Statistics and Probability Commons^™

Predicting Remaining Useful Life Using Multivariate Time-Series Data, Anayah Smith, Victoria Gaibor

Discovery Day - Daytona Beach

Accurate prediction of Remaining Useful Life (RUL) is critical for enabling predictive maintenance, improving system reliability, and reducing operational costs in degrading systems. This project addresses the problem of modeling and predicting RUL using multivariate time-series sensor data from the NASA CMAPSS turbofan engine dataset, with a focus on understanding how predictive performance changes across datasets of varying complexity. The objective is to develop a reproducible machine learning pipeline that captures degradation patterns and produces reliable time-to-failure predictions. The approach includes data preprocessing, exploratory data analysis, feature engineering, dimensionality reduction, and model evaluation. RUL values are computed and capped to …

Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen

Discovery Day - Daytona Beach

The aviation industry relies heavily on accurate demand forecasting to guide critical decisions regarding route planning, capacity management, and pricing strategy. Misjudging passenger demand can result in significant revenue loss and operational inefficiency, making it essential for airlines and analysts to identify the key drivers of flight patronage. This study investigates the factors that most significantly predict the number of passengers on domestic flights departing from Hartsfield-Jackson Atlanta International Airport (ATL) during the 2024 calendar year. Using passenger and route data sourced from the Bureau of Transportation Statistics (BTS) and the U.S. Department of Transportation (DOT), a multiple regression analysis …

A Compact Representation Of Oscillatory Limits Via Asymptotic Value Distributions, Ibrahim Arnous, Eric M. Rodarte, Chirag Kumar

Discovery Day - Daytona Beach

Classical limits describe asymptotic behavior through convergence to a single value, but many important oscillatory functions do not converge in this sense. Standard examples such as sin(𝑥) as 𝑥→∞ and sin(1/x) as x→0 instead display stable distributions of values over time. This project examines how such behavior can be described using a measure-theoretic framework, particularly through occupation measures and, in sequence-based settings, Young measures. The objective is to present this perspective in a clear and accessible way while introducing the Ansatz representation, a compact notation for recording the support and density of an asymptotic value distribution when the limiting measure …

Bounded Thunderstorm Tracking Of Lightning Events With Muon Detection, Skylar Wardlaw, Ainsley Helgerson, Maria Kaminska, Logan Velvet, Georgii Dubrov, Jackson Stewart, Aaron Jung, Nathaniel O’Hara, Amelia Koth, Nash Mcleod, Emaleth Wyckoff

Discovery Day - Daytona Beach

The muon is a high-energy particle that can be produced by cosmic rays and trigger upper-atmospheric particle cascades and energetic processes. It has been hypothesized that such cascades are at the onset of lightning. As such, muons serve as a valuable probe for investigating the underlying mechanisms of its initiation, whose full governing dynamics remain vastly unknown despite extensive research. Traditional approaches to lightning research involve simulations and observations of the discharge itself, but the role of high-energy particle interactions has yet to be fully constrained. The CosmicWatch Muon Detector design enables the detection of atmospheric muons through scintillation events, …

Delineating Differences In Firing Rate Estimates Of Healthy And Parkinsonian Single-Unit Basal Ganglia Recordings, Richard R. Foster, Cheng Ly

Biology and Medicine Through Mathematics Conference

No abstract provided.

Mitigating Parameter Identifiability Issues Through Model Calibration On The Data-Informed Active Subspace: An Example In Tumor Growth, Allison L. Lewis, Rebecca A. Everett

Biology and Medicine Through Mathematics Conference

No abstract provided.

A Statistical Analysis Of Current And Future Hurricane Activity In The North Indian Ocean, Basil Lund

2026 Symposium

A hurricane is defined as a tropical storm with winds sustained at 74 mph or greater. I examined major (category 3 and above) hurricane activity over the North Indian Ocean from the years 1972-2019 as reported by Colorado State University Hurricane Forecast Archive. Using RStudio, I conducted a binomial analysis of the CSU dataset to calculate probabilities of zero to ten years with one or more major North Indian Ocean hurricanes in the next decade. I conducted a geometric analysis to determine probabilities associated with waiting periods for the next year with a major hurricane, as well as a Poisson …

Ma(1) Or White Noise?, Orithea Regn, Ferebee Tunno

Create@State

This project provides an over of testing an MA(1) process confidence interval while keeping the margin of error to a minimum, even for small sample sizes.

Project G.L.E.N. (Enhancing Tornado Research: A Foundation For Transistioning The Enhanced Fujita Scale), Alexis Peshehonoff, Makaylei Huggins, Bernard Muich, Nicholas Fazzolari, Liam John, Harris Meyer, Jakob Graudons, Nicholas Krasznavolgyi, Stephen Syvertson, Aditya Bhattacharya, Kai Hong, Augustine Balish, Zachary Ort, Erin Rhoden

Student Research Symposium (SRS)

"Project G.L.E.N., formally known as “Enhancing Tornado Research: A Case for Transitioning the Enhanced Fujita Scale,” is an ongoing initiative aimed at advancing tornado research through the development and deployment of an unmanned tornado probe. Through the Gale Level Environmental Navigator (G.L.E.N.) probe, a remote-controlled unit equipped with specialized meteorological sensors and innovative design features, we aim to collect real-time, onsite data from within tornadoes. This approach allows for direct measurement of internal atmospheric conditions such as wind speeds, pressure fluctuations, temperature, humidity, and other storm dynamics while removing human risk from tornado interception, significantly enhancing the safety of storm …

Is Hockey Still Canada’S Game? How Usa Teams Have Won Every Stanley Cup Since 1994, Aaron Montgomery, Long Doan, Joe Demaio, Michael Frankel

Symposium of Student Scholars

The last Canadian team to win Lord Stanley’s cup in the National Hockey League was the Montreal Canadiens in 1993. Since then, each championship has been claimed by a team geographically located in the United States. Is this streak unusual? Perhaps it is particularly unusual in light of the fact that Hockey is known as Canada’s game. Is Hockey in its modern incarnation still Canada’s game? Given the long history of the NHL should we expect such a streak to occur at some point in time? Are we too fixated on the geographic location of the teams in question? Perhaps …

Explainable Post-Operative Patients Recovery Prediction Following Elective Brain Tumor Resection: A Precision Medicine Approach, Eleanor Belkin

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Kyda] Biologically Grounded Surrogate-Driven Parameter Inference For Sparsely Observed Dynamical Systems, Joshua C. Macdonald

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Project Insight] Spatio-Temporal Analysis Of Domestic Violence In Puerto Rico, Phyllis Muniu

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mentoring First-Year Stem Students Through Collaborative Research In The Haynes Scholars Program, Alex Capaldi, Laura Tipton

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Lele] Incorporating Physiological Constraints In Estimates Of Post-Prandial Insulin Secretion Rate, Justin K. Garrish, Christine L. Chan, Douglas Nychka, Cecilia Diniz Behn

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Correlation With Car Density In Urban Environments And Its Influence On Chronic Obstructive Pulmonary Disease (Copd) Rates In The United States, Daniel Barreiro-Torres, Kedai Cheng

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Reduced Order Approach For Peening Stress Field Variability, Langdon Feltner, Paul Mort

15th International Conference on Shot Peening

A common goal in shot peening research is to connect operational parameters to resultant residual stress fields, providing a means to control and optimize the effectiveness of surface treatment. In practice, experimental measurements of residual stresses are often averaged values over regions that are large in comparison to an impact dimple. In fact, the stochastic nature of impact locations leads to residual stress fields that are distributed. Finite element peening simulations confirm this observation. The goal of this report is to connect operational parameters to localized fluctuations in residual stress through probabilistic reasoning (Figure 1). In particular, the development of …

A Modern Analytical Method To Forecast Cerebrovascular Diseases (Cd), And Heart Diseases (Hd) Using Multivariate Time Series Model Utilizing The Cdc Provisional Mortality Data, Aditya Chakraborty, Mohan Pant

Cardiovascular Research Symposium

Background: In this study, a new analytical approach was introduced to answer specific questions related to mortalities due to cerebrovascular diseases, heart diseases, and the association of these mortalities with twelve other causes of death (COD).

Methods: A multivariate time series forecasting model was developed utilizing each of the CODs by taking the weekly and yearly seasonality into account, and the mortality counts were forecasted using the most recent CDC weekly mortality count data. A new COD data matrix was structured for all CODs as a function of weeks by combining the observed and predicted values of the mortality counts. …

Keynote - Data? We Don't Have Time For Data: A Realistic Look At Law Enforcement Use Of And Need For Human Trafficking Data, Doug Gilmer Phd

SMU Human Trafficking Data Conference

Drawing on over 35 years of law enforcement experience (25 years with the Department of Homeland Security), Dr. Gilmer will speak from a government and law enforcement perspective on the need and use for human trafficking data. Some agencies and components of the U.S. government, and individual states, are heavily invested in collecting data to satisfy their reporting requirements. From a law enforcement perspective, however, big human trafficking data sets are rarely examined. Data science in law enforcement is a relatively new phenomenon, and most law enforcement officers do not have the time, resources, or background to collect or analyze …

Sabrina Vs Steph: The Battle Between The Wnba And Nba, Naysha Mcgriff

Symposium of Student Scholars

The average salary of a Women’s National Basketball Association (WNBA) player is 110 times less than a National Basketball Association (NBA) player’s. Despite growing WNBA viewership, gender inequality in sports remains high, with critics claiming female athletes are less skilled. Gender bias in sports is severely understudied, making direct comparisons to men’s leagues unfair due to long-term lack of investment in women’s sports. This study investigates whether the perceived disparity in skill levels between WNBA and NBA players' is genuine or influenced more by external factors by developing an unbiased measure of player efficiency to compare athletic performance. This dataset …

Opioid Epidemic In Maine: An Analysis Of Increasing Overdose-Related Deaths Following The Coronavirus, Aysel S. Hamlin

Thinking Matters Symposium

The rate of drug overdose resulting in death doubled in Maine following the COVID-19 pandemic from the onset of the COVID-19 pandemic in late 2019 through 2022. The correlation between increased isolation during the pandemic and overdose death rates sheds a concerning light on the insufficient resources for people struggling with Opioid Use Disorder (OUD) throughout Maine. The increasing trade and access to fentanyl following the pandemic accounted for the majority of drug-related deaths in Maine in 2021 and 2022. This study examines the need for long-term access to drug treatment in rural and urban Maine, both environments with varying …

Leveraging Benford’S Law And Machine Learning For Financial Fraud Detection, Benjamin R. Fu

Cybersecurity Undergraduate Research Showcase

Financial fraud, particularly credit card fraud, continues to pose substantial challenges to financial institutions due to its increasing frequency and impact on consumer trust. While traditional rule-based methods have provided foundational defenses, their limitations in scalability and adaptability have accelerated the adoption of machine learning (ML) techniques. Concurrently, Benford’s Law—a statistical principle often used in forensic accounting—has demonstrated efficacy in detecting anomalies within naturally occurring numerical datasets. This study explores a hybrid fraud detection approach that integrates Benford’s Law with supervised machine learning algorithms, including Logistic Regression, Random Forest, and k-Nearest Neighbors. Using the publicly available European credit card fraud …

A Machine-Learning Tool-Supported Methodology For Nonprofit Donor Analysis, Corbin Weiss

Campus Research Month

We developed a machine-learning tool-supported methodology for modeling the nonprofit donor relationship. This approach was demonstrated in the case of a US-based nonprofit. Conclusions were drawn from this example and tool-support provided for use by other nonprofits.

Predicting Capture And Survival Probabilities Of The Arizona Tiger Salamander: A Comparison Of Capture-Recapture Models, Brittney Nelson

Scholars Week

Capture-recapture models are essential tools for estimating population dynamics in ecological studies. A fundamental component of these models is the capture history matrix, which records individual detection over time and serves as the basis for estimating survival and capture probabilities. This presentation explores three statistical approaches to these estimations: the Cormack-Jolly-Seber (CJS) model, the Hidden Markov Model (HMM) for CJS, and the Bayesian CJS model. The CJS model provides a likelihood-based framework for estimation, and the HMM CJS incorporates latent states into the model to account for uncertainty in detection. The Bayesian CJS extends this same analysis by integrating prior …

Robust Multifidelity Operator Learning For Partial Differential Equations, Jacob Hauck, Yanzhi Zhang

Miners Solving for Tomorrow Research Conference

No abstract provided.

Statistical Programming Package For Simplified Data Exploration, Liam Raymon, Jennifer Schon

Celebration of Research

Simple linear regression can be very helpful for exploring a dataset through identifying variable relationships and the percentage of variance in the dependent variable explained by the model. The project showcases a coding package for the statistical programming language R that I have created to provide a streamlined approach to exploring data through linear regression. Packages serve as extensions of coding languages to add features or functions. This package automates simple linear regression and outputs key values for data exploration such as p value, R^2, and independent variable coefficients in an organized and concise manner. In addition to regression, this …

Discounting Effect Size When Borrowing External Data In Clinical Studies, Zhuanzhuan Ma, Chul Ahn, Bin Wang, Xuefeng Li

Research Symposium

Background: When borrowing information from external data to augment a current trial, many available methods discount the sample size but retain the effect size from previous studies. Discounting the sample size is just one way to discount the prior information. It may not be appropriate if the underlying assumption of unbiased treatment effect does not hold, for example, when the treatment effect in the historical study is likely higher than the one expected in the current trial.

Methods: To tackle this potential issue, we study some methods to shrink the effect size from previous studies assuming that the prior effect …

Sparse Bayesian Variable Selection Using Global-Local Shrinkage Priors For The Analysis Of Cancer Datasets, Zhuanzhuan Ma

Research Symposium

Background: With a rapid development of data collection technology, high dimensional data, whose model dimension k may be growing or much larger than the sample size n, is becoming increasingly prevalent in different fields of study, such as ecology, genetics, among others. This data deluge is introducing new challenges to traditional statistical procedures and theories and is thus generating a renewed interest in the problems of variable selection and classification in high dimensional regression models. In large k, small n settings, variable selection is usually the first step for dimension reduction to uncover significant covariates, which contribute to …

Investigating The Relationship Between The Circadian Clock, Age, And Lifestyle, Samuel Park, Amaka Eziakonwa, Amega Nguyen, Madison Payne, Erich Stahmer, Alexis Salinas, Payson Broome, Angel Oliver, Christian Mccormick, Jasmyn Brown, Julie A. Zacharias-Simpson, Jutta Ward, Deborah Bell-Pedersen

Annual Research Symposium

This poster presentation aims to understand how circadian clock strength and phase are affected by age and lifestyle. By analyzing changes in physiological rhythms, the study seeks to develop strategies for promoting healthy aging by optimizing circadian function.

Tracking The Effects Of Time Zone Shift On An Individual’S Circadian Rhythm, Amaka Eziakonwa, Erich Stahmer, Amega Nguyen, Samuel Park, Madison Payne, Alexis Salinas, Deborah Bell-Pedersen, Julie A. Zacharias-Simpson

Annual Research Symposium

This poster presentation aims to understand how a rapid time-zone change can affect an individual’s circadian rhythms. By quantifying changes in physiological rhythms, the study seeks to develop targeted therapeutic interventions to mitigate the negative effects of jetlag.