CV

Raghav Madan
raghavmadan2010@gmail.com · LinkedIn · +1 (412) 636-2649
Seattle, WA, USA

Interests

Spatial neuroscience modeling · Human cognition · Neurodegenerative science · Neurodevelopmental science · Health tech innovation · Neurotech

Education

• Ph.D. Biomedical and Health Informatics, University of Washington, USA (2020 – 2026)
  Dissertation: NeuroPathPredict — A data-driven paradigm to map the distribution of Alzheimer’s disease neuropathology.

• M.S. Engineering and Technology Innovation Management, Carnegie Mellon University, USA (2019 – 2020)

• B.E. Mechanical Engineering, Manipal Institute of Technology, India (2010 – 2014)

Technical Skills

• Programming languages: Python, R, MATLAB, Bash, SQL, Linux, Java
• Machine learning libraries: SciPy, Scikit-learn, TensorFlow, PyTorch, glmnet, PySpark
• Tools & frameworks: JupyterLab, Git, Bitbucket, VS Code, Docker, LaTeX
• ML models & techniques: Linear/Logistic Regression, Decision Trees, XGBoost, Random Forest, K-Means, Lasso/Ridge/Elastic net, PCA, LSTM, RNN, Universal Kriging

Research Experience

Research Associate, University of Washington (2020 – present)
Dr. Paul Crane, Dr. John Gennari — ACT study

• Developed NeuroPathPredict (NPP), a spatial modeling framework predicting Alzheimer’s pathology from integrated neuroimaging and histopathology data.
• Created Integrated Brain Information System (I-BIS), a customized brain coordinate system aligning structural and functional brain maps, with custom covariate engineering.
• Applied and benchmarked advanced spatial modeling techniques, including universal Kriging, for prediction of regional pathology spread.
• Deployed computationally intensive models on cloud infrastructure (AWS & Azure) for scalable neuroimaging analysis and reduced runtime for spatial inference.
• Conducted statistical comparison of cognitive classification approaches for mild cognitive impairment (MCI) using real-world cohort data; performed psychometric norming and sensitivity analyses.

Research Associate, Carnegie Mellon University (2019 – 2020)
Dr. Timothy Verstynen — Cognitive Axon Lab

• Preprocessed and analyzed fMRI datasets to investigate network-level mechanisms of cortico-basal-ganglia-thalamus loops in human decision-making.
• Applied standard neuroimaging workflows (fMRIPrep) and developed custom Python scripts for signal cleaning, motion correction, and ROI extraction.

Research Assistant, University of California San Francisco (2019)
Dr. Theodore Zanto — Neuroscape Lab

• Conducted a neuro-stimulation study to assess working memory and multi-tasking improvement using EEG, MRI, and tACS.
• Conducted market and feasibility research on digital therapeutic interventions for mental health, contributing to early-stage translational efforts in neurotechnology.

Professional Experience

Manager, Research & Development, Michelin India Technology Center (2016 – 2018)

• Led cross-functional team of 16 engineers delivering analytics-driven product improvements.
• Improved product quality from 85% → 90% via statistical process control.
• Reduced defect losses by ~$100K annually through automated audit workflows.
• Managed $350K annual R&D budget using data-centered optimization.

Product Design Engineer R&D, Michelin India Technology Center / Michelin Thailand (2014 – 2016)

• Led technical transfer of product portfolio across Asia and Europe.
• Filed two design patents supporting Michelin’s innovation pipeline.
• Standardized data workflows, reducing design cycle time by ~80%.

Publications

• Madan R. (2026). NeuroPathPredict: A data-driven paradigm for spatial modeling of Alzheimer’s Disease neuropathology. Ph.D. Dissertation, University of Washington.
• Madan R. et al. (2026). QNPtoVox: A methods pipeline for mapping 2D quantitative neuropathology to 3D MNI voxel space. (Under review)
• Bond K., Rasero J., Madan R., et al. (2023). Competing neural representations of choice shape evidence accumulation in humans. eLife. Link
• Eppig J.S., Madan R., et al. (2021). Comparison of actuarial and conventional MCI criteria in a community-based prospective cohort study: The Adult Changes in Thought (ACT) study. Alzheimer’s & Dementia. Link

Conferences and Talks

• Research talk — SEA-AD/Allen Institute AD Analysis Working Group meeting (November 2025).
• Poster — Center for Neural Circuit Mapping conference (August 2025).
• Research talk — Research in Progress Seminar (RIPS), University of Washington (October 2024).
• Poster — UW Alzheimer’s Disease Research Center (ADRC) REC symposium (September 2022).

References

References can be made available on request.