About me

I’m Yiqi Jiang, currently a PhD candidate in Electrical Engineering at Stanford University, advised by Prof. Mark Schinitzer and Prof. Scott Linderman. I obtained my Bachelor degree in Electrical and Computer Engineering, Computer Science, and a minor in Applied Mathematics in 2022 from Cornell University, where I worked with Prof. Peter Doerschuk on biomedical images processing.

I am interested in the dynamics of neural activity within and across brain regions as they relate to motor control, reinforcement learning, and brain-machine interfaces. My approach involves computational analyses of large-scale neural activity patterns, and I am especially interested in bidirectional approaches that take neural dynamics as inspiration for improving machine learning and robotics, as well as using methods from these engineering fields toward understanding the brain.

Awards

• Mind, Brain, Computation and Technology (MBCT) Student Membership Program, Wu Tsai Neuroscience (2023 - Present)
• Stanford Shenoy-Simons Foundation Grant (2025-present)

NEWS

• I am elected as the receiver of the Stanford Shenoy-Simons Foundation Grant.
• Our paper Extracting task-relevant preserved dynamics from contrastive aligned enrual recordings is accepted by NeurIPS 2025 as a spotlight poster.
• I am hosting an MBCT seminar featuring speaker Prof. Cythia Mossn from John Hopkins University.
• Our paper ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets is accepted by NeurIPS 2024.