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I'm a computational neuroscientist with a mathematics & computer science background and a decade of experience developing the mathematical formalism of integrated information theory (IIT), building scientific software (PyPhi; 150+ citations), and analyzing large-scale neural data. I'm now focusing on mechanistic interpretability and AI safety, which I believe is the most impactful use of my expertise and skills.
13 peer-reviewed publications: first-author in PLOS Computational Biology, Entropy, and eNeuro; co-author in Nature Neuroscience.
Anthropic Fellows finalist (top 130 of ~5,000 applicants).
Research Interests
Mechanistic interpretability and AI safety; machine consciousness and model welfare; neural geometry; integrated information theory (IIT); computational neuroscience
Education
Ph.D. in Neuroscience
University of Wisconsin–Madison
Thesis: Integrated Information Theory: Theoretical Developments & Empirical Applications
Advisor: Giulio Tononi
Sc.B. in Mathematics–Computer Science
Brown University
AI safety training
BlueDot Technical AI Safety Course & Project
Interpretability Research
Belief manifolds, and how to steer along them
Independent · BlueDot Technical AI Safety Project
- Reproduced Sarfati et al. (2026, Goodfire) "The Shape of Beliefs". LLMs represent in-context learned posteriors as curved manifolds; geometry-aware steering along either the primal manifold (activations) or dual manifold (linear field probes) changes the model's posterior with fewer side effects than naive linear steering. I connect this work to an earlier 'geometric turn' in computational neuroscience. The writeup drew a response from the paper's first author.
- Currently extending the method to evaluation awareness and natural-language tasks (translation / code-switching).
- Decomposed concept-injection introspection (Gemma-3 12B, Qwen-2.5 32B) into separable components: representation (what the model encodes about an injection) and report (the prompt-dependent late-layer circuitry that surfaces it), explaining apparent conflicts across prior protocols.
- Answered two open questions from Pearson-Vogel et al. (2026): the circuitry behind prompt-framing effects, and post-training's role in building it. Concurrent with Macar et al. (2026, Anthropic) and Lederman & Mahowald (2026).
Skills
ML & Interpretability: PyTorch, Hugging Face, TransformerLens, nnsight, repeng, SAE Lens, einops, nngeometry, bitsandbytes, scikit-learn, Weights & Biases
Programming Languages: Python, C++, R, JavaScript, LaTeX
Scientific Computing: NumPy, SciPy, Pandas, Matplotlib, Dask, Mathematica, HTCondor
Mathematical Foundations: Information theory, probability theory, causal inference, linear algebra, optimization, discrete mathematics, combinatorics
Experience
Researcher
Center for Sleep and Consciousness
University of Wisconsin–Madison
- Lead developer and maintainer of PyPhi, the standard open-source library for IIT research (paper)
- Developed a refinement of IIT's intrinsic information metric to measure the tradeoff between differentiation and specification (paper)
- Extended IIT's formalism to offer an account of perception (preprint)
Graduate Research Assistant
Center for Sleep and Consciousness
University of Wisconsin–Madison
- Designed and conducted large-scale two-photon calcium imaging experiments in mouse visual cortex in collaboration with the Allen Institute's OpenScope program, quantifying stimulus-evoked neurophysiological differentiation (eNeuro paper)
- Core contributor to the development of IIT's mathematical formalism; co-lead author of its most recent formulation, IIT 4.0 (PLoS Computational Biology paper)
Associate Systems Programmer
Center for Sleep and Consciousness
University of Wisconsin–Madison
- Conceived and built PyPhi
- Designed and implemented evolutionary algorithms for simulating neural network-controlled agents, analyzing their emergent dynamics using information-theoretic measures
- Conducted theoretical research contributing to the formal foundations of IIT
Publications
Lead author
- Mayner, W. G. P., Marshall, W., Tononi, G. (2026). Intrinsic Cause–Effect Power: The Tradeoff between Differentiation and Specification. Entropy, 28(4), 410. https://doi.org/10.3390/e28040410
- Mayner, W. G. P., Juel, B. E., Tononi, G. (2024, December 31). Intrinsic Meaning, Perception, and Matching. arXiv: 2412.21111 [q-bio]. https://doi.org/10.48550/arXiv.2412.21111
- Albantakis, L.*, Barbosa, L.*, Findlay, G.*, Grasso, M.*, Haun, A. M.*, Marshall, W.*, Mayner, W. G. P.*, Zaeemzadeh, A.*, Boly, M., Juel, B. E., Sasai, S., Fujii, K., David, I., Hendren, J., Lang, J. P., Tononi, G. (2023). Integrated Information Theory (IIT) 4.0: Formulating the Properties of Phenomenal Existence in Physical Terms. PLOS Computational Biology, 19(10), e1011465. https://doi.org/10.1371/journal.pcbi.1011465 [*co-lead author]
- Mayner, W. G. P., Marshall, W., Billeh, Y. N., Gandhi, S. R., Caldejon, S., Cho, A., Griffin, F., Hancock, N., Lambert, S., Lee, E. K., Luviano, J. A., Mace, K., Nayan, C., Nguyen, T. V., North, K., Seid, S., Williford, A., Cirelli, C., Groblewski, P. A., Lecoq, J., Tononi, G., Koch, C., Arkhipov, A. (2022). Measuring Stimulus-Evoked Neurophysiological Differentiation in Distinct Populations of Neurons in Mouse Visual Cortex. eNeuro, 9(1). https://doi.org/10.1523/ENEURO.0280-21.2021
- Mayner, W. G. P., Marshall, W., Albantakis, L., Findlay, G., Marchman, R., Tononi, G. (2018). PyPhi: A Toolbox for Integrated Information Theory. PLoS computational biology, 14(7), e1006343. https://doi.org/10.1371/journal.pcbi.1006343
Co-author
- Tononi, G., Albantakis, L., Barbosa, L., Boly, M., Cirelli, C., Comolatti, R., Ellia, F., Findlay, G., Casali, A. G., Grasso, M., Haun, A. M., Hendren, J., Hoel, E., Koch, C., Maier, A., Marshall, W., Massimini, M., Mayner, W. G., Oizumi, M., Szczotka, J., Tsuchiya, N., Zaeemzadeh, A. (2025). Consciousness or Pseudo-Consciousness? A Clash of Two Paradigms. Nat Neurosci, 28(4), 694–702. https://doi.org/10.1038/s41593-025-01880-y
- Findlay, G., Marshall, W., Albantakis, L., David, I., Mayner, W. G., Koch, C., Tononi, G. (2025, March 3). Dissociating Artificial Intelligence from Artificial Consciousness. arXiv: 2412.04571 [cs]. https://doi.org/10.48550/arXiv.2412.04571
- Bugnon, T., Mayner, W. G. P., Cirelli, C., Tononi, G. (2024). Sleep and Wake in a Model of the Thalamocortical System with Martinotti Cells. European Journal of Neuroscience, 59(4), 703–736. https://doi.org/10.1111/ejn.15836
- Gandhi, S. R., Mayner, W. G. P., Marshall, W., Billeh, Y. N., Bennett, C., Gale, S. D., Mochizuki, C., Siegle, J. H., Olsen, S., Tononi, G., Koch, C., Arkhipov, A. (2023). A Survey of Neurophysiological Differentiation across Mouse Visual Brain Areas and Timescales. Front. Comput. Neurosci., 17. https://doi.org/10.3389/fncom.2023.1040629
- Marshall, W., Grasso, M., Mayner, W. G. P., Zaeemzadeh, A., Barbosa, L. S., Chastain, E., Findlay, G., Sasai, S., Albantakis, L., Tononi, G. (2023). System Integrated Information. Entropy, 25(2), 334. https://doi.org/10.3390/e25020334
- Tononi, G., Boly, M., Grasso, M., Hendren, J., Juel, B. E., Mayner, W. G., Marshall, W., Koch, C. (2022). IIT, Half Masked and Half Disfigured. Behavioral and Brain Sciences, 45(e60), 1–19. https://doi.org/10.1017/S0140525X21001990
- Gomez, J. D., Mayner, W. G. P., Beheler-Amass, M., Tononi, G., Albantakis, L. (2021). Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements. Entropy, 23(1), 6. https://doi.org/10.3390/e23010006
- Findlay, G., Marshall, W., Albantakis, L., Mayner, W. G. P., Koch, C., Tononi, G. (2019). Dissociating Intelligence from Consciousness in Artificial Systems – Implications of Integrated Information Theory. Proceedings of the 2019 towards Conscious AI Systems Symposium, AAAI SSS19. https://ceur-ws.org/Vol-2287/short7.pdf
Presentations
28th Meeting of the Association for the Scientific Study of Consciousness (Heraklion, Greece)
Center for Psychedelic & Consciousness Research, Johns Hopkins University (virtual)
Neuroscience School of Advanced Studies (Venice, Italy)
Neuroscience Training Program, University of Wisconsin–Madison
Neuroscience Training Program, University of Wisconsin–Madison
Wisconsin Institute for Sleep and Consciousness
NEST Conference 2020 (virtual)
23rd Meeting of the Association for the Scientific Study of Consciousness (London, Ontario, Canada)
22nd Meeting of the Association for the Scientific Study of Consciousness (Krakow, Poland)
PhiFest, Wisconsin Institute for Sleep and Consciousness
Awards
Morgridge Institute for Research
23rd Meeting of the Association for the Scientific Study of Consciousness (London, Ontario, Canada)
Teaching
Teaching Assistant
Neuroscience School of Advanced Studies (Venice, Italy)
Teaching Assistant (graduate seminar)
Neuroscience Training Program, University of Wisconsin–Madison
Service
Neuroscience Instructor
University of Wisconsin–Madison
Developed and taught a curriculum on neuroscience topics to precollege students from underprivileged backgrounds
Guest Lecturer
University of Wisconsin–Madison
Invited lecture for high school students in the Advanced Learners Program: "What Is Consciousness?"