Portrait of Jarrett D. Phillips

Jarrett D. Phillips

He/Him/His

BSc. (Hons.), MBinf., PhD.

Adjunct Professor
School of Computer Science
Department of Integrative Biology
Affiliated Faculty, One Health Institute
University of Guelph

Download CV jphill01@uoguelph.ca

CV last updated October 2026

About

I leverage AI/ML/Data Science/Big Data methods to help researchers find meaningful signal in a vast sea of noise.

I am a highly motivated and passionate bioinformatician, data scientist and statistician naturally driven by curiosity to use mathematical, statistical and computational methods to answer fundamental and applied research questions in biodiversity science, evolutionary biology, ecology, genomics and bioinformatics, particularly related to molecular species identification and discovery through DNA barcoding, environmental DNA (eDNA) and other DNA-based approaches.

My academic work and research interests can best be described as computational molecular biodiversity science. Biodiversity is under threat in a rapidly changing world, where mitigation requires innovative and collaborative solutions from multiple disciplines. DNA-based specimen identification and species discovery through techniques like DNA barcoding and eDNA offer promising ways forward, yet produce overwhelming amounts of data.

Tools I mainly use

My research in words

The terms that come up most on this site and in my CV. The more often a term appears, the larger it is.

Word cloud of research terms from this site and my CV. The largest are sampling, DNA barcoding, seafood fraud, modelling, eDNA and DNA barcode gap. Software and tools, such as R, HACSim, Shiny and web apps, are set in orange bold type.
  • Research topics and methods
  • Software and tools, in bold
View the terms as a table
TermMentionsType
sampling51Topic or method
DNA barcoding49Topic or method
seafood fraud40Topic or method
modelling37Topic or method
eDNA34Topic or method
DNA barcode gap29Topic or method
statistics27Topic or method
R26Software or tool
association rules24Topic or method
genetic diversity23Topic or method
species23Topic or method
intraspecific21Topic or method
GBADs18Topic or method
biodiversity17Topic or method
supply chain16Topic or method
fishes15Topic or method
Bayesian13Topic or method
ecology13Topic or method
haplotype accumulation13Topic or method
statistical modelling13Topic or method
DNA sequences12Topic or method
HACSim12Software or tool
data mining11Topic or method
Shiny11Software or tool
spatiotemporal11Topic or method
machine learning10Topic or method
livestock8Topic or method
simulation8Topic or method
species identification8Topic or method
web apps8Software or tool
agent-based models7Topic or method
bioinformatics7Topic or method
butterflies7Topic or method
coalescent7Topic or method
CRAN7Software or tool
nonparametric7Topic or method
VLF7Software or tool
classification6Topic or method
disease burden6Topic or method
regression6Topic or method
sequencing errors5Topic or method
data science4Topic or method
evolutionary biology4Topic or method
genomics4Topic or method
optimization4Topic or method
time series4Topic or method
artificial intelligence3Topic or method
bootstrap3Topic or method
kernel density estimation3Topic or method
metadata3Topic or method
Python3Software or tool
RulesTools3Software or tool
Stan3Software or tool
conservation2Topic or method
Gaussian processes2Topic or method
generalized additive models2Topic or method
genetic algorithms2Topic or method

Counts come from the text of this site and my CV. Names, venues and very general words are left out. Open the full-size image.

The DNA barcode gap depends on the bin width

These are simulated distances between DNA barcodes. Change the bin width and watch the gap between the two groups open and close.

0.5%
Largest within-species distance
 
Smallest between-species distance
 
Gap between them
 
View the bins as a table
Bin (% distance)Within speciesBetween species

Simulated data for illustration, not measurement. The DNA barcode gap is the distance between the largest within-species genetic distance and the smallest between-species genetic distance, and those two values do not change with the bin width. The curves are kernel density estimates. For the argument behind this figure, see Phillips, Gillis and Hanner (2022).

Latest publications

  • 2026

    Phillips, J.D. and *De Vuono-Fraser, F.A. (2026). Swimming in deep uncertainty: How proper statistical modelling can help expose seafood product mislabeling. CHANCE, 3. DOI: 10.1080/09332480.2026.2725526

  • 2026

    Phillips, J.D. and *De Vuono-Fraser, F.A. (2026). Statistical modelling of seafood fraud highlights uncertainties in products from Metro Vancouver, British Columbia, Canada: Revisiting Hu et al. (2018). Journal of Food Science, 91: e71201. DOI: 10.1111/1750-3841.71201

  • 2026

    *Toth, N., Antonie, L., Hanner, R.H., Gillis, D.J., and Phillips, J.D. Mining association rules for targeted spatiotemporal aquatic environmental DNA (eDNA) sampling. bioRxiv. DOI: 10.64898/2026.09.16.752056. Submitted to Oikos.

See all publications

Research interests

Computational statistics, data science, machine learning, statistical modelling, biodiversity informatics, and eDNA and DNA barcoding.

Agent-based and individual-based modelling
Bayesian computing and statistics
in R and Stan
Biodiversity informatics
e.g., DNA barcoding, environmental DNA (eDNA), DNA sequence analysis
Data science
Machine learning
e.g., association rule generation, clustering, classification, and dimensionality reduction of (e)DNA sequence data and related metadata
Nonparametric statistics
e.g., bootstrap resampling, local regression, kernel methods
Spatiotemporal modelling
e.g., conditionally autoregressive models (CARs), Gaussian processes (GPs)/Kriging, generalized additive models (GAMs), time series
Stochastic optimization
e.g., random search algorithms, genetic algorithms (GAs), simulated annealing

Appointments

  • 2026

    Affiliated Faculty, One Health Institute
    University of Guelph

  • 2023–present

    Adjunct Professor, School of Computer Science
    University of Guelph

  • 2023–present

    Postdoctoral Fellow
    GBADs Informatics Team, Stacey Lab, School of Computer Science, University of Guelph

    Supervisor: Dr. Deborah Stacey

  • 2023–present

    Postdoctoral Fellow
    Gillis Lab, School of Computer Science; Hanner Lab, Department of Integrative Biology; University of Guelph

    Supervisors: Drs. Daniel Gillis and Robert Hanner

  • 2022

    Postdoctoral Fellow
    Hanner Lab, Department of Integrative Biology, University of Guelph

    Supervisor: Dr. Robert Hanner

Education

  • 2022

    Ph.D. in Computational Sciences, University of Guelph

    Co-advisors: Dr. Daniel Gillis and Dr. Robert Hanner

    Advisory committee: Dr. Deborah Stacey and Dr. Graham Taylor

    Dissertation: A Novel Statistical Framework for Assessment of Intraspecific Haplotype Sampling Completeness: Implications for DNA Barcode Gap Estimation

  • 2014

    Master of Bioinformatics, University of Guelph

    Co-advisors: Dr. Robert Hanner and Dr. Daniel Ashlock

    Major paper: Assessing DNA Barcode Haplotype Sampling Diversity in the Ray-finned Fishes (Chordata: Actinopterygii)

  • 2013

    BSc. (Hons.) in Biological Science, University of Guelph

    Coursework in bioinformatics, ecology, evolutionary biology, comparative animal physiology, genetics, mathematics, and statistics

News

2026

  • My student, Richard Cui, gave a talk at the Applied Mathematics, Modelling, and Computational Science (AMMCS) conference in Waterloo, Ontario, Canada.

  • My student, Nikolett Toth, and I presented a poster and gave a talk, respectively, at the 3rd Pathway to Increase Standards and Competency in Environmental DNA Surveys (PISCeS) conference in Guelph, Ontario, Canada.

  • A paper with my student, Nikolett Toth, on association rule mining of eDNA datasets was accepted to the 39th annual Canadian Artificial Intelligence Conference in Vancouver, British Columbia, Canada.

  • My student, Richard Cui, was featured in a College of Computational, Mathematical, and Physical Sciences (CCMPS) Research Highlights article: Reeling in the Catch: Modelling the Dynamics of Market Fraud Within the Seafood Supply Chain.

  • I am serving on the Program Committee of the 39th Canadian Conference on Artificial Intelligence as a paper reviewer.

2025

  • Fall

    I taught CIS*1910 (Discrete Structures in Computing I).

2024

  • My student, Nikolett Toth, was featured in a College of Engineering and Physical Sciences (CEPS) Research Highlights article: eDNA Collection Gets a Tech Upgrade.

  • I received a $40,000 CAD Food from Thought Advancing Research Impact Fund (ARIF) Livestock Innovation grant to develop the Dynamic Population Model (DPM) as part of my work with GBADs.

  • Two book chapters on DNA barcoding for specimen identification and species delimitation were published online by Springer Nature.

  • 2024

    A preprint on GBADs informatics strategy, data quality, and model interoperability became available. It has since been published in the WOAH Scientific and Technical Review.

  • My preprint on statistical modelling of seafood mislabelling in Canada is now on bioRxiv.

2023

  • I attended the GBADs Technical Workshop in Liverpool, England.

  • I was appointed Adjunct Professor in the School of Computer Science at the University of Guelph.

  • I joined the Global Burden of Animal Diseases (GBADs) Informatics team at the University of Guelph.

  • The VLF paper was published.

2022

  • My paper introducing and outlining the VLF R package was accepted for publication in the Biodiversity Data Journal.

  • I received $30,000 CAD in funding from the Food from Thought Advancing Research Impact Fund (ARIF) to develop a Bayesian hierarchical binary logistic time-series regression model of seafood fraud in the Canadian supply chain.

  • My recent paper arguing a lack of statistical rigor in DNA barcoding was featured as a University of Guelph College of Engineering and Physical Sciences (CEPS) Research Highlights article: Mind the Gap – The DNA Barcode Gap, That Is.

  • My opinion paper on statistical aspects of DNA barcoding and the DNA barcode gap was published in Frontiers in Ecology and Evolution.

Research

Current projects

Agent-based, equation-based, and individual-based models for animal disease burden

  • Developing a deterministic discrete-time dynamical system of seafood fraud in the supply chain using Python.
  • Developing an age- and sex-structured compartmentalized equation-based model in R to assess disease burden in livestock species such as cattle, small ruminants (e.g., sheep and goats), and poultry in developing countries like Ethiopia.

Theoretical aspects of DNA-based taxon identification

  • Developing methods to estimate likely required specimen sample sizes for genetic diversity assessment within species using DNA barcoding.
    • Practical sample sizes for DNA barcoding typically range between 5 and 10 individuals per species, but required levels of sampling depth are highly dependent on the evolutionary history and ecology of the species under study, as well as species rarity and overall project costs.
    • I created HACSim (Haplotype Accumulation Curve Simulator), a novel nonparametric stochastic (Monte Carlo) local search optimization algorithm, to better estimate likely required specimen sample sizes based on asymptotic behaviour seen in species' haplotype accumulation curves.
    • HACSim has been shown to work well for a variety of species of socioeconomic relevance, such as fishes, insects and arachnids, based on extensive simulation studies.
    • The publication of HACSim in PeerJ Computer Science was one of the top 5 most viewed articles in the category “Optimization Theory and Computation”.
  • Developing methods for better visualization and inference of the DNA barcode gap.
    • The DNA barcode gap, the difference between genetic variation observed within and among species, is most often visualized using histograms. These plots can be misleading because they depend on user-defined parameters, which greatly affect the overall shape of the probability distributions.
    • I propose that kernel density estimation provides a better path forward for establishing the efficacy of DNA barcoding as a molecular identification tool.
    • I also propose nonparametric bootstrapping, specifically the m-out-of-n bootstrap, to estimate the sampling distributions of quantities of interest in DNA barcoding. These include extreme order statistics like the minimum interspecific and maximum intraspecific genetic distances, in addition to the DNA barcode gap.
    • We are currently developing a population genetic model of the DNA barcode gap based on the multispecies coalescent (preprint).

Building the reference library of life

  • Constructing the largest DNA barcode reference sequence library for North American butterflies.
    • Butterflies are some of the most genetically and morphologically diverse insects on the planet. One aspect of my work involves generating a DNA barcode library for over 97% (more than 800 species) of known butterfly species found in North America (D’Ercole et al., 2021).
    • Current work using this dataset correlates species’ genetic diversity with geographical covariates (such as latitude and longitude) using semiparametric and nonparametric regression approaches, including Generalized Additive Models (GAMs) and Local Regression (LOESS).

R software packages and R Shiny web apps for molecular biodiversity assessment

  • HACSim, VLF and RulesTools are available through the Comprehensive R Archive Network (CRAN). See the Software tab for details and links.

Assessing R metadata reporting and standards in the ecological literature

  • Within many scientific publications that employ R, lack of proper citation of R versions and packages used in analyses is rampant.
  • We mine article metadata spanning five different ecological journals for publications appearing in 2019 and find significant variation in how R is currently reported.
  • We propose a simple way of standardizing reporting that will help mitigate biases in future studies.

Funding

Research grants

  • 2024

    Food From Thought Advancing Research Impact (ARIF) Fund – Livestock Innovation Grant, University of Guelph. $40,000 CAD

    A Modular Decision- and Policy-Making Tool for Global Livestock Disease Burden Assessment. Role: co-applicant.

  • 2023

    Food From Thought Advancing Research Impact (ARIF) Fund, University of Guelph. $30,000 CAD

    Forecasting Seafood Fraud Occurrence in the Supply Chain Within Major Canadian Cities Using Bayesian Hierarchical Binary Logistic Time-Series Regression Modeling. Role: HQP.

Scholarships, travel awards and assistantships

  • 2019

    SoCS Travel Grant, University of Guelph. $1,000 CAD

  • 2019

    Arthur D. Latornell Graduate Travel Grant, University of Guelph. $500 CAD

  • 2016–2020

    Graduate Teaching Assistantships, University of Guelph. $35,000 CAD

  • 2017–2019

    Graduate Research Assistantships, University of Guelph. $11,000 CAD

  • 2017

    CPES Graduate Dean’s Scholarship, University of Guelph. $3,500 CAD

  • 2016

    CPES Graduate Excellence Entrance (GEE) Scholarship, University of Guelph. $30,000 CAD

Logos of the organizations that fund this research

Collaborators

  • Dr. Daniel GillisSchool of Computer Science, University of Guelph, Canada
  • Dr. Robert HannerBiodiversity Institute of Ontario, Department of Integrative Biology, University of Guelph, Canada
  • Dr. Robert YoungDepartment of Integrative Biology, University of Guelph, Canada
  • Dr. Jacopo D’ErcoleCentre for Biodiversity Genomics, University of Guelph, Canada
  • Dr. Cortland GriswoldDepartment of Integrative Biology, University of Guelph, Canada
  • Dr. Nicolas HubertInstitut de Recherche pour le Développement, Université de Montpellier, France
  • Dr. Dirk SteinkeCentre for Biodiversity Genomics and Department of Integrative Biology, University of Guelph, Canada
  • Dr. Luiza AntonieSchool of Computer Science, University of Guelph, Canada
  • Dr. Deborah StaceySchool of Computer Science, University of Guelph, Canada
  • Dr. Theresa BernardoDepartment of Population Medicine, University of Guelph, Canada
  • Dr. Kurtis SobkowichDepartment of Population Medicine, University of Guelph, Canada
  • Dr. Le NguyenSchool of Computer Science, University of Guelph, Canada
  • Dr. Mike YodzisDepartment of Integrative Biology, University of Guelph, Canada
  • Dr. Ed SykesSchool of Computer Science, University of Guelph, Canada
  • Dr. Elif AcarDepartment of Mathematics and Statistics, University of Guelph, Canada
  • Dr. Stefan KremerSchool of Computer Science, University of Guelph, Canada
  • Dr. Graham TaylorSchool of Engineering, University of Guelph, Canada
  • Dr. Prasad DaggupatiSchool of Engineering, University of Guelph, Canada
  • Dr. Zeny FengDepartment of Mathematics and Statistics, University of Guelph, Canada
  • Dr. Allan WillmsDepartment of Mathematics and Statistics, University of Guelph, Canada
  • Dr. Richard HeckSchool of Environmental Science, University of Guelph, Canada
  • Dr. Shoshanah JacobsBiodiversity Institute of Ontario, Department of Integrative Biology, University of Guelph, Canada
  • Dr. Aicheng ChenDepartment of Chemistry, University of Guelph, Canada

Publications

9 peer-reviewed journal articles (7 as first author), 2 book chapters, and 3 first-author manuscripts in preprint or to be submitted. I am senior (last) author on 2 student-led manuscripts. Citation counts are on Google Scholar.

* marks a student under my direct supervision.

Journal articles

  • 2026

    Phillips, J.D. and *De Vuono-Fraser, F.A. (2026). Swimming in deep uncertainty: How proper statistical modelling can help expose seafood product mislabeling. CHANCE, 3. DOI: 10.1080/09332480.2026.2725526

  • 2026

    Phillips, J.D. and *De Vuono-Fraser, F.A. (2026). Statistical modelling of seafood fraud highlights uncertainties in products from Metro Vancouver, British Columbia, Canada: Revisiting Hu et al. (2018). Journal of Food Science, 91: e71201. DOI: 10.1111/1750-3841.71201

  • 2024

    Raymond, K., Sobkowich, K.E., Phillips, J.D., Nguyen, L., McKechnie, I., Mohideen, R.N., Fitzjohn, W., Szurkowski, M., Davidson, J., Rushton, J., Stacey, D.A., and Bernardo, T.M. (2024). GBADs informatics strategy: User-centric tools, data quality, and model interoperability. WOAH Scientific and Technical Review, 43: 96–107. DOI: 10.20506/rst.43.3522

  • 2023

    Phillips, J.D., Athey, T.B.T., Hanner, R.H., and McNicholas, P.D. (2023). VLF: An R package for the analysis of very low frequency variants in DNA sequences. Biodiversity Data Journal, e96480. DOI: 10.3897/BDJ.11.e96480

  • 2022

    Phillips, J.D., Gillis, D.J., and Hanner, R.H. (2022). Lack of statistical rigor in DNA barcoding likely invalidates the presence of a true species’ barcode gap. Frontiers in Ecology and Evolution, 10: 859099. DOI: 10.3389/fevo.2022.859099

  • 2021

    D’Ercole, J., Dincă, V., Opler, P.A., Kondla, N.G., Schmidt, C.B., Phillips, J.D., Robbins, R., Burns, J.M., Miller, S.E., Grishin, N., Zakharov, E.V., deWaard, J.R., Ratnasingham, S., and Hebert, P.D.N. (2021). A DNA barcode library for the butterflies of North America. PeerJ, 9: e11157. DOI: 10.7717/peerj.11157

  • 2020

    Phillips, J.D., *French, S.H., Hanner, R.H., and Gillis, D.J. (2020). HACSim: An R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves. PeerJ Computer Science, 6(192): 1–37. DOI: 10.7717/peerj-cs.243. Top 5 most viewed article in the category “Optimization Theory and Computation”.

  • 2019

    Phillips, J.D., Gillis, D.J., and Hanner, R.H. (2019). Incomplete estimates of genetic diversity within species: Implications for DNA barcoding. Ecology and Evolution, 9(5): 2996–3010. DOI: 10.1002/ece3.4757

  • 2015

    Phillips, J.D., Gwiazdowski, R.A., Ashlock, D., and Hanner, R. (2015). An exploration of sufficient sampling effort to describe intraspecific DNA barcode haplotype diversity: examples from the ray-finned fishes (Chordata: Actinopterygii). DNA Barcodes, 3: 66–73. DOI: 10.1515/dna-2015-0008

Preprints and manuscripts

  • 2026

    *Toth, N., Antonie, L., Hanner, R.H., Gillis, D.J., and Phillips, J.D. Mining association rules for targeted spatiotemporal aquatic environmental DNA (eDNA) sampling. bioRxiv. DOI: 10.64898/2026.09.16.752056. Submitted to Oikos.

  • 2025

    Phillips, J.D., Hubert, N., and Hanner, R.H. (2025). A Bayesian coalescent model of the DNA barcode gap. Authorea. DOI: 10.22541/au.174073683.37707806/v1

  • 2024

    Phillips, J.D. and *De Vuono-Fraser, F.A. (2024). Statistical modelling of seafood fraud in the Canadian supply chain. bioRxiv. DOI: 10.1101/2024.02.05.578947

  • To submit

    Phillips, J.D., Hubert, N., and Hanner, R.H. A Bayesian-informed coalescent model of the DNA barcode gap. Targeted to Methods in Ecology and Evolution.

  • In prep.

    *Cui, R.C., Yodzis, M.P., and Phillips, J.D. The influence of wholesaler fraud and consumer perception on IUU fishing in a model of the seafood supply chain. Targeted to Proceedings of the National Academy of Sciences.

  • In prep.

    Diao, J., Elliott, T.A., Phillips, J.D., You, J., and Adamowicz, S.J. Benchmarking imputation methods for insect trait data across missingness mechanisms and trait types. Targeted to Methods in Ecology and Evolution.

  • In prep.

    D’Ercole, J., Dapporto, L., Phillips, J.D., Dincă, V.E., Vila, R., Talavera, G., and Hebert, P.D.N. Macrogenetics of North American butterflies: The impact of Quaternary climatic fluctuations. Targeted to Proceedings of the National Academy of Sciences.

Book chapters

  • 2024

    Phillips, J.D., Griswold, C.K., Young, R.G., Hubert, N., and Hanner, R.H. (2024). A Measure of the DNA Barcode Gap for Applied and Basic Research. In: DeSalle, R. (ed.) DNA Barcoding. Methods in Molecular Biology, vol 2744. Humana, New York, NY. Springer

  • 2024

    Hubert, N., Phillips, J.D., and Hanner, R.H. (2024). Delimiting Species with Single-Locus DNA Sequences. In: DeSalle, R. (ed.) DNA Barcoding. Methods in Molecular Biology, vol 2744. Humana, New York, NY. Springer

  • Submitted

    *Cui, R.C., Yodzis, M.P., and Phillips, J.D. Modelling the Interplay between IUU Fishing, Wholesaler Fraud, and Consumer Awareness in the Seafood Supply Chain. VII AMMCS International Conference, Springer Nature.

Proceedings and abstracts

  • 2026

    *Toth, N., Antonie, M.L., and Phillips, J.D. To correct or not to correct?: Assessing the multiple comparisons problem for association rule mining of environmental DNA (eDNA) detection survey datasets. 39th Canadian Conference on Artificial Intelligence, 318: 1012–1019. Short paper and poster.

  • 2023

    Morey, K., Loeza-Quintana, T., Phillips, J., and Hanner, R. (2023). Haplotype diversity reveals challenges and opportunities for developing targeted detection assays for COI in Canadian freshwater fishes. Pathway to Increase Standards and Competency in eDNA Surveys (PISCeS) Conference. Poster.

  • 2019

    Phillips, J.D., Gillis, D., and Hanner, R. (2019). HACSim: Iterative extrapolation of haplotype accumulation curves for assessment of intraspecific COI DNA barcode sampling completeness. Scientific abstracts from the 8th International Barcode of Life Conference, Trondheim, Norway (ed. Torbjørn Ekrem), Genome, 62(6): 349–453. Oral presentation.

  • 2017

    Phillips, J.D., Gillis, D., and Hanner, R. (2017). Intraspecific sample size estimation for DNA barcoding: Are current sampling levels enough? Scientific abstracts from the 7th International Barcode of Life Conference, Johannesburg, South Africa (ed. M. van der Bank), Genome, 60(11): 881–1019. Oral presentation.

  • 2015

    Phillips, J.D., Gwiazdowski, R.A., Ashlock, D., and Hanner, R. (2015). An exploration of sufficient sampling effort to describe intraspecific haplotype diversity in the ray-finned fishes (Chordata: Actinopterygii). Scientific abstracts from the 6th International Barcode of Life Conference, Guelph, ON, Canada (ed. S.J. Adamowicz), Genome, 58(5): 163–303. Poster.

Talks and posters

  • 2026

    *Cui, R.C., Yodzis, M.P., and Phillips, J.D. Modelling the Interplay between IUU Fishing, Wholesaler Fraud, and Consumer Awareness in the Seafood Supply Chain.

    The VII AMMCS International Conference, Wilfrid Laurier University, Canada. Student oral presentation.

  • 2026

    Phillips, J.D. Association rule mining for targeted spatiotemporal aquatic environmental DNA (eDNA) sampling.

    Pathway to Increase Standards and Competency of eDNA Surveys (PISCeS) International Conference, University of Guelph, Canada. Oral presentation.

  • 2026

    *Toth, N., Antonie, M.L., and Phillips, J.D. To correct or not to correct?: Assessing the multiple comparisons problem for association rule mining of environmental DNA (eDNA) detection survey datasets.

    PISCeS International Conference, University of Guelph, Canada. Student poster presentation.

  • 2026

    *Toth, N., Antonie, M.L., and Phillips, J.D. To correct or not to correct?: Assessing the multiple comparisons problem for association rule mining of environmental DNA (eDNA) detection survey datasets.

    39th Canadian Conference on Artificial Intelligence, Simon Fraser University, Canada. Short paper and student poster presentation.

  • 2025

    *Cui, R.C., Yodzis, M.P., and Phillips, J.D. The Importance in Design as a Computer Scientist.

    SoCS Undergraduate Summer Project Show and Tell, University of Guelph, Canada. Student oral presentation.

  • 2024

    *Toth, N. and Phillips, J.D. Association Rule Mining of eDNA Datasets.

    CEPS Undergraduate Student Poster Day, University of Guelph, Canada. Student poster presentation.

  • 2024

    *Toth, N. and Phillips, J.D. Association Rule Mining of eDNA Datasets.

    CBS Undergraduate Poster Session, University of Guelph, Canada. Student poster presentation.

  • 2024

    Phillips, J.D. A Measure of the DNA Barcode Gap for Applied and Basic Research.

    9th International Barcode of Life Conference, Estação das Docas, Belém, Brazil. Poster presentation (abstract accepted, not attended).

  • 2023

    Phillips, J.D. The GBADs R Package (and Why We Need It!)

    GBADs Informatics Technical Workshop, University of Liverpool, England. Oral presentation.

  • 2023

    *De Vuono-Fraser, F.A. and Phillips, J.D. Estimating Seafood Mislabelling Rates in Canada Using Bayesian Modelling.

    CEPS Student Research Day, University of Guelph, Canada. Student poster presentation.

  • 2023

    Phillips, J.D. Haplotype diversity reveals challenges and opportunities for developing targeted detection assays for COI in Canadian freshwater fishes.

    PISCeS International Conference, University of Guelph, Canada. Poster presentation.

  • 2019

    Phillips, J.D. HACSim: Iterative extrapolation of haplotype accumulation curves for assessment of intraspecific COI DNA barcode sampling completeness.

    8th International Barcode of Life Conference, NTNU University Museum and Norwegian Biodiversity Information Centre, Norway. Oral presentation.

  • 2019

    Artificial Intelligence and Machine Learning in Biology.

    Guelph BioMathematics and Statistics (BioM&S) Symposium, University of Guelph, Canada. Attended.

  • 2018

    *French, S.H. and Phillips, J.D. Estimating Sampling Size Using Haplotype Accumulation Curves and Semiparametric Models.

    CEPS Undergraduate Student Poster Day, University of Guelph, Canada. Student poster presentation.

  • 2017

    Phillips, J.D. Intraspecific sample size estimation for DNA barcoding: Are current sampling levels enough?

    7th International Barcode of Life Conference, University of Johannesburg, South Africa. Oral presentation.

  • 2015

    Phillips, J.D. An exploration of sufficient sampling effort to describe intraspecific DNA barcode haplotype diversity: examples from the ray-finned fishes (Chordata: Actinopterygii).

    6th International Barcode of Life Conference, University of Guelph, Canada. Poster presentation.

Outreach and other writing

  • 2026

    *Cui, R.C. and Phillips, J.D. (2026). Student-contributed poster for University of Guelph March Open House.

  • 2026

    *Toth, N. and Phillips, J.D. (2026). Student-contributed poster for University of Guelph March Open House.

  • 2025

    *Cui, R.C. and Phillips, J.D. (2025). The Importance in Design as a Computer Scientist. Student-contributed SoCS Show and Tell video. Video

  • 2024

    Phillips, J.D., *De Vuono-Fraser, F.A., Gillis, D.J., and Hanner, R.H. (2024). Statistical modelling of seafood fraud. Whiteboard explainer video. YouTube

  • 2024

    *Toth, N. and Phillips, J.D. (2024). eDNA Collection Gets a Tech Update. Student-contributed CEPS Research Highlights article. Article

  • 2024

    *Toth, N. and Phillips, J.D. (2024). Unravelling eDNA with Association Rule Mining. Guest post on the Science Borealis-syndicated blog of Dr. Daniel Gillis. Post

  • 2024

    Phillips, J.D. (2024). Summer URA Position. Guest post on the Science Borealis-syndicated blog of Dr. Daniel Gillis. Post

  • 2022

    Phillips, J.D. (2022). Mind the Gap – The DNA Barcode Gap, That Is. CEPS Research Highlights article. Article

  • 2022

    Phillips, J.D. (2022). A Novel Statistical Framework for Assessment of Intraspecific Haplotype Sampling Completeness: Implications for DNA Barcode Gap Estimation. Ph.D. thesis, University of Guelph. Atrium

  • 2020

    Phillips, J.D. (2020). Barcode Cracking. CEPS Research Highlights article. Article

  • 2020

    Phillips, J.D. (2020). Protecting Biodiversity Through the Lens of Genetic Diversity. Guest post on the Science Borealis-syndicated blog of Dr. Daniel Gillis. Post

  • 2019

    Phillips, J.D. (2019). IBOL8 and the Midnight Sun. Guest post on the Science Borealis-syndicated blog of Dr. Daniel Gillis. Post

  • 2017

    Phillips, J.D. (2017). The Big Five and IBOL7. Guest post on the Science Borealis-syndicated blog of Dr. Daniel Gillis. Post

  • 2016

    Phillips, J.D. (2016). Sample size estimation for DNA barcoding: Are current sampling levels enough? Guest post on the DNA Barcoding Blog of Dr. Dirk Steinke. Post

  • 2016

    Phillips, J.D. (2016). Sample size estimation for DNA barcoding of ray-finned fishes: Are current sampling levels enough? Newsletter article, Barcode Bulletin, 7(1). Issue

Software

My R packages have been downloaded more than 98,000 times through the Comprehensive R Archive Network (CRAN).

HACSim

R package and R Shiny web application

Haplotype Accumulation Curve Simulator. Estimates how many specimens are likely needed to capture the genetic diversity within a species, based on the asymptotic behaviour of its haplotype accumulation curve.

More than 50,000 downloads

VLF

R package

Very Low Frequency variants. Detects very low frequency variants, such as sequencing and PCR errors, and computes error rates at second codon positions in DNA sequences.

More than 40,000 downloads

RulesTools

R package

Streamlines the preparation, analysis, and visualization of unsupervised association rules for eDNA data.

More than 3,000 downloads

GBADs ModelBuilder

R Shiny web application

A prototype tool from the GBADs informatics team for building livestock population models and estimating disease burden.

Seafood Fraud Modelling App

Python web application

An interactive model of the dynamics between seafood fraudsters and buyers in the supply chain.

DNA barcode gap estimators

R scripts

Frequentist and Bayesian, coalescent-informed estimators of the DNA barcode gap.

CRAN downloads

Daily and cumulative downloads of each package, refreshed every day. Loading the latest counts…

HACSim

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VLF

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RulesTools

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Counts come from the download logs of the RStudio CRAN mirror, through the cranlogs service that the R package packageRank also uses. They include automated downloads, such as package checks and mirrors.

Teaching & service

Teaching

  • 2025

    Course Instructor, University of Guelph

    CIS*1910 Discrete Structures in Computing I

  • 2016–2020

    Graduate Teaching Assistant (GTA), University of Guelph

    CIS*3130 System Modelling and Simulation (2020)
    CIS*1910 Discrete Structures in Computing I (2017)
    CIS*2460 Modelling of Computer Systems (2016–2019)

Student supervision and mentorship

I have mentored or co-supervised 18 undergraduate and graduate students across computer science, bioinformatics, statistics, and biology.

Undergraduate

  • 2025

    Brendan Carl Rosario

    Undergraduate Student Volunteer. Supervised Machine Learning for eDNA spatiotemporal sampling.

  • 2025

    Richard Cui

    Summer Undergraduate Research Assistant (URA). Dynamical modelling of seafood fraud in the supply chain.

  • 2024–2025

    Nikolett Toth

    CIS*4900/4910. Mining association rules for eDNA spatiotemporal sampling.

  • 2024

    Nikolett Toth

    Summer Undergraduate Research Assistant (URA). Mining association rules for eDNA spatiotemporal sampling.

  • 2024

    Fynn De Vuono-Fraser

    CIS*4900/4910. Bayesian modelling of seafood fraud in the Canadian supply chain.

  • 2023

    Zaid Al-Gayyali

    Summer Undergraduate Research Assistant (URA). Seafood Fraud Visualization Tool Shiny app.

  • 2023

    Fynn De Vuono-Fraser

    STAT*4600. Bayesian modelling of seafood fraud in the Canadian supply chain.

  • 2021

    Navdeep Singh

    CIS*4900. HACSim R Shiny web application.

  • 2020–2021

    Scarlett Bootsma

    CIS*4900/4910. HACSim simulation study.

  • 2020

    Maya Persram

    Hanner Lab volunteer. R reporting ecological meta-analysis.

  • 2020

    Ashley Chen

    Hanner Lab volunteer. R reporting ecological meta-analysis.

  • 2020

    Olivia Friesen Kroeker

    Hanner Lab volunteer. R reporting ecological meta-analysis.

  • 2018

    Steven French

    CIS*4900/4910. HACSim R package.

  • 2018–2019

    Julia Harvie

    MCB*4500/4510. Data mining GenBank and BOLD.

Graduate

  • 2024

    Nathan Zeinstra

    IBIO*6070. Bayesian habitat occupancy modelling for sea lamprey detection using eDNA.

  • 2022

    Amina Asif

    BINF*6999. DNA barcode gap analysis of Canadian disease vectors and agricultural pests.

  • 2018–2019

    Danielle St. Jean

    MSc. thesis (Mathematics), withdrawn. DNA barcode sequence classification with machine learning.

  • 2018–2019

    Christina Fragel

    BINF*6999. DNA barcode sequence classification with machine learning.

  • 2018–2019

    Jiaojia (Paula) Yu

    BINF*6999. MDMAPR R Shiny app.

  • 2018

    Ankita Bhanderi

    BINF*6999. Data mining GenBank and BOLD.

Academic service

  • 2026

    Pathway to Increase Standards and Competency in eDNA Surveys (PISCeS) Conference, University of Guelph

    Conference organizer and volunteer.

  • 2026

    39th Canadian Artificial Intelligence Conference, Simon Fraser University

    Program committee reviewer for the Long and Short Papers Track.

  • 2023

    GBADs Informatics Technical Workshop, University of Liverpool

    Workshop organizer.

  • 2023

    Pathway to Increase Standards and Competency in eDNA Surveys (PISCeS) Conference, University of Guelph

    Conference organizer and volunteer.

  • 2018

    School of Computer Science (SoCS) Faculty Search Committee, University of Guelph

    Member of the hiring panel for an Associate Professor in Cybersecurity.

  • 2017–2018

    School of Computer Science (SoCS) Faculty Search Committee, University of Guelph

    Member of the hiring panel for a 2-year Contractually Limited Assistant Professor in Cybersecurity.

Peer review

I review manuscripts for Ecology and Evolution, F1000 Research, Frontiers in Ecology and Evolution, Lifestyle Genomics, Mitochondrial DNA Part A, Molecular Ecology Resources, Molecular Biology Reports, Methods in Ecology and Evolution, and Nature Communications.

Volunteering

  • 2025

    CEPS Student Research Connections Networking Night, University of Guelph

    Connected with undergraduate students for summer URA project recruitment.

  • 2021–present

    CIS*3750 wireframing session, University of Guelph

    Graded students on mobile app prototypes for various community partners using Qualtrics surveys.

Contact

Email

Curriculum vitae

Download my CV (PDF), last updated October 2026.