Hangwen Guo
Associate professor
Brief Bio
Dr. Guo received his B.S. degree from Fudan University (2007), and Ph.D. degree from University of Tennessee, Knoxville (2013). He worked as postdoctoral fellow at Louisiana State University from 2013-2016, and then promoted as associate professor. He joined Fudan University as research associate professor in 2018. He has published more than 50 papers with total citations more than 1300. He also has multiple invited talks including APS March Meeting etc, and serves as reviewer for Nature Commun., Nano Lett. etc.
Research Interest
1) Physical neural networks: devices and architectures; 2) Spintronics and spin-based probablistic computing devices, architectures and algorithms
Selected Publications:
1. Y. Wang et al., “Superior probabilistic computing using operationally stable probabilistic-bit constructed by manganite nanowire”, National Science Review (IF=16.3) 12, nwae338 (2025).
2. C Niu. et al., “A self-learning magnetic Hopfield neural network with intrinsic gradient descent adaption”, PNAS 121, e2416294121 (2024).
3. W. Yu et al., “Physical neural networks with self-learning capabilities” Sci. China. Phys. Mech. & Astron., 67, 287501 (2024).
4. L. Deng et al., “Polarization-dependent photoinduced metal-insulator transitions in manganites” Science Bulletin (IF=18.9) 69, 183 (2024).
5. W. Hu et al., “Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing” Nature Communications 14, 2562 (2023).
6. C. Niu et al., “Implementation of artificial neurons with tunable width via magnetic anisotropy” Appl. Phys. Lett. 119, 204101 (2021).
