Mentoring

Graduate, undergraduate, and intern research mentorship in microbial ecology, bioinformatics, and multi-omics analysis.

🎓 Student Mentorship

I actively mentor graduate students, master’s students, and research interns in microbial ecology, bioinformatics, metagenomics, metatranscriptomics, and genome-resolved analysis. My mentorship focuses on independent thinking, reproducible workflows, and translating complex data into biological insight.

Below are students I have formally mentored or co-mentored, along with selected research outcomes.

🎓 Graduate Student Mentorship

Dinuka Lakmali Jayasuriya Patabandige

PhD Student, Clemson University
📧 djayasu@g.clemson.edu

Project:
Environmental gradients shape the hydrocarbon-degrading microbiome in two Mid-Atlantic bays

My role:

  • Mentored MTX modeling, co-metabolism analysis, and metatranscriptomic workflows
  • Provided end-to-end bioinformatics support
  • Guided interpretation

Outcome:

  • Environmental gradients shape the hydrocarbon-degrading microbiome in two Mid-Atlantic bays
    Dinuka L. J. Patabandige, Jojy John, Maximiliano Ortiz, Barbara J. Campbell
    mSphere (submitted, 2026)

Nichole Giani

Graduate Student, Clemson University
📧 ngiani@g.clemson.edu

Project:
Cover crop effects on microbial functional redundancy

My role:

  • Guided co-assembly strategies
  • Mentored machine learning–derived MAG recovery
  • Supported functional redundancy quantification and interpretation

Outcome:

  • Manuscript in preparation

Mir Alvee Ahmed

PhD Student, Clemson University
📧 miralva@g.clemson.edu

Project:
Distribution, roles, and environmental drivers of bacterial communities in the Chesapeake and Delaware Bays

My role:

  • Mentored secondary metabolite gene screening
  • Supported metagenomic and metatranscriptomic analyses
  • Contributed as co-author on thesis chapters

Outcomes:

  • Ecological distribution and environmental drivers of Actinobacteriota in two Mid-Atlantic estuaries
    Mir Alvee Ahmed, Jojy John, Barbara J. Campbell (2025)
    mSphere (submitted, 2026) Preprint: https://www.biorxiv.org/content/10.1101/2025.11.21.689735v1

  • PhD dissertation chapters (co-author)
    https://www.proquest.com/docview/3266812896

🎓 Master’s Student Mentorship

Alisha M. Paul

MS Research Student, Campbell Lab, Clemson University
📧 apaul3@clemson.edu

Project:
Functional redundancy of marine synthetic biofilm communities under different environmental stresses

My role:

  • Mentored genome assembly and annotation
  • Guided screening of biofilm-related genes
  • Supported phylogenomics and comparative analysis

Outcome:

  • Conference presentation:
    Functional redundancy of marine synthetic biofilm communities under different environmental stresses
    Alisha M. Paul, Jojy John, Diptee Chaulagain, David Karig, Barbara J. Campbell
    ASM Biofilms, Oregon, 2025

*🧪 Research Intern Mentorship

Mary Elizabeth Glassburner

Undergraduate Research Intern
📧 meglass@clemson.edu

Project:

  • Virome analysis from soil metagenomes

My role:

  • Guided viral sequence identification and annotation
  • Introduced basic viromics workflows

Noah Fultz

Summer Research Intern
📧 nfultz@g.clemson.edu

Project:

  • Development of a shared bioinformatics environment for lab-wide use

My role:

  • Co-developed a centralized analysis environment
  • Installed and maintained commonly used tools:
    • QIIME2
    • ABRicate
    • InterProScan
    • VirSorter
    • PICRUSt2

🧑‍🔬 Additional Lab Support

In addition to formal mentoring, I regularly support lab members including Muhammad Suleman, Shoib Nawaz, and Sophia Rudolph with bioinformatics troubleshooting, data analysis, and interpretation.

I also serve as the manager of shared cloud and HPC storage infrastructure, maintaining and installing software for the Campbell Lab storage environment on Clemson’s Palmetto2 HPC system.

My mentoring emphasizes:

  • Building a strong foundation in reproducible and transparent bioinformatics workflows, ensuring students understand the underlying principles rather than treating analyses as black boxes
  • Linking ecological questions with quantitative and statistical approaches to drive biologically meaningful interpretations
  • Developing independence and long-term confidence so students can design, reproduce, and extend analyses in future projects
  • Training students to troubleshoot errors and adapt workflows as data, tools, and research questions evolve