Zhengjia Wang

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, USA.

Dr. Wang is a Research Associate at the Beauchamp Lab.

His research focuses on cognitive computational neuroscience and on developing statistical machine learning tools and software packages that help researchers make reproducible scientific discoveries. His main areas are interpretable machine learning, functional data analysis, and multiple testing procedures, with applications to human brain-computer interfaces (BCI), including intracranial electroencephalography (iEEG) and deep brain stimulation (DBS).

• Google Scholar, ORCID
• GitHub
• Email: zhengjia.wang at pennmedicine dot upenn dot edu

Education

• Ph.D., Statistics, Rice University (2016-2021)
• M.A., Statistics, Rice University (2016-2017)
• B.S., Statistics, University of Science and Technology of China (2009-2013)

Publications

Peer-reviewed journal articles, newest first. Conference abstracts and preprints are listed on Google Scholar.

• Eckstein K, Androulakis A, Dao TT, …, Wang Z, …, Rorden C. Seamless neuroimaging visualization: The NiiVue wrapper ecosystem. Aperture Neuro, 2026; 6. doi:10.52294/001c.167815
• Tan X, Bersali A, Ingram K, …, Wang Z, …, Li M. Artificial intelligence (AI)-facilitated analysis of single-image tissue Doppler signal to characterize right ventricular dysfunction. Echocardiography, 2026; 43(4):e70447. doi:10.1111/echo.70447
• Wang J, Lesage AC, Zhou O, Malagaris I, O’Leary S, Camarillo Rodriguez L, Silveira DC, Wang Z, Zhang Y, Karas PJ. Building an ecosystem of seizure localization methods: Neural fragility as the first step. eNeuro, 2026; 13(3):ENEURO.0340-25.2026. doi:10.1523/ENEURO.0340-25.2026
• Ma H, Wang Z, Zhang X, Magnotti JF, Beauchamp MS. A deep neural network model of audiovisual speech recognition reports the McGurk effect. Psychonomic Bulletin & Review, 2026; 33(2):84. doi:10.3758/s13423-025-02846-8
• Nho YH, Qiu L, Seilheimer RL, …, Wang Z, …, Halpern CH. Human orbitofrontal neural activity is linked to obsessive-compulsive behavioral dynamics. Cell, 2026; 189(3):739–747.e8. doi:10.1016/j.cell.2025.12.037
• O’Leary S, Lesage AC, Camarillo-Rodriguez L, …, Wang Z, …, Karas PJ. Integrating data across oscillatory power bands predicts the seizure onset zone in focal epilepsies. Brain Communications, 2026; 8(1):fcag008. doi:10.1093/braincomms/fcag008
• Zhang Y, Magnotti JF, Zhang X, Wang Z, Yu Y, Davis KA, Sheth SA, Chen HI, Yoshor D, Beauchamp MS. Stereoelectroencephalography reveals neural signatures of multisensory integration in the human superior temporal sulcus during audiovisual speech perception. Journal of Neuroscience, 2025; 45(42):e1037252025. doi:10.1523/JNEUROSCI.1037-25.2025
• Wang Z, Magnotti JF, Zhang X, Beauchamp MS. YAEL: Your Advanced Electrode Localizer. eNeuro, 2023; 10(10):ENEURO.0328-23.2023. doi:10.1523/ENEURO.0328-23.2023
• Subash P, Gray A, Boswell M, …, Wang Z, …, Duncan D. A comparison of neuroelectrophysiology databases. Scientific Data, 2023; 10(1):719. doi:10.1038/s41597-023-02614-0
• Metzger BA, Kalva P, Mocchi MM, …, Wang Z, …, Bijanki KR. Intracranial stimulation and EEG feature analysis reveal affective salience network specialization. Brain, 2023; 146(10):4366–4377. doi:10.1093/brain/awad200
• Wang Z, Magnotti JF, Beauchamp MS, Li M. Functional group bridge for simultaneous regression and support estimation. Biometrics, 2023; 79(2):1226–1238. doi:10.1111/biom.13684
• Magnotti JF, Wang Z, Beauchamp MS. RAVE: Comprehensive open-source software for reproducible analysis and visualization of intracranial EEG data. NeuroImage, 2020; 223:117341. doi:10.1016/j.neuroimage.2020.117341
• Metzger BA, Magnotti JF, Wang Z, Nesbitt E, Karas PJ, Yoshor D, Beauchamp MS. Responses to visual speech in human posterior superior temporal gyrus examined with iEEG deconvolution. Journal of Neuroscience, 2020; 40(36):6938–6948. doi:10.1523/JNEUROSCI.0279-20.2020

Open-Source Toolbox

• Reproducible Analysis and Visualization of iEEG (RAVE) (rave.wiki, supported by NIH R01MH133717, U01NS113339, R24MH117529)
  • ravepipeline: Reproducible pipeline framework for scientific studies
  • ravetools: Signal-processing and image-registration toolbox for iEEG
  • ravecore: Core RAVE package for handling gigabyte-scale iEEG and DBS datasets
  • ravedash: Dashboards for interactive scientific visualization
• Your Advanced Electrode Localizer (YAEL, video demo, code)
• Web-based 3D brain viewer (threeBrain)
• Imaging and electrophysiology data IO
  • bidsr: Parser for the Brain Imaging Data Structure (BIDS)
  • readNSx: Reader for NEV/NSx files (Blackrock Neurotech, Ripple Neuro) and BCI2000 (a general-purpose brain-computer interface system) recordings
  • ieegio: Swiss Army knife for iEEG, DBS, and medical imaging file formats
• Out-of-memory array (tensor) storage (filearray)
• Functional group-bridge regression (spfda)
• Overlapping cluster detection with functional FDR control (package under development; focr, ICSA 2023)
• iEEG signal processing toolbox (ravetools)
• Interface to ANTs (Advanced Normalization Tools; rpyANTs)
• Isolated Python environments for reproducible R pipelines (rpymat)
• Modular Shiny dashboard templates with AI-agent support (shidashi)