STEM Seminar Fall 2024 - Class Activities

Mon Dec 9, 2024 - 2:00-4:30 Final Conference


Fri Nov 29 - Thanksgiving Break

Fri Nov 22 - Guest Speaker
Dr. Ellie McCabe, Director at Project Data Sphere
Former NSF STEP Chemistry Scholar

Fri Nov 15 - Guest Speaker Series
Rescaling Climate Change Policy
Dr. Eric Marland, Math at Appstate

Fri Nov 8 - Resilience and Wellbeing Workshop
Relaxation and Recovery Strategies (Dr. Lee and Dr. Ginn)
Dr. Shernita Lee, Mrs. Traci Royster and Dr. Mark Ginn

Fri Nov 1 - Guest Speaker
Title: Introduction to Robotics: From Basics to Future Directions
Dr. Yeganeh Madadi, CS at Appstate

Fri Oct 25 - Sharing Undergraduate Research Experience
Dr. Andy Heckert of GES@Appstate and his Research Students

Fri Oct 18 - Resilience and Wellbeing Workshop
Avoid Thinking Traps (Dr. Lee, Dr. Ginn, and Mrs. Royster)
Dr. Shernita Lee, Mrs. Traci Royster and Dr. Mark Ginn

Fri Oct 11 - Resilience and Wellbeing Workshop
Introduction to Resilience and Optimistic mindsets (Dr. Lee/Dr. Ginn)
Dr. Shernita Lee, Mrs. Traci Royster and Dr. Mark Ginn

Fri Oct 4 - Sharing Internships and Summer Research Experiences
Lex Foote, Gabriel Wheatan, Isabela Rengifo Ramirez, and Christiana Wright

Fri Sep 27- Guest Speaker
Dr. Nii Okine, Math @ Appstate
Title: Causality-based feature selection and application to insurance analytics
Abstract: In insurance analytics, insurers use data from policies, claims, and transactions for insurance pricing, reserve estimation, and other insurance processes. With the rise of telematics, usage-based insurance, and smart homes, more detailed datasets are being collected and used. Hence, feature selection techniques are becoming more important to improve the quality of the data for estimation and prediction exercises. Traditional feature selection algorithms focus on selecting features based on their correlations with the response variable without considering causal relationships. This paper aims to establish a causality-based feature selection in the insurance literature. We employ the Hill-Climbing algorithm, a global structure learning approach, and incorporate expert knowledge to determine the causal structure of our model. To estimate the causal effect, we used Pearl’s causal inference framework. Our empirical analysis using data from a Professional Liability claims-made coverage suggests that causality-based models have potential benefits for building interpretable and robust prediction models.

Fri Sep 20- Guest Speaker
Ms. Daphine Nayebare, Mandela Washington Fellow (MWF), Appstate

Fri Sep 13 - Sharing Internships and Summer Research Experiences
Amy Zal, Blake Heckenlaible, Eli Orians, and Sitara Williams

Fri Sep 6 - Sharing Internships and Summer Research Experiences
Jesse Heath, Tayo Olofintuyi, and Miguel Moreno

Fri Aug 30 - Team Building Workshop
Dr. Tashakkori, CS@Appstate

Fri Aug 23 - First Day
Introducing new scholars.
Building the teams
Plan for the semester.

Study Halls
Mondays 5:00-8:00 Room 317,
Tuesdays5:00-8:00 Room 325 & 327 manages all the Study Halls
Dr. Tashakkori - How is your shinny rock doing?
How about the Olympics? Mondo Duplantis breaks his own WORLD RECORD for gold on Olympic stage in Paris - Go Tigers How did he do it?