AISC 2024 Conference

Accepted Abstracts

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Abstracts:

Farooq Ahmad – Process Modeling and Framework of Online Examination System

Shakeel Ahmed – On Some Strategies for Estimating Survival Function in Small Areas

Wedad Alatebi – Comparing Machine Learning Methods on a Breast Cancer Dataset

Aaid Algahtani – Extrinsic Principal Component Analysis

Badr Aloraini – Estimation of Population Variance Using Optional Randomized Response Technique Model in the Presence of Measurement Errors

Romesh Ruwan Thanuja Athuruliye Liyana Arachchige – A Novel Approach to Generating Axially Symmetric Random Processes on the Sphere

Kayode Ayinde – New Algorithms for Outlier’s Identification and Cluster Formation: Voting and Principal Component Analysis Techniques

Kayode Ayinde – On the Distribution of Absolute Deviations of Normal Distribution as Nakagami Distribution and Its Application into Hypothesis Testing

David Banks – Statistics and Large Language Models

David Banks – The Impact of Large Language Models

Steven Barnett – Computer Model Calibration for Large-Scale Spatially Distributed Counts

Paul Bendich – Topological Parallax: a Geometric Specification for Deep Perception Models

David R. Bickel – Logically Coherent Hypothesis Testing and Bayesian Model Checking

Yvonne Boafo – Impacts of Missing Data Imputation on Statistical Models for Environmental Mixtures

Festus Akwasi Boakye – A Comparative Study of Semi-parametric and Parametric Survival Models on the Analysis of ICU Patient’s Length of Stay

Annie Booth – Hybrid Monte Carlo for Failure Probability Estimation with Gaussian Process Surrogates

Nicholas Bussberg – Intrinsic Random Function Kriging on the Sphere

Leonardo Cella – Possibility-Theoretic Statistical Inference Offers Performance and Probativeness Assurances

Anam Chaudhry – Using Structural Equation Modeling to Study the Impact of Green Entrepreneurial Marketing on Purchasing Intention of Skin Care Products

Dongkyu (Derek) Cho – Fast Computer Model Calibration using Annealed and Transformed Variational Inference

Bipulkumar Das – Comparing Imputation Methods on Inference in High Throughput Data with an Example of Acute Myeloid Leukemia RNA Expression Study

Deeya Datta – Developing an R Package for Bayesian Ranking Using Credible Distributions

S. A. Kushani De Silva – Reformulating the Exploration Scaling to Improve Population-Size and Covariance Matrix Adapting Evolutionary Optimization Algorithm

Ian Dryden – Regression and Curve Fitting for Networks and Shapes

Katherine Ensor – Spatial-Temporal Modeling for Public Health Surveillance through Wastewater

Bruce Fang – Limiting Distributions in the Bulk and Blips of Matrix Ensembles Under Anticommutator Operators

Xinyu Fang – Benford’s Law and Random Integer Decomposition with Congruence Stopping Condition

Demba Fofana – Hybrid-testing Increases Power in Multiple Hypothesis Testing: Applications to Gene Expression Data

Subhashis Ghoshal – Optimal Bayesian Inference for High-Dimensional Linear Regression Based on Sparse Projection-Posterior

Jan Hannig – Semiparametric Fiducial Inference

Abeer Hasan – Dynamic Shifts: Advanced Applications of Change Point Detection with Skew-t Distribution

Abeer Hasan – Statistical Approaches to Sparse Data at Low PM2.5 Concentrations: Enhancing Mortality Risk Analysis

Junoh Heo – Active Learning for a Recursive Non-Additive Emulator for Multi-Fidelity Computer Experiments

Matthew Hill – The Operationalization and Validation of Chronic Stress

Chao-hui Huang – Uniform Placement of Alter-nodes on a Spherical Surface (U-PASS) for Ego-Centric Network and its Link to Minimum Energy Designs

Michael Hull – Gaussian Persistence Curves

Amjad Javaid – New Sample Design for 7th Agricultural Census of Pakistan (Integrated Digital Count)

Yi (Irene) Ji – Testing JMP Torch Deep Learning Add-in – A Case Study in Blocked Covering Array

Thomas Johnson III – Model-Assisted Estimation from Randomized Response Data with High-Dimensional Auxiliary Information

Geeta Kalucha – Field Validation of the Mixture Binary RRT Model: Assessing Measurement Errors and Respondent Trust in Sensitive Surveys

Sadia Khalil – The Effect of Measurement Error on Binary RRT Models

Zaheen Khan – Diagonal Modified Systematic Sampling Scheme

Hwanwoo Kim – Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

Arielle King – Factors Impacting Big Data Research Within U.S. Higher Education

Brian Kundinger – Efficient and Scalable Bayesian Record Linkage with Variational Inference

Daoji Li – Nonparametric Screening for Additive Quantile Regression in Ultra-high Dimension

Lexin Li – Statistical Neuroimaging Analysis: An Overview

Yao Li – Defense Against Syntactic Textual Backdoor Attacks

Xueying Liu – Data Composition: A New Experimental Design Problem With Application in Continual Learning

Yufeng Liu – Hub Detection in Gaussian Graphical Models

Miodrag Lovric – Rethinking Statistical Inference: Moving from Point-Null Hypotheses to Interval-Based Approaches in the Wake of the Rao-Lovric Theorem

Joshua Lukemire – Computationally Efficient Approaches to Finding Optimal Designs for the Panel Mixed Logit Model

Changzhi Ma – Estimation of the Long-Range Dependence Parameter With Stationary Increments

Simon Mak – Local Transfer Learning Gaussian Processes for Cost-Efficient Surrogate Modeling of Expensive Computer Experiments

Abhyuday Mandal – Credible Distributions of Overall Ranking of Entities

Jay Mandrekar – Developing and Validating a Predictive Score: A Statistical Analysis in Neurocritical Care?

John Miller – Input Warping Designs for Computer Experiments

Sayed Mostafa – Kernel-based Estimation of Probability Mass Functions Under Ranked Set Sampling

Ismail Muhammad – Efficient Generalized Estimators for Variance Using Auxiliary Information in Simple Random Sampling

Ismail Muhammad – Evaluating Trends and Instabilities of Wet and Dry Events: A Multi-station Examination based on Meteorological Drought Index in Punjab, Pakistan

Eva Murphy – Spatio-Temporal Modeling of the Wind Speed Data

Praise Obanya – Condition Monitoring of Industrial Processes Using Permutation Entropy

Garett Ordway – Mutations Galore: SARS-Cov-2 Trees from a Variety of Perspectives

Adithya Penagonda – Dynamic Graph Neural Networks for Predicting Tumor Microenvironment Evolution and Therapeutic Resistance

Jie Peng – Multiple Comparison Procedures for Binomial Distributions

Chaichana Prasertsrithong – Constructing Covariance Functions for Complex Random Processes

Shih-Ni Prim – Active Learning with Multiple Contour Estimation for Trimmed Aero Database Construction

Wanli Qiao – Embedding Distributional Data: Multidimensional Scaling and Manifold Learning

Marepalli Rao – Models for Destructive Data in Cancer Drug Trials

Nasser Sadeghkhani – Inferecne in Multivariate Interval-Valued Data

Pujita Sapra – Mitigating Lack of Trust in Quantitative RRT Models Using Auxiliary Information

Reetika Sarkar – Improved Apriori Method for Safety Signal Detection Using Post-Marketing Clinical Data

Radmila Sazdanovic – Comparative Cancer Genomics Using TDA

Joshua Slater – Methods of Exploring the Space of Simple Weighted Graphs which Share a Common Persistence Diagram

Kimberly Sellers – Multivariate Approaches Towards Modeling Count Data

Javid Shabbir – On Estimating the Mean of Two Quantitative Sensitive Variables Simultaneously Under New Partial Scrambled Randomized Response (SRR) Model

Islina Shan – Is ChatGPT More Biased Than You? Uncovering Embedded Bias and Beyond in Gen AI

Chenlu Shi – Results on Large Strong Orthogonal Arrays of Strength Three

Alien Shrestha – Predictive Regression With Multiple Endogenous Variables

Jenna Shuffelton – Hyperbishops, Hyperrooks, and Hyperqueens: Percentage of Safe Squares on Higher Dimension Chessboards

Poonam Singh – Estimation of Population Mean Using Neutrosophic Exponential Estimators With an Application to Real Data

Sloka Sudhin – d-QPSO: An R Package for Searching for Efficient Designs Under Generalized Linear Models

John Stufken – Subsampling for Big Data

Jianping Sun – An Application of GAM Model in Analyzing Intensive Repeated Measures

Ahmad Talafha – Impact of Smoothing Techniques on Bootstrap Aggregated Classification for Sparse Functional Data

Pidugu Trisandhya – Analysing the Behaviour of Measurement Error for Sensitive Mean Estimation in Two-Move Successive Sampling

Osasenaga Usoh – Harnessing AI and Machine Learning to Break Barriers: Transforming the Education (FAFSA) System for Equitable Access to Higher Education

Sylvia Vincent – Monitoring and Diagnosis of Particle Detector Faults via Topological Data Analysis

Saad Waheed – Extending James’ Pythagorean Formula to Head-to-Head Matchups in Baseball

Huixia Judy Wang – Conformal Prediction in Non-Exchangeable Data Contexts

Lin Wang – Active Subsampling for High-Dimensional Ridge Estimator With Application in Genome-Wide Association Studies

Thomas Weighill – Generalized Dimension Reduction Using Optimal Transport

Nate Wiecha – Interpretable, Approximate Gaussian Process Regression with Variable Selection for Chemical Mixture Analysis

Mazhar Yaqub – Estimation of the Finite Population Coefficient of Variation under Stratified Random Sampling

Jie Yang – Constrained D-optimal Design for Paid Research Study

Prachet Yerramalla and Adithya Penagonda – Optimizing Urban Traffic Signal Timings with Reinforcement Learning: A Comprehensive Simulation Study

Huijun Yi – Investigating the Lifetime Performance Index of the Generalized Inverted Exponential Distribution Under Balanced Loss Functions

Richard Zhao – Measuring Recruit Growth Using Artificial Intelligence

Qiong Zhang – Sequential Design for Parameter Optimization via Curing Process Simulation

Wei Zheng – Fast Approximation of Shapley Values through Fractional Factorial Designs

Ling Zhou – Toroidal Coordinates: Decorrelating Circular Coordinates With Lattice Reduction

Xietao Zhou – Optimal Designs Under Model Uncertainty