Scholar

Ling-Wei Kong (孔令威)

Google Scholar ID: Ra4lQKgAAAAJ

Cornell University

Nonlinear DynamicsRecurrent Neural NetworksReservoir ComputingComplex Networks

Citations & Impact

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Citations

621

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Publications

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Publications

20 items

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Resume (English only)

Academic Achievements

In June 2024, published a paper titled 'Reservoir-computing based associative memory and itinerancy for complex dynamical attractors' in Nature Communications, which was featured as the editor’s highlight in AI and machine learning and Applied physics and mathematics, and listed in the special collection of Neuromorphic Hardware and Computing. In December 2023, a paper titled 'Effects of growth feedback on gene circuits: A dynamical understanding' was accepted by eLife.

Research Experience

Currently a Schmidt AI in Science Postdoctoral Fellow at Cornell University, working in Prof. Andrew M Hein's lab. During his PhD, he focused on applying machine learning techniques (such as reservoir computing) to problems in the fields of nonlinear dynamics and complex systems, and vice versa, studying problems in machine learning from a dynamic point of view (such as multistability and basin structure in RNN).

Education

Background

Research interests include nonlinear dynamics, machine learning, and complex systems, with a focus on addressing pressing challenges in ecology. Completed a PhD under the supervision of Prof. Ying-Cheng Lai at Arizona State University and received the Dean's Dissertation Award.

Miscellany