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Gainesville, FL, U.S.A. • saurabhr.neuroai@proton.me • saurabhr.github.io
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Ph.D. Cognitive Neuroscientist | Cognitive and Machine Psychology | Human-AI Alignment | NeuroAI
EDUCATION
Ph.D. Psychology: Behavioral & Cognitive Neuroscience University of Florida, USA | 2025
Dissertation: Reality Monitoring in Humans and Artificial Intelligence
M.Sc. Cognitive Science University of Allahabad, India | 2018
Thesis: Intentional Binding in Future-Directed Intentions
B.Sc. Physics Birla Institute of Technology, Mesra, India | 2016
TECHNICAL SKILLS
AI/ML & LLMs: Agentic workflows (LangChain/LangGraph), LLM evaluation & hallucination-detection pipelines, prompt engineering; PyTorch, Hugging Face, scikit-learn, Pydantic, Claude Code (agent testing/tooling)
NeuroAI: Linearizing encoding models, MEG/EEG (MNE), fMRI (Nilearn/SPM), UK Biobank predictive modeling
Stats & Evaluation: Bayesian hierarchical modeling (PyMC, brms), signal detection theory, mixed-effects models (lme4), metacognitive modeling
Data Engineering & MLOps: Python, R, MATLAB, Bash; Pandas, NumPy, Git/GitHub, Docker, SLURM/HPC
Visualization: seaborn, matplotlib, plotly, ggplot2
RESEARCH EXPERIENCE
Researcher: AI for Biomedical Health Outcomes 2026 – Present
University of Florida, Gainesville, FL
• Co-develop UF’s Master’s-level curriculum on Data Science and Agentic LLMs for AI for Biomedical Health Sciences (AIBHS), spanning Foundations, Clinical Application, and Basic Science tracks, part of the program cited in UF’s #1 AI-readiness ranking among large public universities (AIREDEX, 2026); build and maintain the AIBHS Faculty Hub and AI Passport Impact Project sites (20 hands-on modules).
• Built Psych Scanner-Primal, an optimized fork of Psych Scanner for the Prime Intellect Environments Hub, evaluating agentic systems under Reinforcement Learning with Verifiable Rewards (RLVR).
Research Assistant 2025 – 2026
Dr. Andreas Keil’s Lab, University of Florida, Gainesville, FL
• Advanced Psych Scanner from v0.1.0 to v0.4.0, building a harness that automates out-of-distribution (OOD) evaluation of LLMs across 800+ cognitive tasks, giving researchers a reproducible pipeline for running both standard and boutique cognitive paradigms.
Graduate Researcher 2020 – 2025
Dr. Brian Odegaard’s PAC-Lab & UF Department of Psychology, Gainesville, FL
• Discovered that LLM source-attribution accuracy reverses under episodic memory delay, tested across 2 experiments and 6 transformer-based LLMs (Gemma3, Llama3.3, Llama4), a hallucination-relevant failure invisible to single-turn benchmarks.
• Found that corrective feedback produces two distinct metacognitive failure modes, with failure severity tracking active rather than aggregate parameter count, a chain-of-thought-relevant self-knowledge gap that worsens, not improves, with scale (preprint, arXiv:2607.23927).
• Built psychological network models from 2,743 human participants and 6 LLMs (12B–272B parameters): human representational structure replicates across populations (r = 0.31–0.93) while no LLM tested reproduces it at any scale, suggesting a world model can be characterized purely from the structural relationships between internally generated experiences.
• Designed and ran matched experiments with 100+ human participants and parallel LLM simulations to test generalization of reality monitoring across task constraints, complemented by MEG temporal generalization decoding and fMRI encoding models predicting fMRI response from image memorability (NSD dataset), the same seen-vs-imagined question, in humans.
• Authored Psych Scanner (v0.0.1) solo, an open-source framework for running cognitive experiments on LLMs at scale, and built MetaSignal, a Python package for metacognitive/signal-detection analysis.
• Mentored 7 undergraduate researchers and taught a full segment of Physiological Psychology.
Research Assistant 2019 – 2020
Center of Behavioral and Cognitive Sciences, University of Allahabad, India
• Found stronger intentional binding (a measure of sense of agency) for predictive intermediate outcomes than non-predictive ones, replicated across three delays (300/500/700ms) and two contingency levels (OSF preprint).
Research Assistant 2018
Homi Bhabha Centre for Science Education, TIFR, Mumbai, India
• Contributed statistical analysis for Touchy-Feely Vectors (TFV), a gesture-based tool for teaching vectors, across two studies: a 266-student pilot (3 experimental, 3 control classrooms) where the experimental group reasoned differently about vectors and showed higher engagement (IEEE T4E 2019), and a 3-year field study (135 control vs. 131 experimental students) showing improved model-based reasoning in stronger students and engagement in average ones (Journal of Computer Assisted Learning, 2021).
PUBLICATIONS
Working Papers
[1] Ranjan, S., & Odegaard, B. Generalization of generation effect in reality monitoring.
Software
[2] [Preprint] Ranjan, S., Makwana, M., Sokratous, K., & Odegaard, B. (2026). Metasignal: A python package for comprehensive metacognitive analysis and decision-making. arXiv:2607.29093. https://arxiv.org/abs/2607.29093
[1] Ranjan, S., Sokratous, K., & Makwana, M. Psych Scanner: A Framework for Systematic Cognitive Evaluation of Large Language Models.
Theory and Empirical Peer-Reviewed & Preprints
[10] [Preprint] Ranjan, S., Sokratous, K., & Odegaard, B. (2026). Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory. arXiv:2607.23927. https://arxiv.org/abs/2607.23927
[9] [Preprint] Ranjan, S., & Odegaard, B. (2025). Psychological Imagination Networks Show Cross-Population Centrality and Clustering Alignment in Humans That Large Language Models Fail to Replicate. arXiv:2510.04391. https://arxiv.org/abs/2510.04391
[8] Ranjan, S., & Odegaard, B. (2024). Heterarchy or hierarchy? Insights from a new model of visual imagination. Physics of Life Reviews, 49, 74–76.
[7] Ranjan, S., & Odegaard, B. (2024). Reality monitoring and metacognitive judgments in a false-memory paradigm. Neuroscience Research, 201, 3–17.
[6] Maynes, R., Faulkner, R., Callahan, G., Mims, C. E., Ranjan, S., Stalzer, J., & Odegaard, B. (2023). Metacognitive awareness in the sound-induced flash illusion. Philosophical Transactions of the Royal Society B, 378(1886), 20220347.
[5] Chiasson, P., Boylan, M. R., Elhamiasl, M., Pruitt, J. M., Ranjan, S., Riels, K., … & Keil, A. (2023). Effects of neurofeedback training on performance in laboratory tasks: A systematic review. International Journal of Psychophysiology.
[4] Aggarwal, A., & Ranjan, S. (2022). How do undergraduate students reason about ethical and algorithmic decision-making? Proc. 53rd ACM Technical Symposium on Computer Science Education, 488–494.
[3] Karnam, D., Agrawal, H., Parte, P., Ranjan, S., Borar, P., Kurup, P. P., … & Chandrasekharan, S. (2021). Touchy feely vectors: A compensatory design approach to support model-based reasoning. Journal of Computer Assisted Learning, 37(2), 446–474.
[2] Karnam, D., Agrawal, H., Parte, P., Ranjan, S., Sule, A., & Chandrasekharan, S. (2019). Touchy feely affordances of digital technology for embodied interactions can enhance ‘epistemic access’. 2019 IEEE Tenth International Conference on Technology for Education (T4E), 114–121.
[1] [Preprint] Ranjan, S., & Srinivasan, N. (2019). Sense of agency for future-directed intentions. doi.org/10.31234/osf.io/qa93k.
INVITED TALKS
[2] Ranjan, S. (May, 2026). The Spark of Artificial Neuroscience: Psychologically-Grounded Evaluation of Large Language Models. Virtual invited talk, Autonomous Empirical Research Group + Laboratory for Automated Scientific Discovery of Mind and Brain (PI: Dr. Sebastian Musslick), Osnabrück University.
[1] Ranjan, S. (March, 2026). Controlling Imagery Generation and its Awareness. Virtual invited talk, Robert Reinhart Lab, Boston University.
SELECTED CONFERENCE POSTERS & TALKS
[8] Ranjan, S., & Odegaard, B. (2025). Psychological Imagination Networks in Humans and LLMs. Frontiers in NeuroAI, Kempner Institute Symposium, Harvard University.
[7] Ranjan, S., & Odegaard, B. (2025). Visual Imagination Networks in Humans and LLMs. Vision Sciences Society Annual Meeting, St. Pete, FL.
[6] Ranjan, S., & Odegaard, B. (2024). The Fragility of Reality Monitoring under Extraneous Factors. Psychonomic Society 65th Annual Meeting, NYC.
[5] Ranjan, S., & Odegaard, B. (2024). Reality Monitoring, Fast and Slow [Poster + Flash Talk]. Association for Psychological Science, San Francisco. Awarded Scott O. Lilienfeld APS Travel Award.
[4] Maw, M., Zhuang, L., Baltes, J., Ranjan, S., & Odegaard, B. (2024). Task demands and sensory externalization in reality monitoring. PGSO Undergraduate Research Forum, UF. Mentee won 3rd Prize.
[3] Dundigalla, S., Johnson, D., Roh, A., Ranjan, S., & Odegaard, B. (2024). Cognitive strategies in reality monitoring. PGSO Undergraduate Research Forum, UF.
[2] Ranjan, S., Baltes, J., Roh, A., & Odegaard, B. (2023). Confidence in reality monitoring judgments. Journal of Vision, 23(9), 4844.
[1] Ranjan, S., & Srinivasan, N. (2018). Intentional binding and future-directed intentions [Talk]. Annual Conference of Cognitive Science, IIT-Guwahati, India.
AWARDS & FELLOWSHIPS
• 2025: College of Liberal Arts and Sciences Travel Award, University of Florida
• 2025: Threadgill Dissertation Fellowship, University of Florida
• 2024: Scott O. Lilienfeld APS Travel Award, Association for Psychological Science
• 2024–2025: UF Department of Psychology Travel Awards (×4)
• 2020–2025: Graduate Student Fellowship, UF Department of Psychology
• 2016–2018: Graduate Merit Scholarship, Centre of Behavioral & Cognitive Sciences, University of Allahabad