Talks and Other Events - Stephanie Hicks

2021

Evaluating the Alignment of a Data Analysis between Analyst and Audience. Invited session on “Theoretical and Empirical Contributions to Data Analytic Practice”. Joint Statistical Meetings. 2021 Aug 7-12. Seattle, WA. USA.
Increasing the reproducibility and rigor of single-cell RNA-seq through the use of statistics and data science. Reproducible and FAIR Bioinformatics Analysis of Omics Data. 2021 Jul 15. Bar Harbor, ME. USA.
More (single-cell) data, more (statistical) problems. Stanford Center for Biomedical Informatics Research. Stanford School of Medicine. 2021 Feb 25. Stanford, CA. USA. (Virtual).
Addressing Open Challenges in Data Science Education. Department of Statistics, University of British Columbia. 2021 Feb 9. Vancouver, BC. Canada. (Virtual).

2020

CZI Essential Open Source Software (EOSS) Annual Meeting. 2020 Dec 8-10. (Virtual).
Large-scale clustering in Bioconductor. CZI Seed Network Annual Meeting. 2020 Nov 17-19. (Virtual).
Scaling up single-cell data analyses in Bioconductor. Oz Single Cell. 2020 Nov 18. Melbourne, Australia. (Virtual).
Scaling up single-cell data analyses in Bioconductor. Biological Data Science. 2020 Nov 4-7. Cold Spring Harbor Laboratory. USA. (Virtual).
More (single-cell) data, more (statistical) problems. Human Medical Genetics and Genomics Program, University of Colorado (Anschutz Medical Campus). 2020 Oct 22. Denver, CO. USA. (Virtual).
Introduction to GenomicRanges and plyranges. R-Ladies Tunis. 2020 Oct 6. (Virtual).

Setting the Stage for Reproducibility in Single-Cell Data Science. Rigor and Reproducibilty in Cancer Research. Rogel Cancer Center. University of Michigan. 2020 Sept 24. Ann Arbor, MI, USA. (Virtual).
Addressing Public Health Challenges with Statistics, Genomics and Data Science. Annual presentation on my research interests in “Current Topics” courses as part of my participation as a Preceptor in the Department of Biochemistry and Molecular Biology’s NCI-supported PhD training program.
Panelist on Celebrating Florence Nightingale’s Bicentenary. Joint Statistical Meetings. 2020 Aug 1-6. Philadelphia, PA, USA. (Virtual due to COVID-19).
Communicating statistics and data science to the masses via Open Case Studies. Joint Statistical Meetings. 2020 Aug 1-6. Philadelphia, PA, USA.(Virtual due to COVID-19).
Bench pressing single-cell RNA-sequencing imputation methods. Bioconductor Conference. 2020 Jul 29-31. Boston, MA. USA. (Virtual due to COVID-19).
Analyzing Genomics Data in R with Bioconductor. R-Ladies Riverside. 2020 Jul 22.
Addressing Real-World Challenges through Data Science Education. Academic Data Science Alliance (ADSA) Data Science Education special interest group (SIG). 2020 Jul 2.

Annual Symposium of the Division of Gastroenterology at Johns Hopkins University. 2020 Jun 23. Baltimore, MD. USA. (Postponed to due COVID-19).
Mathematical Frameworks for Integrative Analysis of Emerging Biological Data Types at Banff International Research Station. 2020 Jun 14-19. (Virtual due to COVID-19).
Using R and data science to improve human health. Keynote presentation at The European R Users Meeting. 2020 June 17-20. Milan, Italy. (Virtual due to COVID-19).

Watch a pre-conference interview here:

Symposium on Data Science and Statistics (SDSS). 2020 Jun 3-5. Pittsburgh, PA. USA. (Virtual due to COVID-19). Watch a pre-conference interview here:

National Cancer Institute (NCI) / Center for Cancer Research (CCR) Bioinformatics Training and Education Program (BTEP) Distinguished Speakers Seminar Series. 2020 Apr 9. (Postponed to due COVID-19).
Fast clustering for single-cell RNA-seq data using mini-batch k-means. ENAR Conference. 2020 Mar 22-25. Nashville, TN. USA. (Virtual)
WiDS Conference 2020. US Bureau of Labor Statistics. 2020 Mar 2. Washington, DC. USA.
Statistical Genetics and Genomics at Johns Hopkins Biostatistics. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health. 2020 Feb 21. Baltimore, MD. USA.
More (single-cell) data, more (statistical) problems. Department of Biostatistics, University of North Carolina Gillings School of Public Health. 2020 Feb 13. Chapel Hill, NC. USA.
Panelist on Data Science Education at the Data Science for Public Health Summit. 2020 Jan 17. Columbia Mailman School of Public Health. New York City, NY. USA.
More (single-cell) data, more (statistical) problems. Department of Embryology, Carnegie Institution for Science. 2020 Jan 6. Baltimore, MD. USA.

2019

NormJam: A normalization workshop and jamboree for scRNA-seq data. 2019 Nov 19-20. New York City, NY. USA.
Data Science Leadership Summit. 2019 Nov 7-9. Santa Fe, NM. USA.
Addressing Public Health Challenges through Data Science Education. American Public Health Association Annual Meeting. 2019 Nov 2-6. Philadelphia, PA. USA.
Making data science accessible in the Johns Hopkins Data Science Lab. Mathematics Departments and the Explosive Growth of Computational and Quantitative Offerings in Higher Education. AMS Annual Mini-conference on Education. 2019 Oct 25. Washington, D.C. USA.
Teaching data science through case studies in Public Health. Joint Statistical Meeings. 2019 Jul 27-Aug 1. Denver, CO. USA.
mbkmeans: fast clustering for single cell data using mini-batch k-means. Bioconductor Conference. 2019 Jul 24-27. New York City, NY. USA.
Why Statistics Matters: Analysis of Genomics Data. Practical Genomics Workshop at Johns Hopkins University. 2019 June 4-7. Baltimore, MD. USA.
Useful Tools for Teaching And Outreach In Data Science. Symposium on Data Science and Statistics (SDSS). 2019 May 29-Jun 1. Bellevue, WA. USA.
Addressing Open Challenges Data Science Education. Department of Statistics and Data Sciences, Smith College. 2019 Apr 18. Northampton, MA. USA.
Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments. ENAR Conference. 2019 Mar 24-27. Philadelphia, PA. USA.
Making data science accessible world-wide in the Johns Hopkins Data Science Lab. Department of Statistics, University of Connecticut. 2019 Feb 27. Storrs, CT. USA.
Applications of Latent Variables in Identifying Systematic Errors in Genomics. Department of Statistics, Rice University. 2019 Feb 11. Houston, TX. USA.
National Human Genome Research Institute’s Genome to Phenotype Strategic Planning Meeting. 2019 Jan 22-24. Rockville, MD, USA
Estimating cell type composition in whole blood using differentially methylated regions. Department of Statistics, Oregon State University. 2019 Jan 14. Corvallis, OR. USA.

2018

Orchestrating Single-Cell RNA-sequencing Analysis with Bioconductor.
- Keynote presentation at Bioconductor Asia on 2018 Nov 29 at the University of Melbourne, Melbourne, Australia.
- Keynote presentation at Australian Mathematical Sciences Institute (AMSI) Bioinfosummer on 2018 Dec 3-7 at the University of Western Australia, Perth, Australia.
Analyzing Genomics Data in R with Bioconductor at DC R Conference. 2018 Nov 8. Washington D.C., USA.

Estimating cell type composition in whole blood using differentially methylated regions. Department of Biostatistics, The University of Alabama at Birmingham. 2018 Nov 2. Birmingham, AL. USA.
Estimating cell type composition in whole blood using differentially methylated regions at the 12th Annual Symposium and Poster Session on Genomics and Bioinformatics at Johns Hopkins University. 2018 Oct 25. Baltimore, MD. USA.
Women in Statistics and Data Science Conference. Lead a project on building a children’s book to highlight women in Statistics and Data Science.
Data Science Innovation Lab: Mathematical Challenges of Single Cell Dynamics. Invited to participate in a five-day workshop with early-career biomedical and quantitative investigators to create collaborations, answering important questions in single cell data.
Open challenges in Single-Cell RNA-Sequencing. Joint Statistical Meetings. 2018 Jul 29-Aug 2. Vancouver, CA.
Open Challenges in Single-Cell RNA-Sequencing. Single Cell Data Science: Making Sense of Data from Billions of Single Cells. 2018 Jun 4-8. Lorentz Center, Leiden University, Netherlands.
Technology-independent estimation of cell type composition using differentially methylated regions. Office of Biostatistics Research at NHLBI/NIH. 2018 Apr 24. Bethesda, MD. USA.

2017

Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments. Joint Statistical Meetings. 2017 Jul 29-Aug 3. Baltimore, MD, USA.
Estimating cell type composition in whole blood using differentially methylated regions. Bioconductor conference. 2017 Jul 26-28. Boston, MA, USA.
Missing Data and Technical Variability in Single Cell RNA-Sequencing Experiments. Ascona Workshop 2017: Statistical Challenges in Single Cell Biology. 2017 Apr 30-May 5. Ascona, Switzerland.
Setting the Stage for Reproducibility and Replicability in Science. Brandeis University. 2017 Mar 22. Waltham, MA, USA.

2016

On the widespread and critical impact of systemic bias and batch effects in single-cell RNA-seq data. Presented at the Boston Single-Cell Network Meeting in March 2016 (Boston, MA, USA), presented at the Joint Statistical Meetings Aug 2016 (Chicago, IL, USA), and presented at the Single-Cell Genomics Conference Sept 2016 (Hinxton, UK).
Batch effects and technical biases in scRNA-Seq data. HSCI Single-Cell Workshop. 2016 Nov 29-30. Harvard Medical School, Boston, MA, USA.
Transforming the Classroom to Teach Statistics and Data Science with Active Learning. Women in Statistics and Data Science Conference. 2016 Oct 20-22. Charlotte, NC, USA.
Towards progress in batch effects and biases in single-cell RNA-seq data. 2016 Sept 14-16. Wellcome Genome Campus, Hinxton, Cambridge, UK.
On the widespread and critical impact of systemic bias and batch effects in single-cell RNA-seq data. Joint Statistical Meetings. 2016 Jul 31-Aug 4. Chicago, IL, USA.
On the widespread and critical impact of systemic bias and batch effects in single-cell RNA-seq data. Boston Single-Cell Network Meeting. 2016 Mar 15. Boston, MA, USA.

2015

On the widespread and critical impact of batch effects and systematic bias in single-cell RNA-Seq data (Selected for a Stellar Abstract Award). PQG Conference: Single-cell Genomics: Technology, Analysis, and Applications. 2015 Nov 5-6. Boston, MA, USA.
Mozilla Open Science Leadership Summit. Invited to work with community leaders furthering open practice and open science through creating community events, tools for collaboration and learning resources.
Why Statistics Matters in the Analysis of Genomics Data. Presented at the LSU Computational Biology seminar and the LSUConnect event. 2015 Feb 11. Baton Rouge, LA, USA.

2014

Normalization of DNA methylation and Gene Expression Data in the Context of Global Variation. Bioinformatics Meeting, Division of Immunology, Harvard Medical School. 2014 Sept 18. Boston, MA, USA.
quantro: When should you use quantile normalization?. Flashlight talk at the Bioconductor Conference. 2014 Jul 30-Aug 1. Boston, MA, USA.
ROpenSci Unconference. Invited to work with over 40 R enthusiasts from industry, academia, non-profits and government on projects supporting open data, open science and data visualization in R. Contributed to R-packages including explainr and catsplainr.

2011

Modeling Discovery Of Functional SNPs From Genome Scale Data. JSM 2011. Miami, FL, USA.

2010

Prediction of Missense Mutation Functionality Depends on both the Algorithm and Sequence Alignment Employed. Human Genome Variation Society’s Exploring the Functional Consequences of Genomic Variation Meeting. Washington, D.C., USA.