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
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. ``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. ``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
- 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)