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Data Science Student Showcase: Towson Edition

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Hosted By
Jason B.
Data Science Student Showcase: Towson Edition

Details

Please join us in May as we visit Towson University to hear from the next generation of data science superstars. We will be featuring several talks on a range of topics from the students of Towson University.

Agenda

6:30 PM -- Networking & Food

7:00 PM -- Greetings

7:05 PM -- Student Showcase

8:45 PM -- Conclusion

Location

Towson University
Union, Chesapeake Room
Cross Campus Dr, Towson, MD 21204

Directions

The event will be in the Chesapeake Room at the Union. More information can be found here: https://www.towson.edu/campus/landmarks/union/

Parking

Parking can be found at the University Union Garage. Please refer to the campus map here: https://www.towson.edu/maps/

Food and Drinks

Complimentary food, such as pizza and chips, and non-alcoholic beverages will be provided.

Talks

Talk: Elasticsearch for Business Intelligence and Application Insights
Speaker: Sean Donnelly
Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. In this talk, I’ll discuss the fundamentals of storage and retrieval in Elasticsearch, why we decided to use it for search in our applications, and how you can also leverage it for both business intelligence and application insights.

Talk: Machine Learning for Requirements Engineering
Speaker: Jon Patton
This project applies a number of machine learning, deep learning, and NLP techniques to solve challenging problems in requirements engineering.

Talk: An Asynchronous Distributed Deep Learning Based Intrusion Detection System for IoT Devices
Speaker: Pu Tian
Intrusion Detection Systems (IDS) in IoT devices are crucial for cybersecurity. Existing models may fail due to increased traffic pattern complexity and data complexity. To address these challenges, we propose an asynchronous distributed deep learning based IDS in which only training weights are shared and devices of heterogeneous computing power can train asynchronously. Empirical results on a large network intrusion dataset show that the system achieves high detection accuracy.

Talk: Fortune 500 Company Performance Analysis Using Social Networks
Speaker: Yi-Shan Shir
This presentation focus on studying the correlation between financial performance and social media relationship and behavior of Fortune 500 companies. The findings from this research can assist in the prediction of Fortune 500 stock performance based on a number of social network analysis metrics.

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Data Works MD
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University Union
281 University Ave · Towson, MD