Conferences

We like to attend conferences to learn about industry advancements and to learn from the community and to share our work with the community. Conferences are a wonderful opportunity to engage with other individuals and teams involved with similar projects and to learn from each other. We attended the following conferences and community events.

If one of our team members met you at a conference please don’t let that be the end of our interaction! Stay in touch because we love hearing about the community’s continuing work.

2019 Strata Data in New York, NY, USA

Upcoming! Description of the presentation.

2019 Lucidworks Activate in Washington DC, USA

Upcoming! Description of the presentation.

2019 Dataworks Summit in Washington DC, USA

The Dataworks Summits are excellent events that focus on big-data. Topics include managing big-data, analysis, and many more. At this event we presented a method of ingesting and processing natural language text using Apache NiFi, Apache OpenNLP, and Apache Kafka.

2018 PyData in McLean, VA USA

PyData events allows users of the Python ecosystem to share technologies and methods related to the use of Python ecosystem for data analysis. There is always a wide array of interesting topics. At this PyData event we shared how the Sockeye neural machine translation toolkit can be used from Apache Flink to translate streaming text.

2018 Lucidworks Activate in Montreal, Canada

The Activate conference revolves around search and AI technologies such as Apache Solr and Apache Lucene. At this conference we presented a method for cross-lingual information retrieval using Apache NiFi.

2018 Xavier AI Summit in Cincinnati, Ohio USA

This conference focuses on AI’s role in healthcare. We attended this conference to learn more about the issues around AI products and services in a healthcare environment.

2018 Haystack Search Relevance in Charlottesville, VA USA

The Haystack Search Relevance Conference brings together the community interested in search relevance. Search relevance is such an important topic because getting users the information they need quickly is of the highest importance. Techniques such as learning to rank bridges the gap between machine learning and search relevance.