Teaching & advising

Graduate instruction with hands-on advising

Core teaching includes BIOS 667 (longitudinal modeling) and BIOS 735 (statistical computing), complemented by advising, office hours, and workshops for Gillings and Lineberger students.

Teaching evaluations consistently excellent (1.11-1.44 on 1-5 scale, where 1 is best, across all courses 2018-2024).

BIOS 735 course site
3 core graduate courses taught
5 current mentees
12 mentees advised
5 years leading LCCC T32 workshops

Course lineup

Courses taught

Graduate core

BIOS 667 · Applied Longitudinal Data Analysis

GEEs, mixed models, joint modeling, and missing-data tactics grounded in public health and medical case studies. Course re-implemented from scratch with lectures embedding live R code examples and illustrations, complemented by AI-friendly assignments that emphasize reproducible workflows.

Canvas modules + R Markdown labs SAS templates for regulatory deliverables

Computing

BIOS 735 · Statistical Computing

Machine learning, git/GitHub, simulation, optimization, and package development for translational teams.

Project-based, reproducible deliverables Open-source code reviews
View syllabus

Workshops

Reproducible oncology analytics

Git, Quarto notebooks, and genomic-study case studies tailored for LCCC T32 trainees.

LCCC T32 trainees Genomic reproducibility labs

Mentoring & advising

  • Currently mentoring five PhD students in Biostatistics.
  • Five completed PhD advisees (co-advised with Drs. Ibrahim, Love, Kosorok) with 100% placement at leading institutions: Dana-Farber, GSK, UNC, University of Pittsburgh.
  • Students complete 2-4 first-author publications during PhD program, with topics ranging from statistical methodology to translational genomics.
  • Mentoring approach: Independent research aims with clinical collaboration, weekly manuscript meetings, reproducible software deliverables, and embedded trial experience.

Teaching philosophy

Courses emphasize both rigorous theory and practical implementation, using collaborative datasets, version control, and reproducible documentation to prepare students for academic and industry positions.

Mentoring & Student Outcomes

Five completed PhD advisees (co-advised with Drs. Ibrahim, Love, Kosorok) with 100% placement at leading institutions.

Academic Positions

Faculty & Postdoctoral

  • Pedro Baldoni (2020) — Assistant Professor, University of Pittsburgh Biostatistics
  • Euphy Wu (2024) — Postdoctoral Fellow, UNC/Pittsburgh

Industry Positions

Pharmaceutical & Biotech

  • Hillary Heiling (2023) — Senior Biostatistician, Dana-Farber Cancer Institute
  • David Lim (2022) — Scientist, GSK
  • Scott Van Buren (2020) — Scientist, GSK

Training approach: Independent research aims, embedded clinician collaborations, weekly manuscript meetings, and reproducible software deliverables. Students typically complete 2-4 first-author publications during their PhD program.

Last updated: November 2025