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About
is an accomplished data scientist and thought leader with over 15 years of experience in data analytics, machine learning, and AI-driven solutions. Holding a Ph.D. in Applied Statistics, Dr. Tran has worked with leading tech firms and healthcare organizations to develop innovative data models that drive strategic decision-making and improve operational efficiency. Known for her expertise in predictive modeling and her commitment to ethical AI practices, she regularly speaks at industry conferences and publishes in top journals. Passionate about mentorship, Dr. Tran dedicates time to guiding aspiring data scientists and advancing diversity in tech.
Awards
- Sample award, 2024
Affiliations
- Sample centre / division, Leader
- Sample centre / division, Researcher
- Sample group, Leader
- Sample group, Researcher
Research interests
- Predictive Modeling and Machine Learning: Developing advanced algorithms for accurate forecasting in healthcare, finance, and technology sectors.
- Ethical AI and Fairness: Focusing on reducing bias in AI models, ensuring transparency, and promoting responsible data practices.
- Data-Driven Decision Making: Exploring methods for optimizing data analysis processes to enhance strategic insights and operational efficiency.
- Natural Language Processing (NLP): Applying NLP techniques for sentiment analysis, text mining, and customer behavior understanding in real-world applications.
- Healthcare Analytics: Using data science to improve patient outcomes, streamline operations, and support personalized medicine in the healthcare industry.
Projects
- Sample project, Researcher
Teaching information
Dr. Emily Tran is a dedicated educator with a focus on equipping students with both theoretical knowledge and practical skills in data science and machine learning. She teaches courses at both undergraduate and graduate levels, including:
- Introduction to Data Science: A foundational course covering data cleaning, analysis, and visualization, aimed at building strong analytical skills.
- Machine Learning Applications: A hands-on course where students learn to build, train, and evaluate machine learning models for real-world scenarios.
- Ethics in Artificial Intelligence: A seminar-style course exploring ethical considerations in AI development, including bias mitigation, privacy, and transparency.
Dr. Tran emphasizes project-based learning, encouraging students to work with real datasets and present findings that address current industry challenges. She is highly regarded for her approachable teaching style and commitment to mentorship, guiding students through capstone projects and offering career advice for those entering the data science field.
Supervised students
Location
Office location in ANU