Neha Arora

Neha Arora

University of Newcastle, Australia, PHD student

Newcastle, Australia

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I have over 8 years of experience in the IT field and am currently pursuing a PhD in Machine Learning in Healthcare at the University of Newcastle, Australia. I have also been honoured to receive prestigious fellowships, including the CMIE and WOS-C Scientist.

Area of Expertise

  • Environment & Cleantech
  • Government, Social Sector & Education
  • Health & Medical
  • Information & Communications Technology
  • Physical & Life Sciences

Topics

  • Healthcare AI
  • Digital Health
  • Machine Leaning
  • Databases
  • Data Science
  • Data Analytics
  • Big Data
  • Data Science & AI
  • Data Engineering
  • Data Visualization

From Equations to Animation: Building an Interactive Optimization-Algorithm Playground in Flutter

This talk walks through building a small interactive app where users can watch and compare different nature-inspired optimization algorithms (PSO, Ant Colony Optimization, Cuckoo Search) search a 2D landscape in real time, pause, step through iterations, and tweak parameters live. Beyond the visual payoff, this is a practical case study in a category of Flutter app that gets far less coverage than typical CRUD/forms content: apps built around a live simulation loop. We'll cover structuring state for a ticking simulation with Provider/Riverpod, painting thousands of moving points efficiently with a CustomPainter without dropping frames, also adding the interactive controls that mutate a running simulation safely, and packaging multiple algorithms behind a common interface so new ones can be dropped in easily.

Key Takeaways:

- A clean architecture pattern for "simulation "apps"—separating tick logic, state, and rendering
-Efficient custom painter techniques for rendering large numbers of moving elements without performance loss
-Safely mutating a live, ticking simulation from user-facing controls (sliders, pause/step buttons) without race conditions
-A pluggable algorithm pattern so the same visualization shell works for PSO, ACO, Cuckoo Search, or any future algorithm.

The 3 Gradle Mistakes That Nearly Killed My Kotlin Library's Maven Central Release

Publishing a Kotlin Multiplatform library sounds simple until you hit Gradle's publishing configuration , signing keys, Sonatype account setup, and POM metadata that silently reject your release with cryptic errors. In this lightning talk, I'll walk through the three specific mistakes that cost me the most time while taking a KMP library from local code to a real, installable Maven Central dependency and exactly what I'd do differently. A practical, no-fluff account for anyone about to publish an Android/Kotlin library.

Key Takeaways:
-The exact Gradle maven-publish + signing configuration that works for KMP (not just single-platform Kotlin)
-How to set up a Sonatype/Maven Central account and namespace correctly
- The most common POM-metadata mistake that causes silent publish rejections, and how to catch it early
-A realistic timeline for going from "library works locally" to "published and installable"

Neha Arora

University of Newcastle, Australia, PHD student

Newcastle, Australia

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