Data Science Commons^™

Assessing Trends In Medical Students’ Perceptions Regarding Statistical Analysis, Ethan Noble, Valeriy Kozmenko, Paul Thompson

Scholarship Pathways Program

Assessing Trends in Medical Students’ Perceptions Regarding Data Analysis and Statistics Knowledge and Skills

Ethan Noble, MD | Mentors: Valeriy Kozmenko, MD, Paul Thompson, PhD

Introduction: The use of evidence-based medicine requires that physicians are able to properly analyze and interpret the results of new research. The development of new research and medical knowledge is swift, and a strong foundation in statistics and research is needed for physicians and medical students to keep up with new research. Curriculum in medical education often lacks in-depth coverage of the subject, and additional curriculum has been shown to enhance student confidence and ability …

Harvest Scanner, Alexander Murphy

Posters - 2026

In current times, people can find themselves at the whims of markets and may be spending more than they realize or want to on regular, everyday goods. New tools can help users keep track of the goods they are paying for. Harvest Scanner was developed to scan and track local grocery prices from stores using their publicly available website information. It was developed in Python using PyQt5 for GUI. The database is stored as an SQL file with Python using SQLite engine. Users will be able to view local grocery prices in a database interface (GUI). There are many features …

Enhancing Financial Audit Operations Through Ai Anomaly Detection, Nadya Cousin, Rebekah Garza, Talisa Gomez

Posters - 2026

❖ Financial auditing plays a critical role in ensuring accuracy, regulatory compliance, and fraud detection in financial reporting

❖ Traditional audit approaches rely heavily on sampling and manual review processes, limiting their ability to scale with increasing data complexity

❖ The rapid growth of high-volume, high-velocity financial data (big data) has exposed significant limitations in traditional auditing, including:

• Incomplete data coverage
• Delayed anomaly detection
• Increased risk of material misstatements

❖ These limitations create a need for scalable, automated, and data-driven audit solutions

❖ Artificial Intelligence (AI), particularly anomaly detection models, enables:

•  Full-population testing
•  Real-time pattern recognition
•  Proactive risk identification

Maddenlite, Sergio Pena

Posters - 2026

Sports simulations often rely on opaque, proprietary algorithms (like EA's Madden NFL). MaddenLite bridges the gap between sports analytics and interactive gaming by utilizing historical NFL Play-by-Play (PBP) data to drive a transparent, mathematically accurate simulation engine. The goal was to create a lightweight, UI-driven desktop application where users can simulate cross-era matchups (e.g., 2007 Patriots vs. 2025 Chiefs), manipulate rosters, and simulate entire seasons complete with official NFL tiebreaker protocols.

Using Ai-Based Predictive Scheduling To Improve Patient Flow And Reduce Wait Times In Healthcare Clinics, Oscar Martinez

Posters - 2026

• Healthcare systems face increasing challenges in patient access and wait times
• Average wait times for specialist care continue to rise, creating:
  • Delays in treatment
  • Reduced patient satisfaction
  • Increased system inefficiencies (Sanford, 2025)
• A major contributor is operational bottlenecks, defined as:
  • Points of congestion that slow or disrupt service flow
• Hospitals typically operate under process layouts, which:
  • Handle diverse patient needs
  • Reduce specialization efficiency
• Contributing factors to bottlenecks:
  • Physician shortages and burnout
  • Administrative burden
  • Inefficient scheduling systems (Moura & Pinho, 2025)
• AI offers potential solutions through:
  • Predictive scheduling
  • Automation of administrative processes
  • Data-driven optimization of patient flow

Optimizing Retail Grocery Inventory Using Ai And Large Language Models: Evidence On Forecast Accuracy, Waste Reduction, And Cost Efficiency, Robert Miller, Stephen Garcia, Brandon Ermis

Posters - 2026

Aim: To evaluate how AI and LLMs improve forecasting accuracy, reduce waste, and enhance inventory decision-making

Evaluating The Effects Of Anti-Forensic Activities In Additive Manufacturing Devices, Daniel B. Miller

Shelby Hall Graduate Research Forum Posters

Additive Manufacturing (AM) is a newer famlily of production tecchologies that constructs objects by fusing layers of material into the desired shape. Methods for achieving this as described in Gibson et al. [1] are varied and include Fused Filament Deposition, Selective Laser Sintering, Stereolithography (SLA), and Powder Bed Fusion. Computers are integral to the processes being responsible for creating and decoding design instructions, collecting and processing sensor data, and, ultimately, directing the activity of the machines which implement the process. Additionally, the AM industry is rapidly expanding, worth an estimated $23 billion in 2023 and projected to reach $88 billion …

Cellebrite Reliability In Digital Forensics, Christina Huynh

Shelby Hall Graduate Research Forum Posters

Forensic tools like Cellebrite are commonly used in court to gather and interpret raw data for evidence. Cellebrite does not only collect data but creates and interprets the artifacts of data to create a scene of the process it has been through. With this, evidence can be influenced by software designs and not just the data on the mobile device. Courts and police use Cellebrite to gather evidence and reconstruct it to create an easily readable dataset. These tools lack reproducibility, transparency, integrity, and chain of evidence command. Cellebrite is often used in court and by police without further vetting …

Binge Buddies, Joshua Uribe

Posters - 2025

Many people struggle to keep track of the shows and movies they’ve watched or plan to watch. Existing streaming platforms often provide limited or cluttered tracking features, making it challenging to stay organized. Binge Buddies addresses this issue by centralizing watchlists and viewing history in one streamlined location. The website is designed to simplify the binge-watching experience, helping users stay on top of their content and discover new shows/movies. Which makes the experience a smoother and more enjoyable experience.

Topical Text Segmentation For Stream Of Consciousness Writing, Yuwei Lu, Ryan Benton

Shelby Hall Graduate Research Forum Posters

Stream of consciousness writing has a long history, including novelists James Joyce and Virginia Woolf. However, there has been little work done in automated and semi-automated analysis of such writing, which is the focus of this work. We plan to divide real streams of consciousness writing into distinct topical units and then capture different momentary meaningful topics from these units. By doing this, researchers and readers could gain a more nuanced understanding of the narrative structure and thematic elements. In addition, it would also support applications in fields like psychology and linguistics, where understanding thought processes and narrative structures is …

2024 Gateway Magazine, College Of Computing, Michigan Technological University

College of Computing Annual Magazines

Table of Contents

• 50 Years of Computer Science at Michigan Tech
• Data Science for a Changing Planet
• Healthcare Transformed
• Mechatronics Matters
• Powered by Michigan Tech Talent
• Esports: Bringing Everything Great about Sports to More People
• The Michigander Scholars Program: Electrifying Careers in Michigan
• College of Computing News

Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu

College of Sciences Posters

Metadata quality is crucial for digital objects to be discovered through digital library interfaces. Although DL systems have adopted Dublin Core to standardize metadata formats (e.g., ETD-MS v1.1¹), the metadata of digital objects may contain incomplete, inconsistent, and incorrect values [1]. Most existing frameworks to improve metadata quality rely on crowdsourced correction approaches, e.g., [2]. Such methods are usually slow and biased toward documents that are more discoverable by users. Artificial intelligence (AI) based methods can be adopted to overcome this limit by automatically detecting, correcting, and canonicalizing the metadata, featuring quick and unbiased responses to document metadata. …

X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna

College of Sciences Posters

Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and …

Prevention Research Center For Healthy Neighborhoods, Madeline Panus

Celebration of Scholarship 2023

No abstract provided.

Data, Knowledge Practices, And Naturecultural Worlds: Vehicle Emissions In The Anthropocene, Lindsay Poirier

Statistical and Data Sciences: Faculty Books

This chapter details the various techno-cultural assemblages giving rise to data collected to model and measure anthropogenic worlds, arguing that data-based technologies both represent and co-produce the Anthropocene. It begins with a review of scholarship emerging at the intersection of science and technology studies and information studies that advances understanding of data infrastructure and knowledge practices, and their role within the anthropogenic assemblages that shape history. Drawing on a case study describing how vehicle emissions are measured and regulated in the US, I examine the materialities and mutability of technologies designed to produce data about air quality, along with the …

Benefits Of The Snakemake Workflow Management Software In Comparision To Traditional Programming (Presentation), Josh Loecker

Honors Capstone Projects

No abstract provided.

Data-Limited Domain Adaptation And Transfer Learning For Learning Latent Expression Labels Of Child Facial Expression Images, Megan Witherow, Winston Shields, Manar Samad, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

While state-of-the-art deep learning models have demonstrated success in adult facial expression classification by leveraging large, labeled datasets, labeled data for child facial expression classification is limited. Due to differences in facial morphology and development in child and adult faces, deep learning models trained on adult data do not generalize well to child data. Recent deep domain adaptation approaches have improved the generalizability of models trained on a source domain to a target domain with few labeled samples. We propose that incorporating steps of deep transfer learning, e.g. weights initialization from the pre-trained source model and freezing model layers, may …

Iba Newsletter [August 2020], Communications Department, Office Of The Registrar

IBA News

No abstract provided.

Data Science In The Public Interest: Improving Government Performance In The Workforce, Joshua D. Hawley

Upjohn Press

This book is about how new and underutilized types of big data sources can inform public policy decisions related to workforce development. Hawley describes how government is currently using data to inform decisions about the workforce at the state and local levels. He then moves beyond standardized performance metrics designed to serve federal agency requirements and discusses how government can improve data gathering and analysis to provide better, up-to-date information for government decision making.

Iba Newsletter [July 2020], Communications Department, Office Of The Registrar

IBA News

No abstract provided.

Feature Extraction And Analysis Of Binaries For Classification, Micah Flack

Annual Research Symposium

The research project, Feature Extraction and, Analysis of Binaries for Classification, provides an in-depth examination of the features shared by unlabeled binary samples, for classification into the categories of benign or malicious software using several different methods. Because of the time it takes to manually analyze or reverse engineer binaries to determine their function, the ability to gather features and then instantly classify samples without explicitly programming the solution is incredibly valuable. It is possible to use an online service; however, this is not always viable depending on the sensitivity of the binary. With Python3 and the Pefile library, we …

Interview With Deborah Winslow Of The National Science Foundation, Jerome W. Crowder, Mike Fortun, Rachel Besara, Lindsay Poirier

Statistical and Data Sciences: Faculty Books

Chapter Abstract:

In this chapter the editors interview Dr. Deborah Winslow about her work at the National Science Foundation (NSF) and the evolution of data management plans (DMPs) in Anthropology and the Social, Behavioral and Economic Sciences (SBE). She outlines what the NSF expects to see in a DMP and what not to include. The conversation moves into how anthropologists collaborate with “adjacent disciplines” and how the ideas and terms for data, and the expectations of data change. She emphasizes thinking about the kind of data you will collect and what you plan to do with those data later, in …

Deep Learning For Multisensor Image Resolution Enhancement, Charles B. Collins, John M. Beck, Susan M. Bridges, John A. Rushing

Research Horizons Day Posters

No abstract provided.

Mapping Opioid Mortality Rates Across Treatment Capacity To Identify Need And Access, Garrett K. Wong, Justin R. Chang, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow

Graduate Research Posters

Background: The opioid and heroin overdose epidemic is a public health emergency in the state of Virginia, resulting in the death of more than 1,100 people in 2016. In order to overcome this epidemic, we need to match the places with the greatest need for services related to substance use disorders with the appropriate healthcare workforce.

Aims: As the data about the overdose outbreak and related socioeconomic factors grow in size and complexity, data scientists have attempted to utilize big data techniques to identify communities and risk factors contributing to addiction.

Methods: Using data obtained from the …

Visualizing The Opioid Overdose With A Dynamic Heat Map To Identify And Predict Vulnerable Communities, Justin R. Chang, Garrett K. Wong, Chase Greco, Yadunandan Pillai, Mohammad A. Shahrezaei, Melissa H. Burton, Rob Lawrence, Alan Dow

Graduate Research Posters

Background: Opioid and heroin overdose epidemic is a public health emergency in the state of Virginia. In order to prevent overdose deaths, we need the target expertise in substance use disorders to areas with high rates of overdose. In particular, an area with an acute spike in overdoses might represent an urgent need for intervention.

Aims: The CDC urges the use of near real-time surveillance to effectively identify overdose incidence, and to coordinate community responses in the states affected by the epidemic, including Virginia. However, current opioid overdose datasets for Virginia lack adequate consistency, granularity, and temporality for …

Identifying Co2 Sequestration Opportunities, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about CO₂ data organization and gathering to develop promising CO₂ sequestration opportunities within the PCOR Partnership region. [This item is an outdated or superseded version and retained for historical purposes only. It may no longer reflect current information, policies, or practices.]

Fisheries Occasional Paper No. 19 - Management Of Western Rock Lobster Fishery - Proposed Resource Sustainability Management Package For The Northern Zones (A And B), Department Of Fisheries Western Australia

Fisheries Occasional Publications

The proposed effort reduction management package presented in this paper was developed in close co-operation with rock lobster industry to address the short-term sustainability concerns regarding the level of breeding stock in the northern region.

The management package does not address the serious long-term sustainability or socio-economic issues (e.g. cost pressures and related fleet capacity) facing the industry. If the fishery stays with input controls there will need to be regular reviews of the level of exploitation and its impact on the breeding stock. If exploitation increases and the breeding stock continues to decline additional fishing effort reductions in the …

Fisheries Occasional Paper No. 20 - Management Of Western Rock Lobster Fishery - Advice To Stakeholders - Assessment Of Southern Zone Resource Sustainability Options, Department Of Fisheries, Western Australia

Fisheries Occasional Publications

The management options presented in this paper have been developed in close cooperation with the rock lobster industry to address the short-term sustainability and economic concerns regarding the level of exploitation and its impact on the breeding stock in the southern region. The main focus in the short-term is to consider options that reduce fishing effort during periods that may be economically inefficient to fish and at the same time reduce the level of exploitation.

The management package does not address the serious long-term sustainability or socioeconomic issues (e.g. cost pressures and related fleet capacity) facing the industry. If the …

State Of The Fisheries Report 2003/04, J. W. Penn, W. J. Fletcher, F. Head

Status Reports of the Fisheries and Aquatic Resources

The State ofthe Fisheries Report is published annually to provide an additional level of detailed reporting of the management of fish stocks and their environment undertaken by the Department of Fisheries. A summary report from the document is included in the Department's Annual Report to Parliament, which includes the Department's non-financial (fishery) performance indicators.

By summarising management changes, compliance activities and research data including stock assessments and breeding stock levels, this document provides a valuable reference point for Western Australian fisheries of major importance to the commercial and recreational sectors, and the developing aquaculture sector.

This year's State of the …

State Of The Fisheries Report 1999/2000, J. W. Penn, Fisheries Western Australia

Status Reports of the Fisheries and Aquatic Resources

The State of the Fisheries document is designed as an essential supplement to the Annual Report to Parliament and provides a more detailed level of information to support the agency's non-financial performance measures.

By summarising management changes, compliance activities and research data such as landings, effort, catch rates, stock assessment and breeding stock levels, this document provides a valuable reference point for Western Australian fisheries of major importance to the commercial, recreational and aquaculture sectors. Information relevant to Fisheries WA's Fish and Fish Habitat Protection Program is also provided.

The report indicates that overall the major fish stocks which support …