Speaker

Mani Sarkar

Mani Sarkar

Self-employed, Freelance Software, Data/ML Engineer

London, United Kingdom

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Mani is a passionate developer mainly in the Java/JVM space, currently strengthening teams and helping them accelerate when working with small teams and startups, as a freelance software, data, ML engineer.

A Java Champion, JCP Member, OpenJDK contributor, thought leader in the LJC and other developer communities and involved with @adoptopenjdk, @graalvm and other F/OSS projects. Writes code, not just on the Java/JVM platform but in other programming languages, hence likes to call himself a polyglot developer. He sees himself working in the areas of core Java, JVM, JDK, Hotspot, Graal, GraalVM, Truffle, VMs, and Performance Tuning.

An advocate of a number of agile and software craftsmanship practices and a regular at many talks, conferences (Devoxx, VoxxedDays) and hands-on-workshops – speaks, participates, organises and helps out at many of them. Expresses his thoughts often via blog posts (on his own blog site, DZone, Medium and other third-party sites), and microblogs (tweets).

Area of Expertise

  • Information & Communications Technology

Topics

  • java
  • jvm
  • graal
  • graalvm
  • truffle
  • performance tuning
  • viritualisation
  • Polyglot Programming
  • Docker
  • python
  • JavaScript
  • NodeJS
  • bash
  • Artificial Intelligence
  • Machine Learning
  • Data Science
  • Data
  • Deep Learning

Naturally, getting productive with Grakn and Graql!

Over the period of so many weeks and month I have learnt lots about Graknlabs. The two core components I have been learning about Grakn and Graql. In this two-part talk, we can get productive and save compute and human-resources when using Grakn and Graql with added batteries. This is only possible due to the design and technical decisions made by the team which takes advantage of the current and future advancements made on the JVM i.e. GraalVM.

In the latter half, we will see how we can use and speak Graql just like we would be speaking to another human. We will explore English-to-Graql and vice-versa, basically using natural language to communicate with this novel graph engine called Grakn (this all started from a meetup and a few Github issues)! Time permitted we could explore both English-to-Graql and Graql-to-English.

Mani Sarkar

Self-employed, Freelance Software, Data/ML Engineer

London, United Kingdom

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