Wenhao Zhang, Ph.D. Assistant Professor Endowed Title Lupe Murchison Foundation Scholar in Medical Research School Medical School Department Lyda Hill Department of Bioinformatics | Peter O'Donnell Jr. Brain Institute Graduate Programs Biomedical Engineering, Neuroscience Biography Since November 2021, Wenhao Zhang has been appointed as Assistant Professor in the Lyda Hill Department of Bioinformatics, and had his secondary appointment in the Peter O’Donnell Jr. Brain Institute. He is awarded as the Lupe Murchison foundation scholar in medical research. Before establishing his lab at UT Southwestern, Wenhao did his postdoc research on Theoretical and Computational Neuroscience at the University of Chicago, the University of Pittsburgh, and Carnegie Mellon University. Dr. Zhang’s research focuses on developing biologically plausible normative theories that address fundamental questions of information processing in the brain and artificial systems. His research aims to provide theoretical explanations of system neuroscience experiments, as well as shed novel insight from neural systems to develop new intelligent algorithms. To achieve this goal, he has been maintaining intensive collaborations with experimental neuroscientists and psychologists, and computer scientists. See his Google Scholar page for the full list of his publications. Research Interest 1. Theoretical and Computational Neuroscience 2. Neural coding and Bayesian inference 3. Neural network dynamics (Continuous attractor network, Spiking network) 4. Multisensory integration and Causal inference 5. Invariant and equivarient representation in neural circuits Publications Featured Publications Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons W.H. Zhang, S. Wu, K. Josic, B. Doiron Nature Communications 2023 A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation J Zuo, X Liu, Y Wu, S Wu, W.H. Zhang Advances in Neural Information Processing Systems (NeurIPS) 2023 Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors W.H. Zhang*, Y.N. Wu, S. Wu, Advances in Neural Information Processing Systems (NeurIPS) 2022 Distributed sampling-based bayesian inference in coupled neural circuits W.H. Zhang, T.S. Lee, B. Doiron, S. Wu bioRxiv 2020 Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation WH Zhang, H Wang, A Chen, Y Gu, TS Lee, KYM Wong, S Wu eLife 2019 8 e43753 A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits W.H. Zhang, S. Wu, B. Doiron, T.S. Lee Advances in Neural Information Processing Systems (NeurIPS) 2019 3799-3808 Decentralized multisensory information integration in neural systems W.H. Zhang, A. Chen, M.J. Rasch, S. Wu The Journal of Neuroscience 2016 36 2 532-547 Continuous attractor neural networks: candidate of a canonical model for neural information representation S. Wu, K.Y.M. Wong, C.C.A. Fung, Y. Mi, W.H. Zhang F1000Research 2016 5 Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks X. Dong, Z. Ji, T. Chu, T. Huang, W.H. Zhang*, Si Wu* Advances in Neural Information Processing Systems (NeurIPS) 2022 Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells. T. Chu, Z. Ji, J. Zuo, W.H. Zhang, T. Huang, Y. Mi, S, Wu Advances in Neural Information Processing Systems (NeurIPS) 2022 Results 1-10 of 10 1 Honors & Awards Lupe Murchison Foundation Scholar in Medical Research (2021)
