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Case Western Reserve, Computer and Data Science, Class of 2027

Yao is dedicated to advancing knowledge in the field of deep learning, particularly focusing on areas such as federated learning, model compression, data distillation, generative models, and language models.

Case Western Reserve, Computer Science, Class of 2029

Mu Sheng is researching machine learning and security.

Case Western Reserve, Computer and Data Science, Class of 2026

Runchao’s primary interests are distributed learning, AI and security.

Case Western Reserve, Modeling and Biomimetic Stimulation Paradigm Development, Class of 2027

Roberto graduated from the University of Arizona with a B.S. in Mechanical Engineering and minors in French and Mathematics. He completed 4 years of undergraduate research in device development in the Gutruf Lab, and is a recipient of the Astronaut Scholarship Foundation Scholarship and the National Science Foundation Graduate Research Fellowship.

Case Western Reserve, Neuroengineering, Class of 2024

Nabeel’s research focuses on sensorimotor integration of peripheral nerve stimulation with the basic motor system.

Case Western Reserve, Biomedical engineering, Class of 2024

Case Western Reserve, Neuroengineering, Class of 2024

Leah’s research is focused on evaluating how multiple perception points are integrated and perceived, and how temporal properties of stimulation may alter the final sensation.

Case Western Reserve, Biomedical engineering, Class of 2025

Vlad studies optimizing nerve stimulation selectivity using multipolar electrical stimulation.

Case Western Reserve, Neuroengineering, Class of 2026

Susan researches peripheral neural interfacing for tactile sensation.

Case Western Reserve, Biomedical engineering, Class of 2026

Rachel uses peripheral nerve stimulation to provide the sense of touch across realities.

Case Western Reserve, Biomedical engineering, Class of 2027

Laura’s research examines user experience and performance in the context of human-in-the-loop (HITL) systems through a combination of physiological, functional, and subjective measures. The goal is to study how tactile feedback and other informational HITL interface elements affect phenomenological outcomes like embodiment.

Associate Professor
Surgeon, Biotechnology Translation & Healthcare Applications
Case Western Reserve University

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