Sibo Wang-Chen

I am a PhD candidate at the Neuroengineering Laboratory at EPFL, the Swiss Federal Institute of Technology in Lausanne. I am interested in reverse-engineering the neural controller underlying agile and robust animal behaviors. Specifically, I build biologically constrained artificial neural networks to reproduce the behavior of Drosophila, the common fruit fly. I hope these models will teach us about fundamental neurobiology and inspire more efficient control architectures for robotics and AI. I am a Boehringer Ingelheim Fonds PhD fellow.

Before my PhD, I worked at Habiterre, a company devoted to ecosystems modeling and sustainability benchmarking. I led an NSF-funded project on systematically evaluating farmland resilience using satellite images and machine learning. I received my bachelor’s and master’s degrees from the University of Illinois at Urbana-Champaign.

Highlights

2023: Fruit fly digital twin: I’m excited to share NeuroMechFly 2.0, our framework for simulating embodied sensorimotor control in adult Drosophila. Paper.
2023: Descending neuron networks: I’m honored to be a part of our study on how networks of descending neurons transform command-like signals into population-based behavioral control
2019–2021: Habiterre, a company devoted to sustainable agriculture utilizing satellite images and machine learning. I led the research activities at Habiterre in its first two years.
2017–2018: Gravitational astrophysics: I have also briefly worked on simulating gravitational waves and building deep learning models for observational astronomy. See my CV for publications.