Ph.D. Candidate · Carnegie Mellon University

rajee ganesan

(rah-shee guh-NAY-sin)

comparative genomics, evolution & neuroscience  ·  pittsburgh, pennsylvania

I'm a fifth-year Ph.D. candidate in the Pfenning Neurogenomics Lab at Carnegie Mellon University. My research focuses on the molecular and genomic basis of vocal learning and social behaviors — using comparative genomics, machine learning, and epigenomics to understand how enhancer evolution drives the convergent emergence of these complex traits across vertebrates.

I have extensive experience in science education and communication, and graduated with my Bachelors in Science from UNC Chapel Hill in 2022, majoring in Quantitative Biology and minoring in Data Science and Statistics & Analytics. When I'm not in the lab, I'm watching baseball, shooting film photography, playing billiards with the USAPL, or at a live show!

✉ ↓ Curriculum Vitae ↓ Resume 𝕏 ORCID LinkedIn

Selected Research Projects

Enhancer evolution and the convergent emergence of vocal learning

2022 – Present

Pfenning Neurogenomics Lab, CMU Department of Biological Sciences

comparative genomics machine learning epigenomics predictive modeling

Humans, songbirds, and dolphins can all learn to imitate sounds — but our closest primate relatives can't. How did this ability evolve independently across such distantly related species? This project investigates the genomic basis of vocal learning, asking whether species that independently evolved this trait share conserved regulatory DNA that drives it. Using machine learning and comparative epigenomics across 280+ vertebrate genomes, I identify enhancers — genetic "switches" that control when and where genes are expressed — whose activity is uniquely shared among vocal learners. This work has been presented at the Evolution Conference, Society for Neuroscience, and Genes Brain & Behavior Conference, with manuscripts in preparation.

Enhancer-Gene Synteny Conservation Across the Vertebrate Genomes Project

2025 – Present

Pfenning Lab / VGP Consortium

pipeline development data integration cross-species analysis

When a gene and its regulatory "switch" stay physically close together across hundreds of millions of years of evolution, that's a signal the relationship matters. As part of the Vertebrate Genomes Project — a global consortium sequencing one genome from every vertebrate family — I developed computational pipelines to ask which enhancers have maintained this proximity across ~577 species, from fish to mammals. This work helps identify the regulatory elements most likely to be functionally important, with a focus on the motor cortex circuits underlying complex movement and vocal control. This work is currently under review for a manuscript.

Genetic and Epigenomic Risk Architecture of Crohn's Disease

2019 – 2022

Furey Lab, UNC Department of Medicine

translational research gene regulation statistical modeling

Crohn's disease is a chronic inflammatory bowel condition affecting millions, but we still don't fully understand why some people are genetically predisposed to it. For my undergraduate Honors Thesis, I analyzed tissue samples from Crohn's patients to identify regions of DNA that are more or less accessible depending on which version of a gene a person carries — a signal that genetic variation is actively shaping gene regulation in diseased tissue. I identified 2,000+ such sites, including 8 overlapping known Crohn's risk genes. This work was published in Nature Communications.

Selected Publications

Published

• Ganesan R, Pfenning AR. (2025)

  Evolution of Mammalian Regulatory Networks in the Brain.

  Annual Review of Animal Biosciences. ↗
• Nishiyama NC, Silverstein S, Darlington K, Kennedy Ng MM, Clough KM, Bauer M, Beasley C, Bharadwaj A, Ganesan R, et al. (2026)

  eQTL in diseased colon tissue identifies novel target genes associated with IBD.

  Nature Communications. ↗
• Marki A, Buscher K, Lorenzini C, Meyer M, Saigusa R, Fan Z, Yeh YT, Hartmann N, Dan JM, Kiosses WB, Golden GJ, Ganesan R, et al. (2021)

  Elongated neutrophil-derived structures are blood-borne microparticles formed by rolling neutrophils during sepsis.

  Journal of Experimental Medicine. ↗

Under Review & In Preparation

• Formenti G, [...] Ganesan R, [...] Jarvis ED, et al.

  The Vertebrate Genomes Project Phase I: A global reference genome resource.

  Under review
• Ganesan R, [...] Jarvis ED, Pfenning AR, Vernes SC, VGP Vocal Learning Group.

  VGP package: Shared genetic and neural features among humans and other vocal learning lineages.

  In preparation
• Ganesan R, Li X, Sestili H, Pfenning AR.

  Comparative analysis of B cell enhancer evolution associated with mammalian social behavior.

  In preparation
• Phan BN, Lawler AJ, He J, Brown AR, Kaplow IM, Kowalczyk A, Srinivasan C, Fox G, Ganesan R, Chen Z, Schaffer D, Wirthlin ME, Stauffer WR, Pfenning AR.

  Fine-mapping candidate neuropsychiatric regulatory variants using cell type-aware comparative genomics

  In preparation
• Marcus S, Davenport MH, Harter E, Ganesan R, Lee C, Phan BN, Terra N, Pfenning AR, Jarvis ED.

  Transcriptomic signatures of long-range projection class neurons for vocal control.

  In preparation

Teaching Experience

• BIOF555 / BIOF556 — Foundations & Advanced Topics in Single-Cell RNA-seq

  Instructor (sole); Co-instructor; Teaching Assistant  ·  NIH/FAES, Bethesda, MD
  5 semesters
  2024 – 2026
• BIOL03220 — Genetics

  Recitation Instructor  ·  CMU Department of Biology
  Fall 2026
• 02719 — Genomics and Epigenetics of the Brain

  Incoming Guest Instructor  ·  CMU Department of Computational Biology
  Fall 2026
• BIOL03133 — Neurobiology of Disease

  Teaching Assistant  ·  CMU Department of Biology
  3 semesters
  2023 – 2026

Mentorship

Mentorship has been a consistent thread across my research training. I've worked closely with students at the undergraduate, Master's, and doctoral levels, guiding independent projects, providing technical training in computational biology, and supporting scientific writing and presentation. My approach is grounded in the same framework I bring to teaching: moving students from structured exposure to independent application to articulation of their own ideas. I am less interested in producing students who can execute a workflow than in developing researchers who understand why a given approach exists, when it is appropriate, and where it breaks down. All six students I've formally mentored have gone on to PhD or MD programs, including one thesis recognized with the Best Honors Thesis award in the CMU School of Computer Science. For more about my approach to teaching and learning, see my teaching philosophy.

Recognitions

Skills