. His research interests include leveraging physics-based priors in neural implicit functions for deformable object manipulation. He is excited about applying fundamental advances in perception and manipulation to advance healthcare robotics in areas where automation is most needed. Bardienus received his bachelor’s and master’s degrees from Delft University of Technology in the Netherlands.

Fellowship Research: "Physics-Augmented Neural Implicit Functions With Deformable Object Manipulation for Operational Improvement in Hospitals"

Photo of PhD student Asal Yunusova

Asal Yunusova is a Ph.D. student in the Psychology Department, advised by Professor J. David Creswell. She earned her bachelor's degree with a double major in psychology and social behavior and social ecology from the University of California Irvine. Her research focuses on assessing the efficacy of a mindfulness-based digital application in improving health outcomes among adolescent patients diagnosed with irritable bowel syndrome, as well as assessing user-related perceptions and experiences with the application.

Fellowship Research: "Digital Mindfulness Training for Adolescents With Irritable Bowel Syndrome"

Photo of PhD student Zulekha Karachiwalla

Zulekha Karachiwalla is a Ph.D. student in the Robotics Institute advised by Assistant Professor Henny Admoni and Assistant Professor Zackory Erickson. Her research focuses on leveraging user input to guide the design of accessible robotic systems, particularly in addressing the needs of the healthcare community and optimizing the design of robotic solutions. She received her bachelor's degree in computer engineering from the University of Maryland Baltimore County. 

Fellowship Research: "Understanding Wound Care Techniques To Inform Robotic Design Decisions"