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About Me

Yunshi Wen Ph.D Student Department of Electrical, Computer, and Systems Engineering School of Engineering Rensselaer Polytechnic Institute

I am current pursuing my Ph.D. degree at Rensselaer Polytechnic Institute advised by Professor Agung Julius. My broad research interests include machine learning, reinforcement learning, robotics, and control systems. I am particularly interested in interpretable machine learning, neuro-symbolic learning, and their applications in time-series analysis, robotics, and control.

I am currently working on the following topics/projects:

• Interpretable Foundation Models for Time-Series Analysis
• Vision-based Embodied Agents
• Machine Learning Models for Human Circadian Rhythm Modeling and Entrainment

News

• Jan. 2025: Our paper on interpretable times series classification is accepted by ICLR 2025.
• Jan. 2025: Our paper on data-driven circadian rhythm modeling and control is accepted by ACC 2025.
• Sep. 2024: Our paper on interpretable time series foundation model is accepted by NeurIPS 2024.
• July 2024: Our paper on data-driven model for circadian rhythm modeling is published in EMBC 2024.
• Dec. 2023: Our paper on optimal control of discrete-time multivariate point processes is published in CDC 2023.
• June 2023: Our paper on motion profile optimization in industrial robots using RL is published in AIM 2023.
• May 2023: I will join IBM Research as an extern (intership program of the RPI-IBM AIRC program) working on interpretable models for time-series analysis.
• May 2023: Our paper on motion profile optimization in industrial robots is published in ICRA 2023.
• May 2023: Our paper on weighted clock logic point process is published in ICLR 2023.