Friday, April 12th PROGRAM OUTLINE
3:00pm Registration Table Opens [Outside of LOW 3215]
3:30 - 4:00 Welcome! [LOW 3215]
4:00 – 7:00 Tutorials, bring laptops!
4:00 - 5:00 pm
T1A: Introduction to Causal Inference [LOW 3105]
Teresa Gibson, PhD, Professor of Practice, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic to intermediate
T1B: Websites/Webservers & Web Graphics for Beginners [LOW 3115]
Gregory Babbitt, PhD, Associate Professor, Gosnell School of Life Sciences, Rochester Institute of Technology
Level: Basic
T1C: A Gentle Introduction to Diffusion Models in Machine Learning (Part 1) [LOW 3245]
Zi-Jia Gong, Graduate Student, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic to Intermediate
5:00 - 6:00 pm
T2A: Community Detection in Complex Networks [LOW 3105]
Nishant Malik, PhD, Assistant Professor, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic
T2B: Introduction to Basic Bioinformatics Concepts & Databases for Beginners [LOW 3115]
Gregory Babbitt, PhD, Associate Professor, Gosnell School of Life Sciences, Rochester Institute of Technology
Level: Basic
T2C: A Gentle Introduction to Diffusion Models in Machine Learning (Part 2) [LOW 3245]
Zi-Jia Gong, Graduate Student, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic to Intermediate
Canceled
T2D: Demystifying Tiny GPT: Hands-On Training with PyTorch (Part 1) [LOW 1135]
Bardh Rushiti, Co-founder @ AI Kosovo, Computer Vision & AI Engineer @ Calvary Robotics
Level: Intermediate
6:00 - 7:00 pm
T3A: AntiCopyPaster: An Open-Source Ecosystem for Just-in-time Code Duplicates Extraction [LOW 3105]
Mohamed Wiem Mkaouer, PhD, Assistant Professor, Software Engineering, Rochester Institute of Technology
Level: Basic to Intermediate
T3B: An Introduction to the Conformal Prediction Approach to Uncertainty Quantification [LOW 3115]
Ernest Fokoue, PhD, Professor, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Intermediate
T3C: Introduction to Research Computing at RIT [LOW 3245]
Benjamin Meyers, PhD, Research Computing, Rochester Institute of Technology
Level: Intermediate
Canceled
T3D: Demystifying Tiny GPT: Hands-On Training with PyTorch (Part 2) [LOW 1135]
Bardh Rushiti, Co-founder @ AI Kosovo, Computer Vision & AI Engineer @ Calvary Robotics
Level: Intermediate
7:00 - 8:00 Cocktail Hour & Poster Session [A950 – Atrium Area]
8:00 - 9:30 Panel Discussion [LOW 3215]
On the Artificial Intelligence Revolution and Disruption: A candid exploration of the Opportunities and Challenges of the AI revolution, and Disruption in Science and Beyond
Moderator: Gregory Babbitt, Associate Professor, College of Science, Rochester Institute of Technology
Panelists
John McCluskey, PhD
Professor
Criminal Justice
Rochester Institute of Technology
Joaquin Carbonara, PhD
Professor
Mathematics and Statistics
SUNY Buffalo State
Ernest Fokoue, PhD
Professor
Mathematics and Statistics
Rochester Institute of Technology
Saturday, April 13th
8:00am Registration Table Opens [Outside of LOW 3215]
8:30-9:00 Welcome & Breakfast [LOW 3215]
9:00-9:55 Parallel Sessions 1
Invited Session 1A: An exploration of AI assisted research in Criminal Justice [LOW 3225]
Session 1B: New Ideas for the Classroom [LOW 3235]
Session 1C: When Assumptions are Violated [LOW 3245]
10:00-10:55 Parallel Sessions 2
Invited Session 2A: Federated Learning with Data Quality and Security Evaluated OR [LOW 3225]
How to Make Distributed Machine Learning Work in Real-Life?
Invited Session 2B: Recent Advances in Reproducibility in Statistical Learning Using Jupyter [LOW 3235]
Session 2C: Statistics on the Water’s Edge [LOW 3245]
11:00-11:55 Parallel Sessions 3
Invited Session 3A: Network Analysis [LOW 1135]
Session 3B: Analyzing the Lingering Effects of COVID [LOW 3225]
Session 3C: Improving Student Success in the Classroom [LOW 3235]
Session 3D: Classification Methods [LOW 3245]
12:00-1:00 Lunch with Poster Session [Posters in LOW 1225/1235]
1:15-2:25 Parallel Sessions 4
Invited Session 4A: Accelerating Science with High-Performance Computing [LOW 1135]
Session 4B: Bayesian Methods [LOW 3225]
Session 4C: For the Theorists [LOW 3235]
Session 4D: Working with Large Complex Data [LOW 3245]
2:30-3:25 Parallel Sessions 5
Invited Session 5A: Subsampling & Neural Networks [LOW 3225]
Session 5B: Changing Viewpoints in Statistical Education [LOW 3235]
Session 5C: New Tools in the Field [LOW 3245]
3:30-4:00 DataFest 2024 Winner Presentations - Insights [LOW 3215]
Winning teams composed of local undergraduate students from DataFest 2024 will present their findings.
3:30 – 3:40 Enhancing Statistical Learning: Leveraging Kolb's Cycle in CourseKata Curriculum
Analysis
Team Positiv Correlation, Insights
Jonathan Bateman, Cara Stievater, Nishka Desai, Vivian Hernandez, Jack Cawthon
Undergraduate Students, Rochester Institute of Technology
3:40 – 3:50 Mixed Models and Imputation: Tackling the DataFest Dataset
Team Big Data Energy, Insights
Daniel Illera, George Daher, Isabella Wang
Undergraduate Students, University of Rochester
3:50 – 4:00 Backtrack to Success with CourseKata
Team Feisty Folk, Insights
Quan Lu, Gabriel Casselman, Jonah White, Ben Knigin
4:00-4:30 Break & Student Awards Judging
4:30-5:00 Awards & Closing Remarks [LOW 3215]
DETAILED PARALLEL TALK SCHEDULE FOR SATURDAY, APRIL 13
§ Indicates presentations that are eligible for the student presentation awards.
INVITED SESSION 1A LOW 3225
An exploration of AI assisted research in Criminal Justice
Session Organizers & Chairs: John McCluskey and Irshad Altheimer, Professors, RIT Department of Criminal Justice and Center for Public Safety Initiatives
9:00-9:15 Exploring race and crime in a rustbelt town using AI assisted analysis
Venita D’Angelo, Graduate Student, Rochester Institute of Technology
O. Nicholas Robertson, Associate Professor, Rochester Institute of Technology
9:20-9:35 AI Assisted Exploration of RPD Traffic Stop Data
Irshad Altheimer, Professor, RIT Department of Criminal Justice & Center for Public Safety Initiatives
Jillian Antol & Ava Douglas, Undergraduate Students, Rochester Institute of Technology
9:40-9:55 AI assisted analysis of survey data on adoption, use, and consequences of body-worn cameras in the Monroe County Sheriff’s Office
Owen Shedden, Graduate Student, Department of Criminal Justice, Rochester Institute of Technology
John McCluskey, Professor, Department of Criminal Justice, Rochester Institute of Technology
SESSION 1B LOW 3235
New Ideas for the Classroom
Session Chair: Trijya Singh, Associate Professor, Le Moyne College
9:00-9:15 Community-Engaged Data & Analytics Education: Empowering the Student & the
Community Organization
Travis Brodbeck, Associate Director of Data Management, Siena College
9:20-9:35 Building a Data Science Collaboratory
William Cipolli, Associate Professor, Department of Mathematics, Colgate University
9:40-9:55 Probability Playground: Five Years On §
Adam Cunningham, Undergraduate Student, University at Buffalo
SESSION 1C LOW 3245
When Assumptions are Violated
Session Chair: Tanzy Love, Professor, University of Rochester, Biostatistics & Computational Biology
9:00-9:15 Hypothesis Testing about the Pearson and Spearman Correlation Coefficients: Navigating Pitfalls, Software Anomalies, and Alternative Approaches §
Mengyu Fang, Graduate Student, Roswell Park Comprehensive Cancer Center
9:20-9:35 Implementing Empirical Likelihood Within the Causal Inference Framework to Study Causal Effects of Air Pollution on Birth Outcomes
Sima Sharghi, Postdoctoral Researcher, University of Rochester Medical Center
9:40-9:55 Interval-specific censoring set adjusted Kaplan–Meier estimator
Yaoshi Wu, PhD, Statistics, Director, Biostatistics/Biometrics, Cytokinetics
INVITED SESSION 2A LOW 3225
Federated Learning with Data Quality and Security Evaluated OR
How to Make Distributed Machine Learning Work in Real-Life?
Session Chair: Sergei Chuprov, Graduate Student, Rochester Institute of Technology
10:00-10:15 Data Quality Evaluation for Federated Learning OR
What to Look at in Order to Improve FL?
Leon Reznik, Professor, Rochester Institute of Technology
10:20-10:35 Current Trends in Federated Learning: Do they Align with Real-world Application Requirements? §
Raman Zatsarenko, Undergraduate Student, Rochester Institute of Technology
10:40-10:55 Improving Federated Learning Robustness towards Security Violations & Data Quality Degradations OR How to Learn Better via Extracting Knowledge and Accumulating History? §
Sergei Chuprov, Graduate Student, Rochester Institute of Technology
INVITED SESSION 2B LOW 3235
Recent Advances in Reproducibility in Statistical Learning using Jupyter
Session Chair: Yang Liu, Graduate Student, Rochester Institute of Technology
10:00-10:15 A focus on the strengths of Julia for Reproducibility §
Yang Liu, Graduate Student, Rochester Institute of Technology
10:20-10:35 Exploration of Python tools for reproducibility
Gregory Babbitt, PhD, Associate Professor, Gosnell School of Life Sciences, Rochester Institute of Technology
10:40-10:55 How well does R help achieve reproducibility in Statistical Learning and Estimation?
Ernest Fokoue, PhD, Professor, School of Mathematics & Statistics, Rochester Institute of Technology
SESSION 2C LOW 3245
Statistics on the Water’s Edge
Session Chair: Meghan Childs, Graduate Student, Rochester Institute of Technology
10:00-10:15 Improving Coastal Adaptation Decision-Making Using a Robust Decision Criterion §
Carolina Estevez, Graduate Student, Rochester Institute of Technology
10:20-10:35 Forecasting Epidemiology: Time Series Modeling of the West Nile Virus §
Kiersten Winter, Undergraduate Student, Rochester Institute of Technology
10:40-10:55 Understanding the Impact of Structural Uncertainty in Sea Level Rise Models on Adaptation Costs and Strategies §
Kelly Feke, Undergraduate Student, Rochester Institute of Technology
INVITED SESSION 3A LOW 1135
Network Analysis
Session Organizer/Chair: Marianthi Markatou, PhD, SUNY Distinguished Professor, University at Buffalo
11:00-11:25 Correlation network analysis
Naoki Masuda, Professor, Department of Mathematics & Institute of Artificial Intelligence & Data Science, University at Buffalo
11:30-11:55 Identifying brain network trajectories after traumatic brain injury
Sarah Muldoon, Associate Professor, Department of Mathematics & Institute of Artificial Intelligence & Data Science, University at Buffalo
SESSION 3B LOW 3225
Analyzing the Lingering Effects of COVID
Session Chair: Ernest Fokoué, Professor, Rochester Institute of Technology
11:00-11:25 Assessment of the effectiveness of required weekly COVID-19 surveillance antigen testing at a university
Christopher W. Ryan, Professor, SUNY Upstate Medical University, and Agency Statistical Consulting, LLC
11:30-11:55 Impact of COVID-19 on English Football Premier League: Analyzing Rankings and Home-Field Advantage Using New Extended Bradley-Terry Models
Honghong Liu, Graduate Student, University of Rochester, Department of Biostatistics & Computational Biology
SESSION 3C LOW 3235
Improving Student Success in the Classroom
Session Chair: Trijya Singh, Associate Professor, Le Moyne College
11:00-11:25 How can we leverage Large Language Models to Engage Students in Software Quality Improvement
Mohamed Wiem Mkaouer, PhD, Assistant Professor, Software Engineering, Rochester Institute of Technology
11:30-11:55 Analyzing the Impact of the Learning Assistant Program on Student Success in Introductory Physics Courses §
Cameron Bundy, Graduate Student, Rochester Institute of Technology
SESSION 3D LOW 3245
Classification Methods
Session Chair: Tanzy Love, Professor, University of Rochester, Biostatistics & Computational Biology
11:00-11:25 A Model-Based Clustering Method for High-Dimensional, Dependent Data with Categorical Outcomes §
Samantha Manning, Graduate Student, University of Rochester
11:30-11:55 Evaluating Joint Confidence Region of Hypervolume under ROC Manifold and Generalized Youden Index §
Jia Wang, Graduate Student, University at Buffalo
INVITED SESSION 4A LOW 1135
Accelerating Science with High-Performance Computing
Session Organizers: Benjamin Meyers & Kirk Anne, PhDs, Research Computing Laboratory, RIT
Session Chair: Benjamin Meyers, PhD, Research Computing Laboratory, RIT
This session showcases research that has been accelerated through the use of high-performance computing.
1:15-1:35 MELD: A Bayesian Framework to Accelerate Biomolecular Simulations Using External Data §
Alfonso Sierra Uran, Graduate Student, RIT Kate Gleason College of Engineering
Emiliano Brini, Assistant Professor, Rochester Institute of Technology, School of Chemistry & Materials Science
1:40-2:00 Hybrid Heating Optimization: Balancing Comfort and Cost with Electrical Heat Pumps and Natural Gas Furnaces
Sydney Pendelberry, Research Computing Facilitator III, Rochester Institute of Technology
2:05-2:25 Unaccounted for Uncertainty: The Significance of Uncertainty in the Optimization of the Kidney Exchange Problems
Calvin Nau, Graduate Student, Rochester Institute of Technology, Dept. of Industrial & Systems Engineering
Prashant Sankaran, Moises Sudit, Payam Khazaelpour, Katie McConky, Alvaro Velasquez, Liise Kayler
SESSION 4B LOW 3225
Bayesian Methods
Session Chair: Tanzy Love, Professor, University of Rochester, Biostatistics & Computational Biology
1:15-1:35 A hierarchical Bayesian model for the identification of technical length variants in miRNA sequencing data §
Hannah K. Swan, Graduate Student, University of Rochester
1:40-2:00 Bayesian Infinite Mixture Models for Clustering Exposure Data §
Jonathan Klus, Graduate Student, University of Rochester
2:05-2:25 A Bayesian framework for medical product safety assessment using correlated spontaneous reporting system data §
Xin-Wei Huang, Graduate Student, University at Buffalo
SESSION 4C LOW 3235
For the Theorists
Session Chair: Trijya Singh, Associate Professor, Le Moyne College
1:15-1:35 The Asymptotic Distributions of Generalized Win Odds §
Honghong Liu, Graduate Student, University of Rochester
1:40-2:00 Image Processing with Optimally Designed Parabolic Partial Differential Equation §
Qiuyi Wu, Graduate Student, University of Rochester
2:05-2:25 A new class of odd Lindley type distributions and its applications
Nonhle Channon Mdziniso, Assistant Professor, Rochester Institute of Technology
SESSION 4D LOW 3245
Working with Large Complex Data
Session Chair: Ernest Fokoué, Professor, Rochester Institute of Technology
1:15-1:35 Differential abundance analysis method for identifying biologically relevant microbes §
Robert Beblavy, Graduate Student, University of Rochester
1:40-2:00 Veracity Analysis: Current Methods and Limitations §
Le Nguyen, Graduate Student, Rochester Institute of Technology
2:05-2:25 Detection of interpretable communities in multilayer biological networks using a penalized sparse factor model §
Saiful Islam, Graduate Student, University at Buffalo
INVITED SESSION 5A LOW 3225
Subsampling and Neural Networks
Session Organizer: Marianthi Markatou, PhD, SUNY Distinguished Professor, University at Buffalo
Session Chair: Ernest Fokoué, Professor, Rochester Institute of Technology
2:30-2:55 Statistical perspectives on the use of neural networks for clinical prognosis
Douglas Landsittel, Professor, Department of Biostatistics, SPHHP, University at Buffalo
3:00-3:25 Data Integration and Subsampling Techniques in Distribution Estimation for Event Times with Missing Origins
Yi Xiong, Professor, Department of Biostatistics, SPHHP, University at Buffalo
SESSION 5B LOW 3235
Changing Viewpoints in Statistical Education
Session Chair: Trijya Singh, Associate Professor, Le Moyne College
2:30-2:55 Exploring Statistical Ethics with Students
Caitlin Cunningham, Associate Professor, Dept Chair of Mathematics, Le Moyne College
3:00-3:25 Improving Students' Perspectives on Statistics: From Loathing to Loving §
Kylee A. Healy, Undergraduate Student, Niagara University
SESSION 5C LOW 3245
New Tools in the Field
Session Chair: Tanzy Love, Professor, University of Rochester, Biostatistics & Computational Biology
2:30-2:55 Evaluation of the TreeScan method for Adverse Event Identification §
Raktim Mukhopadhyay, Graduate Student, University at Buffalo
3:00-3:25 QuadratiK: A Comprehensive Tool for Goodness-of-Fit Tests and Spherical Data Clustering
Giovanni Saraceno, Postdoctoral Researcher, University at Buffalo