Age, Biography and Wiki

Julian Adam Wise was born on 29 October, 1990 in Melbourne, is an Australian Technology Leader. Discover Julian Adam Wise's Biography, Age, Height, Physical Stats, Dating/Affairs, Family and career updates. Learn How rich is he in this year and how he spends money? Also learn how he earned most of networth at the age of 33 years old?

Popular As Julian Adam Wise
Occupation Technical Lead · Principal (IT) · Senior Architect
Age 33 years old
Zodiac Sign Scorpio
Born 29 October, 1990
Birthday 29 October
Birthplace Melbourne
Nationality

We recommend you to check the complete list of Famous People born on 29 October. He is a member of famous Architect with the age 33 years old group.

Julian Adam Wise Height, Weight & Measurements

At 33 years old, Julian Adam Wise height not available right now. We will update Julian Adam Wise's Height, weight, Body Measurements, Eye Color, Hair Color, Shoe & Dress size soon as possible.

Physical Status
Height Not Available
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Dating & Relationship status

He is currently single. He is not dating anyone. We don't have much information about He's past relationship and any previous engaged. According to our Database, He has no children.

Family
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Wife Not Available
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Julian Adam Wise Net Worth

His net worth has been growing significantly in 2023-2024. So, how much is Julian Adam Wise worth at the age of 33 years old? Julian Adam Wise’s income source is mostly from being a successful Architect. He is from . We have estimated Julian Adam Wise's net worth, money, salary, income, and assets.

Net Worth in 2024 $1 Million - $5 Million
Salary in 2024 Under Review
Net Worth in 2023 Pending
Salary in 2023 Under Review
House Not Available
Cars Not Available
Source of Income Architect

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Timeline

1990

Julian Adam Wise (born October 29, 1990) is an Australian technical lead and Innovator best known for leading the building of AI Platforms for multi-national companies, contributions to spatial technologies, and as a pioneer of MLOps as an AI methodology.

Wise demonstrated the ability of his AI Platform's to rapidly scale time-to-delivery for AI Models, within the field of Machine Learning Operations (MLOps).

Wise also heavily contributed to Geospatial Intelligence through the co-founding of CSIRO's VoxelNET Program.

Wise's contributions to Science, Technology, and Business have spanned over Mining Technology, Robotics, Artificial Intelligence and Industrial Software Systems.

Wise was born and raised in Melbourne, Australia.

Wise's mother's side of the family through Godfrey Cohen draws their arrival to Australia to the larger Solomon family and Cashmore Family of Australian Jewish pioneers, amongst whose descendants many achieved a degree of notability.

During his studies of Software Engineering, Wise worked with CSIRO, the Australian national science agency on AI to place a cognitive architecture onto drones for autonomous cave exploration and simulation.

The intellectual property generated was collected by CSIRO and commercialized into the Emesent program.

After working in Israel, Julian accepted a role with Mining3, a private Mining Research Institute in collaboration with CSIRO.

During this time, Wise published with Cambridge University Press on Legal Smart Contracts for derivative trades of mineral stockpiles.

As a professional consultant, Wise commenced as an AI engineer with Newcrest Mining, to build AI Platforms and productionise machine learning models on said platforms.

It was during this time that Wise created three AI platforms within the sub-field of MLOps for Newcrest.

One to production models in Azure with Python, one open source MLFlow Platform for the life-cycle management of AI models produced in R, and one to productions custom modified Kubeflow platform to production models produced in MatLab.

Wise achieved Consultant of the Year in 2021 with the Fortune 500 Organisation he was employed by, Insight Enterprises.

During this period, Julian relocated to South America to build the AI Platform for BHP's Latin American operations.

The platform was hallmarked as revolutionary and improved the time to deliver solutions from months to weeks.

The features included automated retraining, model cataloging, performance cataloging, performance-to-model-to-code lineage.

During this time Wise authored the AI and Machine Learning Global Technology Standards, to govern the management of BHP's AI models over their operational lifecycle.

The methodology was validated with a challenge to deliver a project which would normally take twelve months, to deliver in twelve weeks.

The project was a decisive success and the uplift in copper recovery for Escondida Mine was demonstrated with the outcomes published to a peer-reviewed scientific journal of the value generated through Copper Concentrator optimizations.