Final List of confirmed talks (in order of presentation):

1. An Introduction to Solr & latest developments in Solr 7 - Vrinda Davda, Lucidworks Inc.
2. Graph Traversal for Significantly Related Terms (Semantic Knowledge Graph) in Apache Solr -- Amrit Sarkar, Lucidworks Inc.
3. Learning to Rank in Solr - Swapnil Chaudhari, Myntra
4. Search on Steroids: Hardware acceleration for Lucene -- Ishan Chattopadhyaya, Committer & PMC Member, Apache Lucene/Solr & Kishore Angani, Principal Search Architect, Unbxd

In case you want to present a session at a future event, please send a message to the organisers.

Talk #1:

Title: An Introduction to Apache Solr & latest developments in Solr 7

Description: This is a getting started talk that will aim to briefly introduce beginners to Solr with focus on the latest features in Solr 7

Speaker Bio: Vrinda is Search Engineer and Consultant working at Lucidworks Inc

Talk #2:

Title: Graph Traversal for Significantly Related Terms (Semantic Knowledge Graph) in Apache Solr.

Description:
The Semantic Knowledge Graph (SKG) is an Apache Solr plugin that can be used to discover and rank the relationships between any arbitrary queries or terms within the search index. It is a relevancy swiss army knife, able to discover related terms and concepts, [https://github.com/careerbuilder/semantic-knowledge-graph] contributed by CareerBuilder and discussed by Trey Grainger, SVP of Engineering at Lucidworks at Activate 2018 [https://activate2018.sched.com/event/Fk8W/how-to-build-a-semantic-search-system]. This short talk will cover the broader concept of SKG and developments done in version 7.4 [SOLR-9480] where the SKG capabilities are infused into JSON Faceting.

Speaker Bio:
Amrit Sarkar is Search Engineer and Consultant at Lucidworks Inc, California-based enterprise search technology company, with 3+ years experience in search domain and big data, e-commerce and product. LinkedIn: https://www.linkedin.com/in/sarkaramrit2

Talk #3:

Title: Learning to Rank in Solr

Description: In the past decade,Learning to Rank (LeToR) methods have been tried and studied for optimising search engine ranking. Learning to Rank module introduced from Solr 6.6 allows us to configure and run machine learned models to rerank top N documents. In this talk, we explore what Solr LTR plugin has to offer, how we customise the framework to add support for external query document features. We also talk about challenges we faced while scaling the system and their solutions.

Speaker Bio: Swapnil is an SSE in Search team at Myntra. He works on relevance and performance improvements in Search.

Talk #4:

Title: Search on Steroids: Hardware acceleration for Lucene

Description:
In this talk, we discuss opportunities for speed up using GPU acceleration in Lucene and Solr/ES. We discuss initial results and road ahead.

Speaker(s) Bio:
Ishan Chattopadhyaya is a committer and PMC member for Apache Lucene and Solr & Kishore Angani, Principal Search Architect, Unbxd