About

Adam Kurth

I am an incoming Ph.D. student in Biostatistics at Brown University, with academic training in mathematics, statistics, and computational methods. I recently completed a B.S. in Mathematics (Statistics) and am currently finishing an accelerated M.S. in Statistics at Arizona State University. My research spans Bayesian modeling, causal inference, machine learning, and applications in biomedicine—particularly in neuroimaging, protein structure analysis, and clinical diagnostics. I am especially drawn to problems in predictive modeling, uncertainty quantification, and statistical decision-making in public health and medicine.

For detailed research projects and roles, please visit the Research page.

Voice of the Patient — AZBIO

In this talk, I share insights from my long-term health journey and personal reflections.

ASU Graduate Overcomes Health Challenges

Click below to read about my academic and health journey, featured by ASU News:

ASU Graduate Overcomes Health Challenges

ASU Graduate Overcomes Health Challenges

How one student's resilience and passion for statistics helped him succeed after serious health setbacks.

Interview with Christian Gardner

In this conversation, I discuss my pathway through mathematics and statistics, the role of research in public health, and advice for aspiring statisticians.

Journey Through Mathematics and Statistics

Interview: A Journey Through Mathematics and Statistics

Exploring the intersections of math, stats, and space exploration through personal and academic experiences.

My Liver Transplant – Adam’s Story

My journey with transplantation and recovery, featured by Phoenix Children’s Hospital:

My liver transplant – Adam’s story

My Liver Transplant – Adam’s Story

Featured story on my experience overcoming life-threatening illness and pursuing education in STEM.

Skills and Interests

Statistical Methods: Bayesian inference, causal inference, regression, GLMs, survival analysis, NLP, machine learning.

Mathematics: Real analysis, topology (knot theory), numerical methods, probability, linear algebra.

Programming: Python, R, Bash, LaTeX, MATLAB, Java, Linux/CLI.

Tools: PyTorch, Scikit-Learn, Git, Sphinx, Tableau, Plotly, ggplot2.

Research Areas: Biostatistics, neuroimaging, protein folding, statistical computing, medical diagnostics, public health.

Outside research, I enjoy public speaking, reading philosophy, running, meditation, and guitar.

Scholarships & Awards

2024: NASA GRC Rising Star Nomination, BioXFEL Scholar, John W. Luttrell Children’s Network Scholarship

2023: Pediatric Cancer Research Foundation Scholar, Coats & Todd Overcoming Disability Scholar, Ruth Cheatham Foundation, HPFY Scholar

2022: Burress Foundation Underdog Scholar, Luttrell Children’s Network Scholar

2021: ASU Alumni Legacy Scholar

Degrees: B.S. in Mathematics (Statistics), Summa Cum Laude; currently pursuing M.S. in Statistics (4+1 Program)

Dean's List: Fall 2022 – Present

Vision for the Future

As I begin my Ph.D. in Biostatistics, I aim to advance flexible and interpretable Bayesian methods for real-world health applications. My goal is to bridge theory and practice in service of population health and clinical decision-making, while mentoring the next generation of statistical scientists.

For a more comprehensive overview, download the full CV below:

Download CV