Jason Barbour, Matt Motyka, and Sean Murphy bring you the Mid Maryland Data Science Meetup's First Event

Do you love Data Science but just can't get into the District for one of the many amazing data science events after work? I am happy to announce that the brand new Mid Maryland Data Science Meetup group has been kicked off by yours truly, Jason Barbour, and Matt Motyka.  Even more exciting, the first meetup, a Data Science Kickoff, will be held Tuesday, January 29th, at the Johns Hopkins University Applied Physics Laboratory in Columbia, MD.  For more information, see below.



The Meetup

The Mid-Maryland Data Science group is intended to be a gathering of professionals, students, and enthusiasts in the area to discuss diverse topics related to data science. We aim to have frank discussions on all topics related to the field of data analytics. No subject is too big or too small, as we believe analytics can operate on any scale. We plan to mix education with practical examples, helping attendees maximize their time.


The Event!

Called the sexiest job of the 21st century, data scientists increasingly are changing industry, government, and academia. As the data science field grows, the need for a supportive community increases. Come help us build a local group to share relevant knowledge and bring enthusiasts together. For our first meetup, we will introduce ourselves and our vision for the group. Next, Sean will discuss data products and Harlan will present the results of a data science survey. We will end with a presentation on the experiences of an active practitioner.

  • 6:00 PM -- Networking, Food, and Drinks
  • 6:30 PM -- Greetings and Mission - Jason Barbour & Matt Motyka
  • 6:50 PM -- The Rise of Data Products - Sean Murphy
  • 7:10 PM -- The Variety of Data Scientists - Harlan Harris
  • 7:30 PM -- Main Presentation
  • 8:00 PM -- Time for Drinks


The Rise of Data Products - So, exactly why is data science so hot? Why now? Don't scientists from all fields collect and use data? And what exactly is a data product? And why are scientists making products? This talk will weave together a number of disparate threads to not only answer these questions but also provide some possible insights into the future of the field (and career strategies).

The Variety of Data Scientists - The term "data scientist" is unclear, leading to miscommunication and lost opportunities. I will review how a variety of previously useful terms for data-related professions came to be chewed up by the buzzword meat grinder, then will discuss some alternatives. Based on original survey research, I will demonstrate some new underlying categories of data scientist that may lead to greater understanding of the new field and more efficient communication for practitioners, educators, and organizations.

Cloudera Impala - Closing the near real time gap in BIGDATA - The Near Real Time Analytic capability that Cloudera Impala provides is essential in many high value use cases associated with Cyber Security: comparing current activity with observed historical norms, correlation of many disparate data sources/enrichment and automated threat detection algorithms.


Wayne Wheeles is a Senior Network Forensics Analytic/Enrichment Developer (CND-OPS). Over the last decade, Wayne has worked on the Cyber Security problem in a variety of roles as an analytic developer, framework developer, system architect and data engineer.

Wayne is an advocate, practitioner and developer for open-source Cyber Security Solutions. He is a specialist in the area of BIG DATA and Analytics applied in the Cyber Security domain. He has developed and delivered solutions for a variety of customers across Federal Government space. Wayne has been a member of the Six3 Systems Cyber Security team for three years.

Harlan Harris has a PhD in Computer Science (Machine Learning) from the University of Illinois at Urbana-Champaign, and post-doctoral work in Cognitive Psychology at several universities. He currently is Senior Data Scientist at Kaplan Test Prep, President of Data Community DC, Inc, and co-organizes Data Science DC.

Sean Patrick Murphy, with degrees in math, EE, and biomedical engineering and an MBA from Oxford, has served as a senior scientist at JHUAPL for over a decade. Previously, he served as the Chief Data Scientist at a series A funded health care analytics firm, and the Director of Research at a boutique graduate educational company. He has also cofounded a big data startup.

Jason Barbour is a software engineer at Varen Technologies, focused on developing analytics for large data sets using tools such as Hadoop, Pig, and Accumulo. Previously, Jason worked as a network analyst for computer network operations. Jason holds a Master of Computer Science degree from UMBC where he concentrated on sensor network connectivity and security analysis.

Matt Motyka is a computer scientist who has spent the last 9 years as a consultant to the Department of Defense. He previously worked for L-3 Communications and now works for Six3 Systems developing software for both traditional and big data platforms. Matt obtained his BS in Computer Science at the University of Maryland College Park and has an MS in Computer Science from Johns Hopkins University focusing on networking and telecommunications.