This is home to all my academic accomplishments. A pdf copy of my CV is available here. Please reach out if you have any questions.

Education

Columbia University, Mailman School of Public Health

  • Location: New York, NY
  • Expected Graduation: Spring 2025
  • Degree: Doctorate of Philosophy
  • Area of Study: Biostatistics

Marist College,

  • Location: Poughkeepsie, NY
  • Graduation: May 2020 Honors: Summa Cum Laude, Honors in Mathematics
  • Degree: Bachelor of Science
  • Double Major: Applied Mathematics and Data Science & Analytics
  • Minor: Computer Science

Interesting Projects

Welcome to my portfolio showcasing a curated collection of projects that I’ve accomplished during my academic journey.

Association of Bayesian Go/No-Go Design in Early Oncology Studies

This is a project completed during my internship at Bristol Myers Squibb. It is a shiny app that explores how the Simon’s Two-Phase Design can be adapted to a dual criterion Bayesian design.

Dose Escalation Methods

This is the second project that I completed during my time at Bristol Myers Squibb. I developed a shiny app that compares 11 different dose escalation methods through user specified simulations. It also compares decision tables for the methods that can be summarized into one.

Missing Data in Cancer Studies.

View an interactive visualization of how missing data introduce bias in my Shiny App!

Finding Time Series Breakpoints with Fully Connected Neural Networks

Here is the published paper!

Experience

Research Analyst (2021-Present)

Location: Biostatistics Department, Mailman School of Public Health

  • Assists in the development of methods and sensitivity analysis for transportability in multi-study, multi-outcome settings and their applications to cognitive remediation therapy for patients with schizophrenia, Mentor: Dr. Caleb H. Miles
  • Develops methods for graphical causal models and identification of direct effects with positivity violations and their applications to the causal effect of anesthesia on fetal development, Mentor: Dr. Caleb H. Miles
  • Implements MRP models to improve survey representativeness and the inference of health outcomes among patients with HIV during COVID-19 pandemic, Mentor: Dr. Qixuan Chen
  • Creates reproducible reports and visualizations to share with collaborators using tidyverse, R Markdown, and RShiny
  • Attends multidisciplinary meetings to discuss both methods and applications

Graduate Teaching Assistant (2020-Present)

Location: Biostatistics Department, Mailman School of Public Health

  • Fosters learning through holding weekly office hour, and answering student questions during class and over email
  • Provides detailed feedback on weekly assignments, quizzes and projects
  • Classes include Introduction to Data Science in R, Randomized Clinical Trials, Biostatistical Methods II, Statistical Methods for Casual Inference, and Data Science II

Summer Associate Healthcare Intern (Summer 2024)

Location: Analysis Group, New York, NY

  • Applied statistical methods to gain insight into drug efficacy and patient reported outcomes in collaboration with leading pharmaceutical companies
  • Cleaned and explored electronic health data to help create a statistical analysis plan
  • Designed a survey of physicians to gather critical insights on clinical practices, effectively informing subsequent chart reviews and enhancing understanding of healthcare trends and practices

Biostatistics Research Fellow (Summer 2021)

Location: Bristol Myers Squibb, Remote Internship

  • Selected to be a part of the 2021 summer Bristol Myers Squibb Internship Program in the Biostatistics department.
  • Explored two projects, one comparing dose escalation designs through simulations and another looking at go/no go decision. Both project shiny apps are found above.

Math Lab Lead Tutor (2018-2020)

Location:Department of Mathematics, Marist College

  • Supervise, train, and administrate staff of six students
  • Provide tutoring in the Math Lab, a peer help/tutoring center staffed entirely by students
  • Courses covered are: Calculus with Management Application, Calculus I-III, Linear Algebra, Differential Equations, Introduction to Mathematical Reasoning, Mathematical Analysis

Biostatistics Research Fellow (Summer 2019)

Location: Memorial Sloan Kettering Cancer Center, New York, NY

  • Accepted to competitive Quantitative Sciences Undergraduate Research Experience (QSURE)
  • Explored the effects of missing data in cancer studies under advisement of attending biostatistician
  • Created a RShiny Application currently accessible online. Paper currently in process of being written
  • Abstract accepted for both a presentation and poster session at the Joint Mathematics Meetings in January 2020

Research Experience for Undergraduates (REU) (Summer 2018)

Location: Lafayette College, Easton, Pennsylvania

  • Developed a Bayesian procedure to detect breakpoints in time series alongside two other undergrad students and a professor
  • Produced working R code and a rough draft of a paper that is in the process of being edited to eventually be submitted for publication

Relevant Skills

Programming Languages: R, RStudio, LaTeX, git, GitHub, PASS, Python, HTML, CSS, JavaScript, SQL, MATLAB, Java

Statistical Skills: Causal Inference, Hypothesis testing, Regression Techniques (linear, glm, lasso, ridge), Multivariate, Longitudinal and Survival Analysis, Neural Networks/Deep Learning, Bayesian Approaches, Stochastic Processes

Data Visualization Tools: RShiny, ggplot, gtsummary, Rmarkdown, tikZ, D3, tableau

Relevant Course Work

Columbia University (PhD)

  • P9186: Statistical Practices and Research for Interdisciplinary Sciences II (SPRIS II)
  • P9185: Statistical Practices and Research for Interdisciplinary Sciences I (SPRIS I)
  • P9130: Advanced Methods
  • P9120: Data Mining
  • P9111: Asymptotic Statistics
  • P9110: Theory of Statistical Inference II
  • P9109: Theory of Statistical Inference
  • P9104: Probability for Biostatisticians
  • P8160: Advanced Statistical Computing
  • P8140: Randomized Clinical Trials
  • P8131: Biostatisic Methods II
  • P8130: Biostatisic Methods I
  • P8124: Graphical Models for Complex Health Data
  • P8122: Statistical Methods for Causal Inference
  • P8109: Statistical Inference
  • P8106: Data Science II
  • P8105: Data Science I
  • P8104: Probability
  • P6400: Priciples of Epidemiology

Marist College (B.S.)

Double Major in Applied Mathematics and Data Science with a Minor in Computer Science

Mathematics: Applied Statistics, Differential Equations, Applied Mathematics, Complex Analysis, Mathematical Analysis, Numerical Analysis, Operations Research, Abstract Algebra, Independent Study in Math Biology, Computational Linear Algebra, Probability and Statistics

Computer Science: Algorithms, Software Development I-II, Database Management

Data Science: Machine Learning, Data Mining, Data Analysis, Data Visualization, Data Management courses

Publications/ Presentations / Posters

Publications

  • Pitts, Amy, & Rivas, Pablo, “Finding Time Series Breakpoints with Fully Connected Neural Networks”, Int’l Conf. Artificial Intelligence CSREA Press. 2019. p.352-357. ISBN: 1-60132-501-0.
  • Duong, Ngoc Q., Pitts, Amy J., Kim, Soohyun & Miles, Caleb H. ``Sensitivity analysis for transportability in multi-study, multi-outcome settings’’ arXiv preprint arXiv:2301.02904 (2023).
  • Pitts, Amy J. & Fowler, Charlotte R. ``Comparison of open-source software for plotting directed acyclic graphs” arXiv preprint arXiv:2305.12006 (2023).
  • Pitts, Amy, & Patil, Sujata. “Missing data in cancer studies” in preparation.

Presentations

  • Pitts, Amy. “Using a separable effects model to overcome extreme positivity violation and distinguish the causal effects of surgery and anesthesia” Eastern North American Region (ENAR). Baltimore, MD. Mar 2024.
  • Pitts, Amy. “Inference of health outcomes among patients with HIV during covid-19 pandemic: using mrp model to improve survey representativeness”, American Association for Public Opinion Research (AAPOR). Philadelphia, PA. May 2023.
  • Pitts, Amy. Fowler, Charlotte. “Software to Draw DAGs”, Causal Inference Learning Group. Feb 2023.
  • Pitts, Amy. “R-Shiny Crash Course” Columbia Biostatistics Computing Club. Nov 2022.
  • Pitts, Amy. “Bayesian Go/No-Go Rules & Two-stage Designs and Comparison of Dose Escalation Designs in Early Oncology Studies”, Bristol Myers Squibb. Microsoft Teams. August 2021.
  • Pitts, Amy. “Predicting Mesothelioma Disease Status Using Demographic, Clinical, and Exposure-Related Factors”, Marist College Pi Mu Epsilon Induction Ceremony. May 2021.
  • Pitts, Amy. Kwizera, Muhire. “Python Tutorial”, Columbia Biostatistics Computing Club. December 2020.
  • Pitts, Amy. Mulligan, Kaitlyn. & Allison Nowakowski. “The Machine Learning Quote Generator” Marist College School of Computer Science & Mathematics. Cisco Webex. May 2020.
  • Pitts, Amy. “SeminaR: an R tutorial looking at shiny applications” Marist College Department of Mathematics. Poughkeepsie, NY. November 2019.
  • Pitts, Amy. “My Research Experience at Memorial Sloan Kettering Cancer Center’’ Marist College Department of Mathematics. Poughkeepsie, NY. October 2019.
  • Pitts, Amy. “Overleaf Overview’’ Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center. New York, NY. August 2019.
  • Pitts, Amy, & Rivas, Pablo. “Finding time series breakpoints with fully connected neural networks” 2019 International Conference of Artificial Intelligence. Las Vegas, NV. July, 2019.
  • Pitts, Amy. “Missing Data in Cancer Studies” QSURE Final Presentations hosted in the Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center. New York, NY. July 2019.
  • Pitts, Amy. Haglich, Kathryn. & Neitzel, Sarah. “A Bayesian method for locating breakpoints in time series” Joint Mathematics Meetings. Baltimore, MD. January 2019.
  • Pitts, Amy. “My Research Experience at Lafayette College” Marist College Department of Mathematics. Poughkeepsie, NY. September 2018.

Poster Presentations

  • Pitts, Amy. “Multilevel Regression & Poststratification with Population Margins: Application to HIV Inference” Joint Statistical Meeting (JSM), Portland OR. Aug 2024.
  • Pitts, Amy. “Using a separable effects model to overcome extreme positivity violation and distinguish the causal effects of surgery and anesthesia” American Causal Inference Conference (ACIC). Seattle, WA. May 2024.
  • Pitts, Amy. “Inference of health outcomes among patients with HIV during covid-19 pandemic: using mrp model to improve survey representativeness”, Eastern North American Region International Biometric Society (ENAR). Nashville, TN. Mar 2023.
  • Pitts, Amy. Haglich, Kathryn. Neitzel, Sarah. & Leibner, Jeffery. “A Bayesian method for locating breakpoints in time series” ACM New York Celebration of Women in Computing. Lake George, NY. April 2019.
  • Pitts, Amy. Haglich, Kathryn. Neitzel, Sarah. & Leibner, Jeffery. “A Bayesian method for locating breakpoints in time series” Joint Mathematics Meeting. Baltimore, MD. January 2019.

Activities / Honors

Activities

  • Board Member, Columbia University Biostatistics Computing Club, (2020-Present)
  • Chair of Student Committee, Columbia Biostatistics Department Master Practicum Symposium, (2023)
  • President, Marist College Alpha Pi Chapter, Pi Mu Epsilon (2019-2020)
  • President and Founder, Association for Women in Mathematics (AWM) Chapter at Marist College (2019-2020)
  • Vice President, Marist Math Club (2019-2020)
  • Treasurer, Equestrian Team (2017-2020)
  • Member of Marist Team, 79th annual William-Lowell Putnam Mathematical Competition (2018)

Honors

  • Poster Award from the Joint Statistical Meeting Survey Research Method Section at the 2024 Joint Statistical Meetings in Portland, Oregon (2024)
  • Travel award from the Survey Research Methods Section to attend the 2024 Joint Statistical Meetings in Portland, Oregon (2024)
  • Invited to give a key note presentation and the presidential address at the Marist College Pi Mu Epsilon Induction Ceremony (2021)
  • Marist College Excellence in Mathematics Award (2020)
  • Inducted into the Marist College Pi Mu Epsilon Chapter Mathematics Honors Society (2019)
  • Recipient of an Outstanding Poster Award at the Joint Mathematics Meeting, Baltimore (2019)
  • Student Subcommittee Chair, 2019 Marist Math Department Faculty Search Committee (2019)
  • Recipient of the Marist College Early Career Undergraduate Mathematics Research Award (2018)
  • Awarded Best Visualization at DataFest located at Vassar College (2018)
  • Winner of the Hack Harassment Category in Marist College Hackathon (2016)