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Jitong **** AL/ML Engineer

$600 / day

Summary

AI/ML Engineer and PhD candidate researching fluid mechanics at the University of Melbourne. Research integrates mathematical modeling, data analysis, and programming. Possesses strong research skills in problem identification, systematic problem-solving, and academic writing.

SKills

BashC++KerasMATLABMatplotlibNumPyOpenCVPandasPythonPyTorchScikit-LearnscipyseabornSQLTensorFlow
AI ConsultantAI ProgrammerAI Software DeveloperMachine Learning Engineer

Education

Nov 2020 - Present Doctor of Philosophy at The University of Melbourne
July 2018 - July 2020 Master of Engineering at The University of Melbourne
Aug 2014 - June 2018 Bachelor of Engineering at Xi’an Jiaotong University

Experience

Aug 2020 - Present Academic Tutor at University of Melbourne

– Tutored two graduate-level courses at the Organisation: Vibration (MCEN90046) and Aeroelasticity and Advanced Fluid Dynamics (MCEN90018).
– Tutored one undergraduate level course at Newman College: Calculus 1 (MAST10005). This role encompasses delivering tutorials, marking assignments, and collaborating with
lecturers to enhance course content.

July 2023 - Oct 2023 Student Meteorologist at China Meteorological

– Completed an internship in Administration. My responsibilities included analysing large-scale climate data of satellite images, temperature and
precipitation as well as maintaining the stored data on cluster computers.
– Responsible for weather forecasting modelling using an in-house code written in Python.

Apr 2023 - Present Academic Translator at HATCH Biosystems

– Translated academic journals written in Chinese from various universities.
– Additionally, provided translation services to organisation, assisting with the operation of screeners purchased from Chinese manufacturing companies.

Oct 2021 - Oct 2021 Business Innovation Lab at Coles

– Collaborated in a four-person team to devise strategies aimed at recycling soft plastics for organisation.
– Analysed the large-scale plastics recycling data using SQL and proposed simple prediction models. Our team’s final presentation was awarded first prize.

Dec 2019 - March 2020 Research Internship at University of Melbourne

– At the organisation, applied ‘Principal Component Analysis’ to the linearised Navier-Stokes equations model to extract dominant modes in channel flows.
– Developed simulations on a supercomputer to suppress turbulence onset by targeting at the extracted modes.