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ChangWei *** AI/ML Researcher

$840 / day


ChangWei Tan is a distinguished researcher and machine learning specialist based at Monash University, Australia. He holds a PhD in Information Technology and a Bachelor of Engineering with First Class Honours in Wireless Sensor Networks from the same institution. ChangWei’s career spans roles as a Research Fellow in Machine Learning, a Consultant at Stemly PTE LTD, and various academic positions at Monash University. His expertise lies in scalable time series classification and regression, with notable contributions to supply chain forecasting and epilepsy diagnosis using machine learning. ChangWei is recognized for his extensive publication record in top-tier journals and conferences, and he actively contributes to the academic community as a reviewer and committee member for leading conferences in data science and machine learning.


Algorithm DesignArtificial IntelligenceComputational Cultural UnderstandingData AnalysisData ScienceDeep LearningEEG AnalysisExcelFeature EngineeringMachine LearningMATLABMulti-modal Data AnalysisPythonRegression AnalysisResearch and DevelopmentSignal ProcessingSupply Chain ForecastingTime Series ClassificationWireless Sensor Networks
AI ConsultantData ScientistDeep Learning EngineerMachine Learning Engineer


Apr 2019 Doctor of Philosophy (PhD) at Monash University,
May 2015 Bachelor of Engineering at Monash University


June 2019 - Current Data Science and Machine Learning Consultant at Stemly PTY LTD

– Led the design and implementation of machine learning models tailored to client-specific needs, focusing on supply chain forecasting and inventory optimization for diverse
– Advised on data-driven decision-making processes by leveraging advanced statistical analysis and predictive modeling techniques, resulting in improved operational efficiencies
and cost reductions.
– Collaborated closely with cross-functional teams to interpret complex data sets, extract actionable insights, and communicate findings to stakeholders at all levels,
facilitating informed business strategies.
– Contributed to the development of custom algorithms and tools for automated data processing, anomaly detection, and real-time monitoring systems, enhancing overall business
intelligence capabilities.
– Conducted workshops and training sessions on data science methodologies, including machine learning algorithms and model validation, to empower teams and foster a culture of
data-driven innovation within client organizations.
– Acted as a technical lead on multiple projects, overseeing project lifecycle from requirement gathering and solution design to implementation and post-deployment support,
ensuring alignment with client objectives and timelines.

Sept 2019 - Current Research Fellow (Machine Learning) at MONASH UNIVERSITY

– Conducted cutting-edge research in machine learning algorithms and techniques, with a focus on time series classification and regression, contributing to advancements in
scalable and interpretable models.
– Collaborated with interdisciplinary teams to formulate research hypotheses, design experiments, and analyze complex datasets using statistical methods and machine learning
– Published research findings in reputable journals and presented at international conferences, establishing credibility and contributing to the academic discourse in the field
of machine learning.
– Developed and implemented novel machine learning algorithms for real-world applications, such as healthcare monitoring systems and predictive analytics for financial markets,
demonstrating the practical impact of research outcomes.

Apr 2019 - Aug 2019 Research Assistant at MONASH UNIVERSITY

– Assisted senior researchers in conducting literature reviews, compiling research data, and performing statistical analysis using tools like Python, R, or SPSS.
– Designed and executed experiments, collected and processed data, and maintained detailed records of experimental procedures and outcomes to ensure reproducibility.
– Contributed to writing research proposals, grant applications, and progress reports, demonstrating strong organizational skills and attention to detail.
– Participated in team meetings and collaborated with interdisciplinary researchers to brainstorm ideas, troubleshoot problems, and contribute to project planning and execution.

July 2015 - Dec 2018 Teaching Associate at MONASH UNIVERSITY

– Course Instruction: Delivered lectures, conducted tutorials, and led laboratory sessions for undergraduate courses in [specific subject area]. Provided clear explanations of
complex concepts, fostering student engagement and comprehension.
– Curriculum Development: Contributed to the design and updating of course materials, including lecture notes, assignments, and assessment criteria. Incorporated innovative
teaching methodologies and real-world examples to enhance learning outcomes.
– Student Assessment: Designed and graded assignments, quizzes, and exams, ensuring fair and consistent evaluation of student performance. Provided constructive feedback to
students to support their academic growth and development.
– Student Support: Held regular office hours to provide academic support and mentoring to students. Addressed student inquiries, clarified course content, and guided students in
understanding difficult concepts.