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Feb 23, 2019
Topic Modeling Using Latent Dirichlet Allocation
Portland Community Church

Philip Robinson will be presenting research whilst at NASA on Topic Modeling.

Topic modeling is the task of taking a collection of objects and establishing a strategy for describing these objects by common categories found across the collection. This is usually an unsupervised activity applied to a document collection and doesn't require topics to be human interpret-able. My talk introduces Latent Dirichlet Allocation, as a topic modeling strategy for a collection of topics, and discusses an implemented prototype system I developed for NASA's Jet Propulsion Lab. For this project, I addressed the "Matchmaker's Problem" in the context of identifying the best employee to solve a mission-critical engineering anomaly in late-stage missions. The long-form presentation can be found here

If you would like to join the discussion check us out on Zoom

Do you want to learn and share your passion in a supportive community? Knowledge Mavens is an ethos of sharing, creativity, and inspiration.

Our Meetup provides an opportunity to "Show and Tell" followed by feedback and Q&A. You'll have the opportunity to share with our channels such as Meetup, GitHub, YouTube, and Facebook to connect with more passionate people.

The second half of our session we'll collaborate on new topics. The winner wins an award for the most interesting topic and the opportunity to share in an upcoming session.

Oct 22, 2020
DAMA Day 2020: "Data... In SPACE!" with NASA Scientists, sponsored by Snowflake

Presented by NASA Scientists Sponsored by Snowflake

Calling all data enthusiasts and/or space nerds in Portland, Oregon and beyond. Join us for an exciting, all-day virtual event with NASA scientists. Attendees will work with actual NASA data and have an opportunity to collaborate on matters of data analysis directly with our presenters.

Opening Remarks: 8:30 AM: DAMA PDX Board

Morning Session: 9AM – 11:30 AM: Eric Lyness and Victoria Da-Poian, NASA

Eric Lyness is the NASA software and operations lead at Goddard Space Flight Center for the Mars Organic Molecule Analyzer on the ExoMars 2020 rover and Victoria Da-Poian is an Aerospace Engineer. They will present their talk, Machine Learning to Find Life on Mars and Beyond.

In 2021 the European ExoMars rover will land on Mars with the Mars Organic Molecular Analyzer (MOMA) laboratory to analyze soil samples searching for past or present life. NASA is developing machine learning algorithms to help the scientists more quickly analyze the data when it arrives from Mars. In this talk, we will present the current work using MOMA mass spectrometer data acquired during ground testing. Using this data we are aiding the scientists by matching new spectra with the most similar spectra from past experiments. We will present the nuances of mass spectra, our limitations with respect to data, and our approach to the problem. We hope to elicit feedback from the attendees.

More details at

30 minute Break

Lunch Session: 12:00 – 1:00 PM: Snowflake Presentation, Drew Swanson and Brian Whittington

30 minute Break

Afternoon Session: 1:30 PM – 3:30PM: Details soon!

15 minute Break

Closing Remarks and Next Steps: 3:45 – 4:00 PM: DAMA PDX Board

Times above may be revised in the days before our event.

Event will be presented via a Zoom bridge. Analytical discussions and collaboration will be hosted via a Slack workspace that will begin on event day and last for a few weeks afterwards. This is a BYOAE (bring your own analytical environment). However, attendees will have access to the data via Snowflake and to notebook templates via Zepl.

Pre-event tasks for analysis setup will be shared on 10/19 via email.

Date – Thursday, Oct. 22nd Time – 8:30 – 4:00pm

NOTE: This is an all day event