WiDS² 2024 Annual Event
Women in Data Science - Flagship Intro Video 2024
WiDS Stillwater is independently organized by Priyadharsini Ramamurthy to be part
of the mission to increase participation of women in data science and to feature outstanding
women doing outstanding work.
Women in Data Science
WiDS Stillwater is independently organized by Priyadharsini Ramamurthy to be part
of the mission to increase participation of women in data science and to feature outstanding
women doing outstanding work.
Data Science Lecture Series
Dr. Miriam McGaugh
Title: Break the Chain - Combatting Sex Trafficking with Big Data.
Abstract: Human trafficking is an international challenge and it affects every country. The
United Nations defines it as the recruitment, transportation, transfer, harboring,
or receipt of persons by improper means (such as force, abduction, fraud, or coercion)
for an improper purpose including forced labor or sexual exploitation. It is a grave
violation of human rights. The problem has escalated as human traffickers have now
tapped into the power of online advertising. Online advertising is cost effective
and has an exhaustive reach which allows human traffickers to operate on a global
level and reach their targeted customers. Hundreds of online ads are posted on websites
such as Backpage.com where sex traffickers advertise their services. In an attempt
to tackle the problem, this project uses the power of text analytics to build a robust
model for identification and categorization of potential human and sex trafficking
ads. The talk with cover the background of trafficking, current research conducted
by OSU and other groups into the issue, and how everyone can play a part in combatting
the problem.
Dr. Kayla Loper
Title: Utilizing Predictive Models and Construct Measurement to Aide Student Success.
Abstract: You don't have to step far away from your studies to find that data science is also
used for higher education organizations to inform decisions and ultimately improve student
success. Dr. Loper will be sharing her life experience working in higher education:
her path to the Director of Data Analytics, utilizing predictive models as a practitioner,
and her research on measuring Sense of Belonging. Many predictive models such as retention
models, enrollment predictions, and predictors of academic success are utilized by
decision makers in higher education. These predictive models are often strengthened
by additional variables, which supports the work towards developing trustworthy, validated
measurement tools for various constructs. Dr. Loper will provide an overview of the
process she used to develop the University Student Belonging Scale and review the
potential it has for strengthening prediction models at the university.
Dr. Luo Xiao
Title: AI, Large Language Models and their applications in Health Informatics and interdisciplinary
research
Abstract: Recent advancements in Large Language Models (LLMs) and Artificial Intelligence (AI)
enable the extraction of crucial insights like symptoms, social determinants of health,
and interconnections among medical concepts from unstructured text data found in Electronic
Health Records (EHR) and other sources. These insights can significantly enhance clinical
decision-making and healthcare outcomes. Similarly, in fields like network security,
LLMs are being used to analyze network traffic and provide detailed analyses for intrusion
detection and prevention. This presentation will outline our recent advancements in
developing innovative computational models and applying LLM and AI techniques in clinical
research to improve healthcare outcomes. It will also cover the application of LLMs
in security and other interdisciplinary areas, addressing current challenges and future
opportunities for pioneering research.
Kim Strom
Title: The Journey to the Data
Business Domain Expertise: Complete life cycle of full-stack development; database
design, development, and implementation | data and business process modeling | data
cleaning including ETL and Data Warehouse design | IT Project Management
Technical Expertise: .NET suite of products, SQL Server, C#, HTML, CSS, Bootstrap,
SSIS, Advanced Excel, VBA Scripting
Professional Title: Instructor of Professional Practice | MSIS Assistant Department
Head
Stillwater, OK, USA