Danial Azam

Danial Azam

Data Scientist | Software Developer

435 Marrickville Road, 2203, Dulwich Hill, New South Wales, Australia
(+61) 405 546 662



Research Software Developer at Basin Genesis Hub - University of Sydney

The BGH is an established leader in e-Geoscience services and software in a basin analysis and management context.


  • Led development and maintenance of Open-source Bayesian Inference framework in Python for Landscape modelling-Bayeslands and BayesReef.
  • Created parallelized framework run on High Performance Computers to efficiently sample multivariate parameter distributions.
  • Utilised neural networks(keras) as surrogate models to significantly curb simulation runtime with minimal losses in accuracy.
  • Coordinated multiple workshops in-house and at conferences on application of computational statistics frameworks in Geo-sciences.

Data Scientist at Engage2

“Working on thesis bla bla bla”


  • Responsible for extracting valuable insights from data collected and generated by engage2 and it’s clients.
  • Optimized Information management workflows and infrastructure by integrating existing SQL and NoSQL databases.
  • Produced reports providing analysis coupled with recommendations to meet business development goals.

Software Developer at 10Pearls

“Working on thesis bla bla bla”


  • Developed Trial Presentation software TrialMax enabling litigators with trial presentation and exhibit management.
  • Implemented critical modules such as PDF Import, Video capturing and Image processing using C# and C++.
  • Responsible for the redesign of the PDF to Image conversion architecture.

Oracle Applications Developer at Hinopak Motors Limited (Toyota Tsusho Corporation)

“Worked on Trial Max”


  • Part of team designated to extend the Oracle EBS R12 Purchasing Module to provide a self-service portal to Hinopak vendors.
  • Developed critical modules including the ability for vendors to review Requests for Quotations, Outstanding Purchase Orders, Delivery Schedules and Payment Statuses.
  • Developed web development skills by working in .NET using C# to develop the front-end and Oracle EBS Database as the back-end.


Political Sentiment Analysis Tools (NLP) at LUMS


  • Extracted Text corpus from Twitter & local political blogs to investigate relationship between political sentiments & corresponding events in a volatile country like Pakistan.
  • Reduced the dimensionality of the problem (numerous attributes to classify against) using Principal Component Analysis (PCA).
  • Used Topic modeling & Event Detection to model correlation.
  • Logistic Regression & Support Vector Machine (SVM) were used to predict sentiment based on labeled training data.
  • Analyzed & compared performance of classification models using F1 score to improve precision & recall while implementing crossvalidation for best results.
  • Conducted research on creating an Urdu (Pakistan’s national language) lexicon to include texts posted in Roman Urdu.

Quality Assurance System using ML & Computer Vision at WipeHero


  • Created automated system to assist with the auditing and Quality Assurance processes using ML & Computer Vision techniques.
  • Ensured automatic detection of the car in the image and Determination of whether quality of car wash was acceptable or not.
  • Implemented semi-supervised Learning GAN’s & Ladder Network alongside use of OpenCV for Vehicle component Detection.
  • Delivered a basic working framework that still required further improvements in order to be used as a working feature.

Freelance Business Intelligence Projects at Reliance Paint Industries (Pakistan)


  • Studied source data to assess its feasibility in fulfilling user requirements.
  • Designed and developed Extract Transform and Load (ETL) routines for initial data load and periodic data refreshes.
  • Developed a dashboard in PowerBI to fulfill business performance management and analytics needs - helping create accountability for KPI’s important to the business.


Email: rohitash.chandra@unsw.edu.au Mobile: +61 413 071 839

Dr. Rohitash Chandra


Software Development
Level: Master
  • Python
  • Java
  • C#
  • C++
  • R
Statistics and ML
Level: Master
  • Bayesian Inference
  • NLP
  • Computer Vision
  • Time series analysis
Database Management
Level: Intermediate
  • SQL
  • MongoDB
  • Cassandra
Visualisation tools
Level: Intermediate
  • Tableau
  • Qlikview
  • PowerBI
Cloud Technologies
Level: Beginner
  • AWS
  • Azure


Master in Information Technology & Information Technology Management from University of Sydney with GPA of

Bachelor in Computer Science from Lahore University of Management Sciences (LUMS) with GPA of


BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands by Computers & Geosciences

Bayesian inference provides a rigorous methodology for estimation and uncertainty quantification of unknown parameters in geophysical forward models.

Multicore Parallel Tempering Bayeslands for Basin and Landscape Evolution by Geochemistry, Geophysics, Geosystems

In this paper, we extend Bayeslands using parallel tempering with high‐performance computing to address previous limitations in Bayeslands

Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics by Environmental Modelling & Software

We present a Bayesian framework called Bayesreef for the estimation and uncertainty quantification of parameters in pyReef-Core that represent environmental conditions affecting the growth of coral assemblages in geological timescales



Coordinated workshop for installation & execution of Bayeslands framework for individuals from various technical backgrounds. Resources are available online at BayesLands Workshop


  • Won at varsity and college levels and Captained High School team
  • Completed introductory football coaching course
  • Successfully completed expeditions to the summit at Machulu La (5100 meters), Karakoram Range & peak at Deosai Plains (4050 meters)